- Email: [email protected]
Wound Disruption after Lower Extremity Bypass Surgery is a Predictor of Subsequent Development of Wound Infection
Accepted Manuscript Wound Disruption After Lower Extremity Bypass Surgery is a Predictor of Subsequent Development of Wound Infection Faisal Aziz, MD, FACS, Tiffany Bohr, Erik B. Lehman, MS PII:
S0890-5096(17)30381-3
DOI:
10.1016/j.avsg.2016.10.065
Reference:
AVSG 3208
To appear in:
Annals of Vascular Surgery
Received Date: 29 June 2016 Revised Date:
17 October 2016
Accepted Date: 20 October 2016
Please cite this article as: Aziz F, Bohr T, Lehman EB, Wound Disruption After Lower Extremity Bypass Surgery is a Predictor of Subsequent Development of Wound Infection, Annals of Vascular Surgery (2017), doi: 10.1016/j.avsg.2016.10.065. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Wound Disruption After Lower Extremity Bypass Surgery is a Predictor of Subsequent
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Development of Wound Infection
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Faisal Aziz MD, FACS1, Tiffany Bohr2 and Erik B. Lehman MS3
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Division of Vascular Surgery, Penn State Heart and Vascular Institute, Pennsylvania State University College of Medicine.
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Office of Medical Education, Pennsylvania State University, College of Medicine. Department of Public Health Sciences, Pennsylvania State University, College of Medicine.
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Correspondence to:
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Faisal Aziz MD, FACS. Penn State Milton S. Hershey Medical Center, 500 University Drive Mail Code H053, Room C4632 Hershey, PA 17033 Tel: 717-531-8898 Fax: 717-531-4151 E-Mail: [email protected]
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ACCEPTED MANUSCRIPT 2 ABSTRACT
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Objectives: Despite advances in endovascular surgery, lower extremity arterial bypass (LEB)
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remains the gold standard treatment for severe, symptomatic Peripheral Arterial Disease (PAD).
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With recent changes in healthcare, there has been an increasing emphasis on reducing the
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hospital length of stay (LOS). The purpose of this study is to identify the postoperative
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complications, which occur after discharge from hospital, and to find risk factors for developing
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such complications.
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Methods: The 2013 lower extremity revascularization –targeted American College of Surgeons
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(ACS-NSQIP) database and generalized 2013 general and vascular surgery ACS-NSQIP PUF
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were used for this study. Patient, diagnosis, and procedure characteristics of patients undergoing
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LEB were assessed. Postoperative complications were identified and their relationship to the
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median discharge date. Univariate and Multivariable analyses were performed to identify the
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risk factors associated with developing these complications. A prediction model was then
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created to accurately predict the risk of developing such complications.
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Results: A total of 2646 patients (65% male, 35% female) were identified in the NSQIP database
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that underwent LEB during the year 2013. Median LOS was 6 days. Most common significant
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complications after hospital discharge were: Wound infection/complication (13.7%. Mean Days
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from Operation (MDAO) = 15 days), wound disruption/dehiscence (1.6%. MDAO = 15 days)
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and organ space SSIs (0.6%. MDAO = 16 days). Multivariable analysis showed these factors
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associated with wound infection: Wound disruption/dehiscence (OR 16, CI 7.09-36.07,
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p<0.001), organ space infection (OR 9.63, CI 2.71-34.25, p<0.001), unplanned reoperation (OR
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3.86, CI 2.85-5.24, p<0.001), UTI (OR 2.79, CI 1.28-6.05, p=0.010), BMI≥40 vs. <25 (OR 2.28,
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CI 1.18-4.39, p<0.001), Post-operative bleeding requiring a transfusion (OR 2.03, CI 1.49-2.78,
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ACCEPTED MANUSCRIPT 3 p<0.001), Operation time >300 min. vs. 0-170 min. (OR 1.98, CI 1.32-2.96, p=0.008), Prior
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ipsilateral percutaneous intervention involving currently treated segment vs Prior ipsilateral
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bypass involving currently treated segment (OR1.98, CI 1.30-3.01, p=0.004), history of COPD
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(OR 1.73, CI 1.21-2.48, p =0.003) and total length of stay (LOS) ≥28 days vs. <7 days (OR 1.21
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CI 0.60-2.48, p=0.014). The risk prediction model for developing wound infection is listed
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below.
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Conclusions: Wound infection is the most common complication after LEB. Most of these
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complications occur after discharge from hospital. Patients with risk factors for developing
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wound infections should be followed and closely monitored after discharge from the hospital.
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ACCEPTED MANUSCRIPT 4 1 2 Introduction
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Surgical site infections (SSIs) are among the most complications after any surgical operation.
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Recent changes in health care reimbursement structure incentivize hospitals to reduce the length
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of hospital stay (LOS). One of the disadvantages of minimal LOS is inability of health care
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providers to assess the patients for development of any postoperative complications. Many of
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such clinical signs and symptoms can be detected at an early stage by performing vigilant
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physical examinations and can be potentially prevented from developing into serious
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complications. Once developed, SSIs can be a source of serious morbidity and may lead to
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increased postoperative pain, systemic complications, return to the operating room, prolonged
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length of hospital stay and readmission to the hospital1,2. It is estimated that wound infections
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count for 38%3,4 of all post operative complications and contribute to approximately 20,000
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preventable deaths every year4-7. Wound complications after surgical operations may cost up to
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$3 billion every year5-7. Recognizing the medical and financial impact of such complications has
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lead to nationwide efforts, including Surgical Care Improvement Project (SCIP) with the goal of
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improving surgical care by reducing postoperative complications. Institute of Medicine released
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a report on medical errors in 19998 and since then, there has been an increasing public demand9
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for prevention of postoperative complications. According to a recent estimate, up to 66% of all
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hospital adverse events are related to surgery and majority of these events are considered
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preventable10-13. Patients with peripheral arterial disease who need open surgical bypasses
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represent a cohort of patient population which has multiple severe systemic illnesses and are
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prone to developing numerous postpone complications, which may require further treatment,
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ACCEPTED MANUSCRIPT 5 operations or readmission to hospital14. Lower extremity bypasses are technically demanding
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operations, which involve a series of steps, which require paying meticulous attention to minor
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details. Proponents of endovascular therapy site risk of surgical site infection after lower
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extremity bypasses as one of the reasons to avoid open surgery in patients with symptomatic
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peripheral arterial disease15. With increasing health care scrutiny, it is essential to determine the
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nationwide incidence of surgical site infections among patients undergoing lower extremity
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bypasses, the relationship to the day of discharge from the hospital and to analyze the factors
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associated with high risk of developing surgical site infections in this group of patients.
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Reimbursement agencies hold hospitals accountable for major postoperative complications. In
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the recent past, development of sacral decubiti, urinary tract infections and blood stream
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infections during hospital stay have become targets for measuring physicians’ and institutional
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performance and have been tied to reduced financial reimbursements. It is highly likely that
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wound infections will be added to the list of preventable events in near future. Determining the
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factors associated with deep wound infections after lower extremity bypasses has important
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medical and financial implications.
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ACCEPTED MANUSCRIPT 6 1 2 Methods
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Data set: The American College of Surgeons (ACS) has created National Surgical Quality
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Improvement Program (NSQIP) Participant Use File (PUF)16 , which is a de-identified dataset.
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It is compliant with Health Insurance Portability and Accountability Act (HIPAA). The number
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of participating institutions has gradually increased over the course of past decade. Systemic
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sampling method used to extract data from NSQIP database has been described previously17-21.
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Briefly, general and vascular surgical operations are divided into 8-day cycles. At each NSQIP
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site, the first forty operations performed within each 8-day that meet program inclusion criteria
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are entered in the database. NSQIP ensures heterogeneity by limiting the number of cases per
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cycle for certain higher volume and lower risk surgeries. Personnel trained specifically for
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NSQIP at each site are responsible for data collection. Studies showing outcomes based on
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NSQIP database have been shown to be highly reliable with minimal disagreements during
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annual audits19. To ensure complete follow-up, patients with incomplete 30-day outcomes are
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excluded from the database. Since there are no patient identifiers in NSQIP database, no
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Institutional Review Board (IRB) approval or patients’ consent was required.
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Patients: All patients who underwent any infra-inguinal lower extremity open revascularization
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procedure during the year 2013, using Procedure Targeted Participant User File16 from NSQIP
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database. Using unique case identification numbers, this file was merged to the main ACS
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NSQIP adult Participant Use Data File. Any patient who presented with revascularization of
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bilateral limbs in the same calendar year was deleted from the data set.
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ACCEPTED MANUSCRIPT 7 Outcomes: Primary outcome was to identify the most common complications after surgery.
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Secondary outcome was to identify factors associated with wound infection. Basic demographic
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data were analyzed including age, gender, race, and body mass index range. Several peri-
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operative variables were analyzed: operative times, length of hospital stay, type of operation,
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symptoms, high risk physiologic factors, high risk anatomic factors (defined as prior ipsilateral
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percutaneous intervention involving currently treated segment or prior ipsilateral bypass
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involving currently treated segment), pre-operative symptoms, pre-operative use of aspirin, pre-
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operative use of beta-blockers, pre-operative use of statins, need for amputation, significant post-
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operative bleeding, post-operative myocardial infarction, post-operative stroke, untreated loss of
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patency, wound infection, pre-operative albumin, number of days from hospital admission to
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operation, type of anesthetic, American Society of Anesthesiology (ASA) classification, diabetes
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mellitus, end-stage renal disease, emergency operation, congestive heart failure, chronic
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obstructive pulmonary disease (COPD), hypertension, post-operative renal failure, need for re-
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operation, history of smoking, surgeons’ specialty, need for blood transfusion, transfer status,
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urinary tract infection, wound classification, cardiac arrest, wound disruption/dehiscence,
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pneumonia and need for re-intubation (Please refer to Appendix for definitions of these
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variables).
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Statistical Analysis: All variables were initially summarized with frequencies and percentages or
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means, medians, and standard deviations. A sign test was used to test for differences between
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the median days from operation for each complication and the median length of stay (6 days).
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Logistic regression was used to determine any bivariate associations of independent variables
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with wound infection. Odds ratios were used to quantify the magnitude and direction of any
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significant associations. The significant (p<0.05) independent variables from the bivariate
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ACCEPTED MANUSCRIPT 8 analysis were then used in a process of stepwise selection to find the group of variables
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collectively that were most significantly associated with significant post operative complications
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in a multivariable logistic regression model. With so many variables and a large sample size, a
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more stringent entry criteria of p<0.05 and a stay criteria of p<0.05 were used for the stepwise
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process of variable selection to be more conservative. Forward and backward selection methods
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were also employed to check for other potential models, but the three approaches resulted in
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similar reduced models. The fit of the final model was checked using the Hosmer and
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Lemeshow goodness-of-fit test (p=0.1017). The c-statistic (c=0.753) was used to estimate the
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prediction strength of the final model. All analyses were performed using SAS version 9.4 (SAS
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Institute, Cary, NC).
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Demographics and preoperative comorbidities: A total of 2,646 patients (65% Males, 35%
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Females) underwent lower extremity revascularization operations in the year 2013. Mean age
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was 67.7 (± 11.3) years. Median length of hospital stay was 6 days.
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Post-operative complications: The incidence of post-operative complications are as follows:
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wound infection (13.7%), untreated loss of patency (1.9%), urinary tract infection (1.7%), wound
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disruption/dehiscence (1.6%), DVT/Thrombophlebitis (0.9%), organ space SSI (0.6%),
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pulmonary embolism (0.2%), post-op bleeding requiring a transfusion (17.2%), MI/stroke
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(3.1%), myocardial infarction (2.3%), pneumonia (1.3%), cardiac arrest requiring CPR (0.8%),
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progressive renal insufficiency (0.6%), acute renal failure (0.6%), stroke/CVA (0.6%).(Table I).
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Timing of complications after lower extremity bypass surgery: The three significant wound
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complications (p<0.05) occurred well after the median discharge of 6 days: Wound infection
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occurred at day 15 after surgery (range: 10-22 days), wound disruption/dehiscence also at day
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15.0 (range: 14.0, 21.0) and organ space SSI at 16.0 days following surgery (range: 14.0, 23.0)
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(Table I).
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Independen t variables associated with wound infection: Since wound infection was the most
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common complication after lower extremity bypass surgery, attention was focused on the
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patients who developed this complication. Patients were divided into two groups: no wound
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ACCEPTED MANUSCRIPT 10 infection (N=2284) and wound infection (N=361) groups. The following variables were found
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to have a significant association with wound infection: higher BMI 30-<40 (OR 1.88 CI 1.41-
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2.51), BMI ≥40 (OR 2.37, CI 1.37-4.12, p<0.05), non-insulin dependent diabetes mellitus (OR
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1.37, CI 1.06-1.77, p<0.05), severe COPD (defined as emphysema and/or chronic bronchitis
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resulting in any one or more of the following: -Functional disability from COPD (e.g., dyspnea,
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inability to perform ADLs) -Hospitalization in the past for treatment of COPD -Requires chronic
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bronchodilator therapy with oral or inhaled agents. -An FEV1 of <75% of predicted on
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pulmonary function testing) (OR 1.51, CI 1.12-2.03, p<0.05), hypertension requiring medication
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(OR 1.5, CI 1.08-2.08, p<0.05), contaminated wound classification (OR 2.15, CI 1.00-4.61),
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open wound at the time of operation (OR 1.43, CI 1.14- 1.79, p<0.05), longer operative times
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(for operative time more than 300 minutes, OR 2.16, CI 1.57-2.97, p<0.05), cardiac surgery as
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surgeon’s specialty (OR 12.43, CI 2.27-68.13, p<0.05), length of hospital stay ≥ 28 days (OR
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2.88, CI 1.70-4.90, p<0.05), need for amputation (OR 1.78, CI 1.07-2.95, p<0.05), post operative
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bleeding (OR 2.42, CI 1.88-3.12, p<0.05), combined MI and stroke (OR 1.85, CI 1.08-3.16,
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p<0.05), untreated loss of patency (OR 2.52, CI 1.35-4.72, p<0.05), need for re-operation (OR
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4.52, CI 3.53-5.77, p<0.05), wound disruption/dehiscence (OR 17.78, CI 9.04-34.96, p<0.05),
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organ space SSI (OR 15.66, CI 5.48-44.70, p<0.05), progressive renal insufficiency (OR 2.90, CI
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1.00-8.40, p<0.05), post-operative UTI (OR 3.26, CI 1.74-6.12, p<0.05) and re-admission (OR
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8.54, CI 6.68-10.92, p<0.05) (Table II).
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The following factors were found to have no significant association with wound infection: age,
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gender, race, presenting symptoms, high risk physiologic factors, pre-operative use of aspirin,
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pre-operative use of beta blockers, pre-operative use of statins, dialysis dependence, emergency
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operation, history of congestive heart failure, smoking, transfer status, pre-operative urinary tract
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ACCEPTED MANUSCRIPT 11 infection, albumin levels, number of days from hospital admission to operation, presence of high
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risk anatomic factors, ASA class, blood transfusion prior to surgery, cardiac arrest, post
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operative MI, acute renal failure, post operative pneumonia and re-intubation (Table II).
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Multivariable analysis for wound infection; Stringent entry and stay criteria of p<0.05 were used
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for the stepwise process of variable selection to determine the best multivariable logistic
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regression model that included the factors most significantly associated with 30-day wound
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infection. The following factors were found to have significant associations with wound
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infection: wound disruption/dehiscence (OR 16, CI 7.09-36.07, p <0.05), organ space SSI (OR
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9.63, CI 2.71-34.25, p<0.05), unplanned reoperation (OR 3.86, CI 2.85-5.24, p<0.05), UTI (OR
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2.79, CI 1.28-6.05, p<0.05), BMI≥40 vs. <25 (OR 2.28, CI 1.18-4.39, p< 0.05), post operative
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bleeding requiring a transfusion (OR 2.03, CI 1.49-2.78, p<0.05), operation time >300 minutes
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vs. 0-170 minutes (OR 1.98, CI 1.32-2.96, p<0.05, prior ipsilateral percutaneous intervention
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involving currently treated segment (OR 1.98, CI 1.30-3.01, p<0.05), history of COPD (OR
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1.73, CI 1.21-2.48, p<0.05) and length of hospital stay ≥28 days (OR 1.21, CI 0.60-2.48, p<0.05)
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(Table III).
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Predicted probability of wound infection: The probability of wound infection was calculated for
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all of the factors identified to be significant in the multivariable analysis, either alone or
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combined, using the prediction equation generated from the model parameter estimates. The
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probability of wound infection was 3.21% for patients whose length of hospital stay was ≥ 28
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days, 4.51% for patients with history of COPD, 5.13% for patients with a prior ipsilateral
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percutaneous intervention involving currently treated segment, 5.13% for patients with an
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operative time >300 minutes, 5.27% for patients who had significant bleeding requiring a
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transfusion post operatively, 5.87% for patients with BMI≥40, 7.08% for patients with a post-
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operative UTI, 9.55% for patients who needed an unplanned re-operation, 20.84% for patients
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with organ space SSI, 30.42% for patients who developed wound disruption/dehiscence and
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99.94% for patients who had all of these risk factors (Table IV).
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Patients undergoing lower extremity open revascularization in the current times likely represent a
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cohort of patients with the severest forms of atherosclerotic burden with poorly controlled risk
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factors and are at a high risk for developing surgical site infections. During the hospital stay,
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early signs of wound complications such has wound disruption or dehiscence, erythema,
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tenderness or low grade fevers may be easily detected on daily rounds and can be easily treated
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before they progress to a severe, deep wound infection and sepsis. Focused physical
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examinations after lower extremity bypass surgery are of paramount importance. Close
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attentions should be paid to the appearance of the surgical incisions. Minor wound disruptions
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should be closely monitored, as these superficial wound disruptions can lead to complete wound
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dehiscence and our data clearly shows that such patients are at an extremely high risk for
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developing subsequent wound infections. Incidence of surgical site infections after lower
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extremity bypass in reported literature varies from 11%22 to 20%23. With bundle payment
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models for treatment of surgical patients, physicians and hospitals are under increasing pressure
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to reduce the length of hospital stay. Several surgical disciplines have devised new protocols to
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reduce the hospital stay24,25. While reducing the hospital stay is associated with advantages, such
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ACCEPTED MANUSCRIPT 13 as reduce postoperative pain and early return to work for majority of the patients; it carries with
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it the inherent disadvantage of patients not being examined by surgical team on a daily basis.
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This continued monitoring by health care providers ceases once patients leave the hospitals.
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Usually, the first postoperative appointment with surgical service is scheduled two to three
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weeks after discharge from the hospital26. Whitby et al27 have shown that patients in general
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lack clinical acumen and expertise to diagnose wound complications at an early stage. Despite
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education and teaching about recognizing early signs of complications, majority of the patients
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are unable to detect such complications at an early stage.
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Our study shows that the incidence of wound infections after lower extremity bypass is 13.7%
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and the median time for the diagnosis was 15 days. Our cohort shows the median length of
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hospital stay after lower extremity bypass surgery at 6 days. Other significant complications
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such as wound disruption/dehiscence and organ space SSI also occurred after the median length
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of stay at 15 and 16 days respectively following surgical bypass (Table I). As noted, the onset
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of any of these complications was apparent after a considerable time period following discharge
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from the hospital. Most of the prior literature has focused on determining the risk factors for
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developing wound complications after lower extremity bypass, during the hospital stay7,28-30. Our
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analysis aims to compare all patients with wound infections as a separate group and compares it
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to the group of patients with no wound infection to determine the factors associated with
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increased risk of post operative complications after lower extremity bypass surgery. The
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multivariable analysis (Table III) shows that wound disruption/dehiscence puts a patient at a 16-
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fold risk for developing a wound infection. Similarly, occurrence of postoperative bleeding puts
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a patient at 2.4 fold risk for developing a wound infection and BMI≥40 increases the risk of
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developing post operative wound infection by 2.28 fold. Previously published studies have also
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ACCEPTED MANUSCRIPT 14 shown that morbid obesity is associated with an increased risk of developing surgical site
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infections1,30,31,32. Several factors may predispose obese patients to higher risk of infection:
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increased thickness of subcutaneous tissue, traction related injury to adipose tissue and high
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bacterial count in deep groin creases. It is an established fact that morbidly obese patients have
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altered levels of leptin and adiponectin33 which predispose these patients to be at a higher risk for
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developing infections.
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days) to be associated with increased risk for developing surgical site infections. Our data also
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shows that increased LOS is associated with development of such complications, however, in our
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analysis, LOS greater than or equal to 28 days was found to be a significant predictor for
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Likewise, Wiseman et al34 have identified prolonged hospital stay (≥14
developing postoperative infections. Our group14 has previously shown that unplanned
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reoperation after lower extremity surgical bypass is associated with increased risk of
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readmission; this study shows that need for unplanned reoperation also puts patients at risk for
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developing wound infections after lower extremity bypass surgery. Association between
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reoperation and wound infection have been reported in prior reports as well34. Similarly, our
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findings of association between postoperative bleeding requiring blood transfusion and wound
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infection are consistent with previously published literature35. Cardiac surgery literature shows
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an increased incidence of sternal wound infections among patients who receive blood
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transfusions36. The association between blood transfusions and infection after cardiac and
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vascular surgeries37-39 is considered to be dose dependent, suggesting that transfusions may
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suppress the immune system. Basic science research suggests that blood transfusions may
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downregulate macrophages and T-cell immunity40 and affect immunomodulation41.
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Surgical Care Improvement Project (SCIP) and many other national and institutional initiatives
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have focused on standardizing surgical care to minimize the risk of perioperative infections.
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ACCEPTED MANUSCRIPT 15 These measures include, but are not limited to administration of preoperative antibiotics within
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one hour of surgical incision42-44. Some authors have reviewed the impact of showering with
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antiseptic solutions prior to surgery on the occurrence of post operative wound infections45.
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Likewise, some surgical disciplines have investigated the use of chlorhexidine for cleansing the
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skin prior to surgery and a randomized controlled trial showed that it reduced the surgical site
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infection rate from 16.1% to 9.5%46. The protection against occurrence of surgical site infection
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in these cases may be attributable to chlorhexidine’s rapid onset of action and persistence of its
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antimicrobial effect despite being exposed to different body fluids. Gynecological literature47
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shows that chlorhexidine gluconate based preparations reduce the number of surgical site
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infections when compared to povidone based solutions. Likewise, orthopedic studies48 show
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superiority of 2% chlorhexidine gluconate with 70% alcohol over 0.7% iodine and 74%
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isopropyl alcohol. Patients with critical limb ischemia suffer from poor blood flow to the lower
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extremities and it is quite possible that lack of blood flow to an extremity may reduce the
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bioavailability of antibiotics to the surgical incision site, although there is no scientific evidence
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to prove or disprove this hypothesis. For vascular surgery operations, it has been shown that the
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development of postoperative infection is associated with three-time increase in the hospital
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costs49.
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Based on our analysis, we have developed a probability model for risk of developing a wound
19
infection after a lower extremity bypass surgery (Table IV). With further validation, it can be a
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useful tool for prevention of wound infections in the future. It also allows for the identification
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of patients who are at a high risk for developing wound infections. After identifying such
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patients, clinicians can make the patients aware of their risk for developing wound infection after
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lower extremity bypass operations. Patients who are at an extremely high risk for developing
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ACCEPTED MANUSCRIPT 16 such wound complications may then be given additional directions to examine their wounds on a
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regular basis to detect early signs of infection and clinicians may choose to follow the selected
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group of patients in clinic at a shorter time interval as compared to other patients. This
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probability model is based on ACS-NSQIP, which is one of the best-standardized surgical
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databases in the world, however we caution against the routine use of such models until they are
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validated in prospective studies. Needless to say, predictability models like this provide a
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framework for future research studies.
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The results of this analyses should be interpreted in the context of several limitations. It is a
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retrospective analysis of a large, national surgical database. It only includes variables that are
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included in NSQIP database. It is important to point out that this database does not record the
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type of preparation used to clean the skin before surgery. Despite being the largest surgical
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database, hospital participation in NSQIP is voluntary and the results of this study may not be
13
generalized to all the hospitals. Lastly, this database does not record outcomes beyond thirty
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days and any wound infection that occurs after thirty days will not be included in it. The
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strength of this study is that NSQIP database is the largest and the most comprehensive surgical
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database in the US.
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and previously published results based this database have been validated.
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To summarize, a significant number of wound disruptions after lower extremity bypass occur
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after discharge from the hospital and predispose these patients to development of more serious
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complications. Our predictability model identifies the patients who are at the highest risk for
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developing wound infections and who would benefit from close monitoring by health care
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providers.
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SC
RI PT
1
AC C
EP
The quality of this dataset is assured by the American College of Surgeons
ACCEPTED MANUSCRIPT 17 1 2 3
RI PT
4 5 6
SC
7 8
M AN U
9 10 11 12 13 14 15
1.
16
complications in continuous infrainguinal incisions after lower limb arterial reconstruction:
17
incidence, risk factors, and cost. Surgery 1996;119:378-83.
18
2.
19
readmission after lower extremity bypass. Journal of vascular surgery 2013;57:955-62.
20
3.
21
surgical site infection, 1999. Hospital Infection Control Practices Advisory Committee. Infection
22
control and hospital epidemiology 1999;20:250-78; quiz 79-80.
TE D
References
EP
Kent KC, Bartek S, Kuntz KM, Anninos E, Skillman JJ. Prospective study of wound
AC C
McPhee JT, Barshes NR, Ho KJ, et al. Predictive factors of 30-day unplanned
Mangram AJ, Horan TC, Pearson ML, Silver LC, Jarvis WR. Guideline for prevention of
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4.
2
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5.
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6.
8
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9
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National Nosocomial Infections Surveillance S. National Nosocomial Infections
SC
de Lissovoy G, Fraeman K, Hutchins V, Murphy D, Song D, Vaughn BB. Surgical site
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Kirkland KB, Briggs JP, Trivette SL, Wilkinson WE, Sexton DJ. The impact of surgical-
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7.
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9.
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17
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Kohn LT CJ, Donaldson M. To Err is Human: Building a Safer Health System.
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Leape LL, Brennan TA, Laird N, et al. The nature of adverse events in hospitalized
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Thomas EJ, Brennan TA. Incidence and types of preventable adverse events in elderly
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17
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10
EP
Adam DJ, Beard JD, Cleveland T, et al. Bypass versus angioplasty in severe ischaemia of
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Veterans Affairs Surgical Risk Study. Journal of the American College of Surgeons
2
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3
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4
mortality on comparisons of hospital surgical quality. Annals of surgery 2010;252:183-90.
5
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7
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8
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9
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Shiloach M, Frencher SK, Jr., Steeger JE, et al. Toward robust information: data quality
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11
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12
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13
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Journal of the American College of Surgeons 1995;180:519-31.
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16
open lower extremity revascularization. Journal of vascular surgery 2011;54:433-9.
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10
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Khuri SF, Daley J, Henderson W, et al. The National Veterans Administration Surgical
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randomized trial of edifoligide for the prevention of vein graft failure in lower extremity bypass
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surgery. Journal of vascular surgery 2006;43:742-51; discussion 51.
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6
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7
25.
8
major surgery and the adverse effect of postoperative complications. Annals of surgery
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RI PT
Conte MS, Bandyk DF, Clowes AW, et al. Results of PREVENT III: a multicenter,
SC
Miller TE, Thacker JK, White WD, et al. Reduced length of hospital stay in colorectal
M AN U
Khuri SF, Henderson WG, DePalma RG, et al. Determinants of long-term survival after
10
26.
11
readmission among general and vascular surgery patients: a case for redesigning transitional
12
care. Surgery 2014;156:949-56.
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27.
14
reliably diagnose surgical wound infections? The Journal of hospital infection 2002;52:155-60.
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16
infection: a focus on prevention using the American College of Surgeons National Surgical
17
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TE D
Saunders RS, Fernandes-Taylor S, Rathouz PJ, et al. Outpatient follow-up versus 30-day
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Whitby M, McLaws ML, Collopy B, et al. Post-discharge surveillance: can patients
Gibson A, Tevis S, Kennedy G. Readmission after delayed diagnosis of surgical site
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29.
2
infections after patients leave hospital. The Journal of hospital infection 2010;75:188-94.
3
30.
4
Medina-Cuadros M, Llorca J. Efficacy of surveillance in nosocomial infection control in a
5
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6
31.
7
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8
National Surgical Quality Improvement Program 2005-2007. Annals of vascular surgery
9
2010;24:48-56.
Daneman N, Lu H, Redelmeier DA. Discharge after discharge: predicting surgical site
SC
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Delgado-Rodriguez M, Gomez-Ortega A, Sillero-Arenas M, Martinez-Gallego G,
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Giles KA, Hamdan AD, Pomposelli FB, Wyers MC, Siracuse JJ, Schermerhorn ML.
10
32.
11
influence of body mass index obesity status on vascular surgery 30-day morbidity and mortality.
12
Journal of vascular surgery 2009;49:140-7, 7 e1; discussion 7.
13
33.
14
2006;6:438-46.
15
34.
16
after hospital discharge in patients undergoing major vascular surgery. Journal of vascular
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surgery 2015;62:1023-31 e5.
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Davenport DL, Xenos ES, Hosokawa P, Radford J, Henderson WG, Endean ED. The
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Falagas ME, Kompoti M. Obesity and infection. The Lancet Infectious diseases
Wiseman JT, Fernandes-Taylor S, Barnes ML, et al. Predictors of surgical site infection
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2
transfusion is associated with increased morbidity and mortality after lower extremity
3
revascularization. Journal of vascular surgery 2010;51:616-21, 21 e1-3.
4
36.
5
mortality, postoperative morbidity, and cost after red blood cell transfusion in patients having
6
cardiac surgery. Circulation 2007;116:2544-52.
7
37.
8
associated with increased wound infection and graft thrombosis. Journal of the American
9
College of Surgeons 2013;216:1005-14 e2; quiz 31-3.
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O'Keeffe SD, Davenport DL, Minion DJ, Sorial EE, Endean ED, Xenos ES. Blood
SC
Murphy GJ, Reeves BC, Rogers CA, Rizvi SI, Culliford L, Angelini GD. Increased
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Tan TW, Farber A, Hamburg NM, et al. Blood transfusion for lower extremity bypass is
10
38.
11
components and postoperative infection in patients undergoing cardiac surgery. Chest
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2001;119:1461-8.
13
39.
14
Suppurative mediastinitis after open-heart surgery: a case-control study covering a seven-year
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period in Santander, Spain. Clinical infectious diseases : an official publication of the Infectious
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17
40.
18
and clinical challenge. The American journal of medicine 1996;101:299-308.
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Leal-Noval SR, Rincon-Ferrari MD, Garcia-Curiel A, et al. Transfusion of blood
AC C
Farinas MC, Gald Peralta F, Bernal JM, Rabasa JM, Revuelta JM, Gonzalez-Macias J.
Blumberg N, Heal JM. Immunomodulation by blood transfusion: an evolving scientific
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2
update. Blood reviews 2007;21:327-48.
3
42.
4
cefotetan prophylaxis in elective colorectal surgery. The New England journal of medicine
5
2006;355:2640-51.
6
43.
7
intravenous antimicrobial prophylaxis alone with oral and intravenous antimicrobial prophylaxis
8
for the prevention of a surgical site infection in colorectal cancer surgery. Surgery today
9
2007;37:383-8.
Vamvakas EC, Blajchman MA. Transfusion-related immunomodulation (TRIM): an
SC
RI PT
Itani KM, Wilson SE, Awad SS, Jensen EH, Finn TS, Abramson MA. Ertapenem versus
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Kobayashi M, Mohri Y, Tonouchi H, et al. Randomized clinical trial comparing
10
44.
11
administration of antimicrobial agents immediately before surgery for patients with
12
gastrointestinal cancers. Hepato-gastroenterology 2007;54:1487-93.
13
45.
14
surgical site infection. The Cochrane database of systematic reviews 2012;9:CD004985.
15
46.
16
Iodine for Surgical-Site Antisepsis. The New England journal of medicine 2010;362:18-26.
EP
TE D
Uchiyama K, Takifuji K, Tani M, et al. Prevention of postoperative infections by
AC C
Webster J, Osborne S. Preoperative bathing or showering with skin antiseptics to prevent
Darouiche RO, Wall MJ, Jr., Itani KM, et al. Chlorhexidine-Alcohol versus Povidone-
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47.
2
compared povidone iodine and chlorhexidine as antiseptics for vaginal hysterectomy. American
3
journal of obstetrics and gynecology 2005;192:422-5.
4
48.
5
and ankle surgery. The Journal of bone and joint surgery American volume 2005;87:980-5.
6
49.
7
complications after elective vascular surgical procedures. Journal of vascular surgery
8
2010;51:122-9; discussion 9-30.
RI PT
Culligan PJ, Kubik K, Murphy M, Blackwell L, Snyder J. A randomized trial that
SC
Ostrander RV, Botte MJ, Brage ME. Efficacy of surgical preparation solutions in foot
9
AC C
EP
TE D
10
M AN U
Vogel TR, Dombrovskiy VY, Carson JL, Haser PB, Lowry SF, Graham AM. Infectious
ACCEPTED MANUSCRIPT
Table 1. Complications After lower extremity bypass surgery and their relation to the time of development after the operation P value to median length of stay (6 days) <.0001 0.6271 0.0660 <.0001 0.0525 0.0023 0.1250 <.0001 <.0001 <.0001 0.0294 0.5034 0.1185 0.7905 0.4240
RI PT
Days from operation Median (Q1, Q3) 15.0 (10.0, 22.0) 6.5 (2.0, 16.0) 10.0 (3.0, 14.0) 15.0 (14.0, 21.0) 11.0 (5.50, 20.0) 16.0 (14.0, 23.0) 15.0 (9.0, 20.0) 1.0 (0, 3.0) 3.0 (1.0, 5.0) 2.0 (1.0, 4.0) 3.0 (2.0, 9.0) 4.0 (2.0, 14.0) 3.0 (2.0, 9.5) 4.0 (3.0, 12.0) 4.0 (1.0, 8.0)
M AN U
SC
Incidence N (%)/2646 361 (13.70) 50 (1.89) 45 (1.70) 43 (1.63) 24 (0.91) 17 (0.64) 5 (0.19) 455 (17.20) 81 (3.10) 62 (2.34) 33 (1.25) 21 (0.79) 16 (0.60) 15 (0.57) 15 (0.57)
Complication Deep Wound infection Untreated loss of Patency Urinary tract infection Wound disruption complications DVT/Thrombophlebitis Organ space SSI Pulmonary embolism Post-op bleeding requiring a transfusion MI/Stroke Myocardial infarction Pneumonia Cardiac arrest requiring CPR Progressive renal insufficiency Acute renal failure Stroke/CVA
AC C
EP
TE D
Complications reported within 30 days following lower extremity bypass surgery. Each complication shows the number of patients as well as the number of days from bypass. Those values were then compared to the median discharge date to evaluate the significance of the complication as it relates to the hospital discharge. The table above shows 3 major variables with significance post hospital discharge. Significant variables have a median of approximately 15 days following a lower extremity bypass. The median length of hospital stay for these patients is 6 days, indicating that patients should be closely monitored following hospital discharge to prevent wound infections or complications.
ACCEPTED MANUSCRIPT
Table II. Univariate Analysis of factors contributing to wound infection Wound Infection
(N=2284)
(N=361)
≤75
1701 (86.4)
267 (13.6)
>75-85
456 (86.9)
69 (13.1)
>85
127 (83.6)
25 (16.4)
Female
790 (84.7)
143 (15.3)
Male
1494 (87.3)
Variable
SC
Age (years)
M AN U
Sex
Race
OR (95% CI)*
RI PT
No Wound Infection
Reference
1.24 (0.99, 1.56)
218 (12.7)
Reference
18 (14.6)
1.15 (0.68, 1.93)
68 (15.0)
1.18 (0.88, 1.58)
4 (11.1)
0.84 (0.29, 2.39)
Non-Hispanic Black
386 (85.0)
Non-Hispanic Other
32 (88.9)
Non-Hispanic White
1505 (87.0)
225 (13.0)
Reference
<25
796 (89.7)
91 (10.3)
Reference
25-<30
770 (87.8)
107 (12.2)
1.22 (0.90, 1.64)
601 (82.3)
129 (17.7)
1.88 (1.41, 2.51)
70 (78.7)
19 (21.3)
2.37 (1.37, 4.12)
51 (92.7)
4 (7.3)
Reference
619 (90.6)
64 (9.4)
1.32 (0.46, 3.77)
CLI – Rest Pain
725 (85.9)
119 (14.1)
2.09 (0.74, 5.90)
CLI – Tissue Loss
861 (83.4)
171 (16.6)
2.53 (0.90, 7.10)
Symptoms Asymptomatic Claudication
EP AC C
>40
TE D
105 (85.4)
30-<40
High risk physiologic
0.568
0.96 (0.73, 1.28) 1.25 (0.80, 1.96)
Hispanic
BMI (kg/m^2)
P-value*
0.064
0.678
<0.001
<0.001
0.604
ACCEPTED MANUSCRIPT
factors Present
480 (85.6)
81 (14.4)
1.07 (0.82, 1.40)
1768 (86.4)
278 (13.6)
Reference
1840 (86.1)
298 (13.9)
429 (87.7)
60 (12.3)
1372 (85.4)
234 (14.6)
1.20 (0.95, 1.51)
886 (87.6)
126 (12.5)
Reference
260 (14.3)
1.19 (0.93, 1.52)
100 (12.4)
Reference
Pre-procedural medication – Aspirin Yes No
No Pre-procedural medication – Statin
1556 (85.7)
Yes
1.16 (0.86, 1.56)
None
597 (84.0)
114 (16.0)
Reference
Non-insulin dependent
1292 (87.8)
180 (12.2)
1.37 (1.06, 1.77)
Insulin dependent
395 (85.5)
67 (14.5)
1.22 (0.90, 1.65)
19 (12.9)
0.94 (0.57, 1.54)
2156 (86.3)
342 (13.7)
Reference
127 (84.7)
23 (15.3)
1.16 (0.73, 1.83)
2157 (86.5)
338 (13.6)
Reference
Dialysis dependent
No
128 (87.1)
AC C
Yes
0.332
Reference
EP
Diabetes mellitus
TE D
709 (87.6)
No
M AN U
Yes
SC
Pre-procedural medication Beta blocker
RI PT
Absent
0.126
0.179
0.045
0.793
Emergency operation Yes No
0.536
History of CHF 30 days prior to surgery Yes
0.271
ACCEPTED MANUSCRIPT
No
59 (81.9)
13 (18.1)
1.41 (0.77, 2.60)
2225 (86.5)
348 (13.5)
Reference
Yes
286 (81.7)
64 (18.3)
1.51 (1.12, 2.03)
No
1998 (87.1)
297 (12.9)
1883 (85.6)
316 (14.4)
401 (89.9)
45 (10.1)
Yes No
SC
Hypertension requiring medication
937 (86.3)
No
1347 (86.4)
M AN U
Smoking Yes
RI PT
History of severe COPD
Reference
1.50 (1.08, 2.08)
1.01 (0.81, 1.27)
212 (13.6)
Reference
35 (12.2)
0.87 (0.60, 1.26)
326 (13.8)
Reference
9 (81.8)
2 (18.2)
1.41 (0.30, 6.55)
2275 (86.4)
359 (13.6)
Reference
2160 (86.6)
335 (13.4)
Reference
52 (82.5)
11 (17.5)
1.36 (0.71, 2.64)
27 (75.0)
9 (25.0)
2.15 (1.00, 4.61)
45 (88.24)
6 (11.8)
0.86 (0.36, 2.03)
Yes
764 (83.5)
151 (16.5)
1.43 (1.14, 1.79)
No
1520 (87.9)
210 (12.1)
Reference
252 (87.8)
No
2032 (86.2)
Yes No Wound classification Clean
Contaminated Dirty/Infected
AC C
Clean/Contaminated
EP
Preoperative UTI
TE D
Yes
0.017
Reference
149 (13.7)
Transfer status
0.007
0.929
0.448
0.662
0.189
Open wound at time of operation
0.002
ACCEPTED MANUSCRIPT
Mean ± (standard deviation)
Mean ± (standard deviation)
3.56 (0.68)
3.51 (0.67)
Mean ± (standard deviation)
Mean ± (standard deviation)
2.01 (3.60)
1.87 (3.41)
0-170
611 (90.3)
66 (9.8)
170-225
563 (88.5)
73 (11.5)
225-300
568 (85.5)
96 (14.5)
1.57 (1.12, 2.18)
>300
541 (81.1)
126 (18.9)
2.16 (1.57, 2.97)
216 (13.6)
1.22 (0.95, 1.629)
69 (11.4)
Reference
76 (17.0)
1.60 (1.13, 2.27)
118 (87.4)
17 (12.6)
Reference
1681 (86.8)
256 (13.2)
1.06 (0.63, 1.79)
484 (84.6)
88 (15.4)
1.26 (0.72, 2.20)
Cardiac Surgery
2 (33.3)
4 (66.7)
12.43 (2.27, 68.13)
General Surgery
36 (97.3)
1 (2.7)
0.17 (0.02, 1.26)
Thoracic
57 (93.4)
4 (6.6)
0.44 (0.16, 1.21)
Days from hospital admission to operation
Absent Prior ipsilateral bypass involving currently treated segment
1377 (86.4)
Prior ipsilateral percutaneous intervention involving currently treated segment
370 (82.96)
No Disturbance-Mild Disturbance (1-2)
TE D
AC C
Severe Disturbance (3)
EP
ASA class
537 (88.6)
Life ThreateningMoribund (4-5)
M AN U
High risk anatomic factors
0.401
0.99 (0.96, 1.02)
0.499
Reference
SC
Operative time, minutes
0.91 (0.72, 1.14)
RI PT
Pre-op albumen level, mg/dl
1.20 (0.84, 1.71)
<0.001
0.031
0.388
Surgeon’s specialty:
0.008
ACCEPTED MANUSCRIPT
Vascular
2188 (86.1)
352 (13.9)
Reference
<7
1294 (87.9)
178 (12.1)
Reference
7-<13
638 (85.0)
113 (15.1)
14-<21
218 (85.5)
37 (14.5)
21-<28
81 (87.1)
12 (12.9)
>=28
53 (71.6)
21 (28.4)
Yes
73 (78.5)
20 (21.5)
1.78 (1.07, 2.95)
No
2211 (86.6)
341 (13.4)
Reference
109 (24.0)
2.42 (1.88, 3.12)
252 (11.5)
Reference
Yes
346 (76.0)
No
1938 (88.5)
SC
TE D
Combined MI and stroke
M AN U
Amputation
Bleeding
RI PT
Length of hospital stay, days
1.29 (0.99, 1.66) 1.23 (0.84, 1.81)
2.88 (1.70, 4.90)
Yes
63 (77.8)
18 (22.2)
1.85 (1.08, 3.16)
No
2221 (86.6)
343 (13.4)
Reference
36 (72.0)
14 (28.0)
2.52 (1.35, 4.72)
2248 (86.6)
347 (13.4)
Reference
19 (90.5)
2 (9.5)
0.67 (0.15, 2.87)
2265 (86.3)
359 (13.7)
Reference
281 (66.8)
140 (33.3)
EP
Untreated loss of patency Yes
AC C
No
0.002
1.08 (0.58, 2.01)
0.027
<0.001
0.025
0.004
Acute renal failure post operatively Yes No
2.865
Need for re-operation Yes
<0.001 4.52 (3.53, 5.77)
No
2003 (90.1)
221 (10.0)
ACCEPTED MANUSCRIPT
Transfusion >4 units PRBCs in 72hr before surgery
44 (93.6)
3 (6.4)
0.43 (0.13, 1.38)
2240 (86.22)
358 (13.8)
Reference
16 (76.2)
5 (23.8)
2268 (86.4)
356 (13.6)
Yes
49 (79.0)
13 (21.0)
No
2235 (86.5)
Yes
0.155
Yes No
31 (72.1)
17.78 (9.04, 34.96)
330 (12.7)
Reference
5 (29.4)
12 (70.6)
15.66 (5.48, 44.70)
2279 (86.7)
349 (13.3)
Reference
25 (75.8)
8 (24.2)
2.05 (0.92, 4.58)
2259 (86.5)
353 (13.5)
Reference
33 (78.6)
9 (21.4)
1.74 (0.83, 3.68)
2251 (86.5)
352 (13.5)
Reference
11 (68.8)
5 (31.3)
2.90 (1.00, 8.40)
2273 (86.5)
356 (13.5)
Reference
Yes No
EP
Postoperative pneumonia
TE D
2272 (87.3)
Organ space SSI
Yes
AC C
No
1.70 (0.92, 3.17) Reference
12 (27.9)
0.182
Reference
348 (13.5)
Wound disruption or dehiscence
No
M AN U
Post-operative MI
Yes
1.99 (0.73, 5.47)
SC
Cardiac arrest requiring CPR
RI PT
No
0.093
<0.001
<0.001
0.081
Need for re-intubation Yes No Progressive renal insufficiency (postoperative) Yes
0.144
0.049
ACCEPTED MANUSCRIPT
No
Yes
30 (66.7)
15 (33.3)
3.26 (1.74, 6.12)
No
2254 (86.7)
346 (13.3)
Reference
Yes
243 (57.2)
182 (42.8)
No
2041 (91.9)
179 (8.1)
RI PT
Postoperative UTI <0.001 Readmission
8.54 (6.68, 10.92)
<0.001
Reference
AC C
EP
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* All odds ratios and p-values are from binomial logistic regression modeling wound infection, exact logistic regression used as needed. Odds ratios with 95% confidence limits not including 1 are considered significant.
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Table III. Multivariable model Risk Factor
Adjusted Odd’s Ratio P- Value
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(95% CI) 15.99 (7.09, 36.07)
<0.001
Organ space infection
9.63 (2.71, 34.25)
<0.001
Unplanned reoperation
3.86 (2.85, 5.24)
<0.001
Urinary tract infection (UTI)
2.79 (1.28, 6.05)
0.010
2.28 (1.18, 4.39)
<0.001
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Wound disruption/dehiscence
Post-operative bleeding requiring a transfusion
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BMI ≥40 vs. <25
Operation time >300 minutes vs. 0-170 minutes
2.03 (1.49, 2.78)
<0.001
1.98 (1.32, 2.96)
0.008
1.98 (1.30, 3.01)
0.004
1.73 (1.21, 2.48)
0.003
Total LOS ≥ 28 days vs. <7 days
1.21 (0.60, 2.48)
0.014
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Prior ipsilateral percutaneous intervention involving currently treated segment vs Prior ipsilateral bypass involving currently treated segment History of COPD
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+ +
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Unplanned Re-Operation
Organ Space Infection
Wound Disruption/ Dehiscence
+ +
+ +
+ +
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BMI≥40 Postoperative UTI
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Table 4: Predicted Probability of Deep Wound Infection LOS COPD Prior ipsilateral Operation Bleeding percutaneous ≥28 time >300 Requiring a intervention days minutes Transfusion involving currently treated segment + + + + + + + + + +
Probability of Surgical Wound Infection 3.21% 4.51% 5.13% 5.13% 5.27% 5.87% 7.08% 9.55% 20.84% 30.42% 99.94%
S0890-5096(17)30381-3
DOI:
10.1016/j.avsg.2016.10.065
Reference:
AVSG 3208
To appear in:
Annals of Vascular Surgery
Received Date: 29 June 2016 Revised Date:
17 October 2016
Accepted Date: 20 October 2016
Please cite this article as: Aziz F, Bohr T, Lehman EB, Wound Disruption After Lower Extremity Bypass Surgery is a Predictor of Subsequent Development of Wound Infection, Annals of Vascular Surgery (2017), doi: 10.1016/j.avsg.2016.10.065. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Wound Disruption After Lower Extremity Bypass Surgery is a Predictor of Subsequent
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Development of Wound Infection
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Faisal Aziz MD, FACS1, Tiffany Bohr2 and Erik B. Lehman MS3
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Division of Vascular Surgery, Penn State Heart and Vascular Institute, Pennsylvania State University College of Medicine.
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Office of Medical Education, Pennsylvania State University, College of Medicine. Department of Public Health Sciences, Pennsylvania State University, College of Medicine.
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Correspondence to:
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Faisal Aziz MD, FACS. Penn State Milton S. Hershey Medical Center, 500 University Drive Mail Code H053, Room C4632 Hershey, PA 17033 Tel: 717-531-8898 Fax: 717-531-4151 E-Mail: [email protected]
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ACCEPTED MANUSCRIPT 2 ABSTRACT
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Objectives: Despite advances in endovascular surgery, lower extremity arterial bypass (LEB)
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remains the gold standard treatment for severe, symptomatic Peripheral Arterial Disease (PAD).
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With recent changes in healthcare, there has been an increasing emphasis on reducing the
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hospital length of stay (LOS). The purpose of this study is to identify the postoperative
6
complications, which occur after discharge from hospital, and to find risk factors for developing
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such complications.
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Methods: The 2013 lower extremity revascularization –targeted American College of Surgeons
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(ACS-NSQIP) database and generalized 2013 general and vascular surgery ACS-NSQIP PUF
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were used for this study. Patient, diagnosis, and procedure characteristics of patients undergoing
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LEB were assessed. Postoperative complications were identified and their relationship to the
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median discharge date. Univariate and Multivariable analyses were performed to identify the
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risk factors associated with developing these complications. A prediction model was then
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created to accurately predict the risk of developing such complications.
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Results: A total of 2646 patients (65% male, 35% female) were identified in the NSQIP database
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that underwent LEB during the year 2013. Median LOS was 6 days. Most common significant
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complications after hospital discharge were: Wound infection/complication (13.7%. Mean Days
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from Operation (MDAO) = 15 days), wound disruption/dehiscence (1.6%. MDAO = 15 days)
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and organ space SSIs (0.6%. MDAO = 16 days). Multivariable analysis showed these factors
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associated with wound infection: Wound disruption/dehiscence (OR 16, CI 7.09-36.07,
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p<0.001), organ space infection (OR 9.63, CI 2.71-34.25, p<0.001), unplanned reoperation (OR
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3.86, CI 2.85-5.24, p<0.001), UTI (OR 2.79, CI 1.28-6.05, p=0.010), BMI≥40 vs. <25 (OR 2.28,
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CI 1.18-4.39, p<0.001), Post-operative bleeding requiring a transfusion (OR 2.03, CI 1.49-2.78,
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ACCEPTED MANUSCRIPT 3 p<0.001), Operation time >300 min. vs. 0-170 min. (OR 1.98, CI 1.32-2.96, p=0.008), Prior
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ipsilateral percutaneous intervention involving currently treated segment vs Prior ipsilateral
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bypass involving currently treated segment (OR1.98, CI 1.30-3.01, p=0.004), history of COPD
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(OR 1.73, CI 1.21-2.48, p =0.003) and total length of stay (LOS) ≥28 days vs. <7 days (OR 1.21
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CI 0.60-2.48, p=0.014). The risk prediction model for developing wound infection is listed
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below.
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Conclusions: Wound infection is the most common complication after LEB. Most of these
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complications occur after discharge from hospital. Patients with risk factors for developing
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wound infections should be followed and closely monitored after discharge from the hospital.
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ACCEPTED MANUSCRIPT 4 1 2 Introduction
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Surgical site infections (SSIs) are among the most complications after any surgical operation.
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Recent changes in health care reimbursement structure incentivize hospitals to reduce the length
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of hospital stay (LOS). One of the disadvantages of minimal LOS is inability of health care
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providers to assess the patients for development of any postoperative complications. Many of
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such clinical signs and symptoms can be detected at an early stage by performing vigilant
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physical examinations and can be potentially prevented from developing into serious
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complications. Once developed, SSIs can be a source of serious morbidity and may lead to
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increased postoperative pain, systemic complications, return to the operating room, prolonged
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length of hospital stay and readmission to the hospital1,2. It is estimated that wound infections
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count for 38%3,4 of all post operative complications and contribute to approximately 20,000
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preventable deaths every year4-7. Wound complications after surgical operations may cost up to
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$3 billion every year5-7. Recognizing the medical and financial impact of such complications has
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lead to nationwide efforts, including Surgical Care Improvement Project (SCIP) with the goal of
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improving surgical care by reducing postoperative complications. Institute of Medicine released
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a report on medical errors in 19998 and since then, there has been an increasing public demand9
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for prevention of postoperative complications. According to a recent estimate, up to 66% of all
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hospital adverse events are related to surgery and majority of these events are considered
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preventable10-13. Patients with peripheral arterial disease who need open surgical bypasses
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represent a cohort of patient population which has multiple severe systemic illnesses and are
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prone to developing numerous postpone complications, which may require further treatment,
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ACCEPTED MANUSCRIPT 5 operations or readmission to hospital14. Lower extremity bypasses are technically demanding
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operations, which involve a series of steps, which require paying meticulous attention to minor
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details. Proponents of endovascular therapy site risk of surgical site infection after lower
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extremity bypasses as one of the reasons to avoid open surgery in patients with symptomatic
5
peripheral arterial disease15. With increasing health care scrutiny, it is essential to determine the
6
nationwide incidence of surgical site infections among patients undergoing lower extremity
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bypasses, the relationship to the day of discharge from the hospital and to analyze the factors
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associated with high risk of developing surgical site infections in this group of patients.
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Reimbursement agencies hold hospitals accountable for major postoperative complications. In
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the recent past, development of sacral decubiti, urinary tract infections and blood stream
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infections during hospital stay have become targets for measuring physicians’ and institutional
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performance and have been tied to reduced financial reimbursements. It is highly likely that
13
wound infections will be added to the list of preventable events in near future. Determining the
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factors associated with deep wound infections after lower extremity bypasses has important
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medical and financial implications.
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ACCEPTED MANUSCRIPT 6 1 2 Methods
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Data set: The American College of Surgeons (ACS) has created National Surgical Quality
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Improvement Program (NSQIP) Participant Use File (PUF)16 , which is a de-identified dataset.
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It is compliant with Health Insurance Portability and Accountability Act (HIPAA). The number
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of participating institutions has gradually increased over the course of past decade. Systemic
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sampling method used to extract data from NSQIP database has been described previously17-21.
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Briefly, general and vascular surgical operations are divided into 8-day cycles. At each NSQIP
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site, the first forty operations performed within each 8-day that meet program inclusion criteria
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are entered in the database. NSQIP ensures heterogeneity by limiting the number of cases per
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cycle for certain higher volume and lower risk surgeries. Personnel trained specifically for
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NSQIP at each site are responsible for data collection. Studies showing outcomes based on
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NSQIP database have been shown to be highly reliable with minimal disagreements during
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annual audits19. To ensure complete follow-up, patients with incomplete 30-day outcomes are
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excluded from the database. Since there are no patient identifiers in NSQIP database, no
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Institutional Review Board (IRB) approval or patients’ consent was required.
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Patients: All patients who underwent any infra-inguinal lower extremity open revascularization
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procedure during the year 2013, using Procedure Targeted Participant User File16 from NSQIP
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database. Using unique case identification numbers, this file was merged to the main ACS
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NSQIP adult Participant Use Data File. Any patient who presented with revascularization of
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bilateral limbs in the same calendar year was deleted from the data set.
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ACCEPTED MANUSCRIPT 7 Outcomes: Primary outcome was to identify the most common complications after surgery.
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Secondary outcome was to identify factors associated with wound infection. Basic demographic
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data were analyzed including age, gender, race, and body mass index range. Several peri-
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operative variables were analyzed: operative times, length of hospital stay, type of operation,
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symptoms, high risk physiologic factors, high risk anatomic factors (defined as prior ipsilateral
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percutaneous intervention involving currently treated segment or prior ipsilateral bypass
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involving currently treated segment), pre-operative symptoms, pre-operative use of aspirin, pre-
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operative use of beta-blockers, pre-operative use of statins, need for amputation, significant post-
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operative bleeding, post-operative myocardial infarction, post-operative stroke, untreated loss of
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patency, wound infection, pre-operative albumin, number of days from hospital admission to
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operation, type of anesthetic, American Society of Anesthesiology (ASA) classification, diabetes
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mellitus, end-stage renal disease, emergency operation, congestive heart failure, chronic
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obstructive pulmonary disease (COPD), hypertension, post-operative renal failure, need for re-
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operation, history of smoking, surgeons’ specialty, need for blood transfusion, transfer status,
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urinary tract infection, wound classification, cardiac arrest, wound disruption/dehiscence,
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pneumonia and need for re-intubation (Please refer to Appendix for definitions of these
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variables).
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Statistical Analysis: All variables were initially summarized with frequencies and percentages or
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means, medians, and standard deviations. A sign test was used to test for differences between
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the median days from operation for each complication and the median length of stay (6 days).
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Logistic regression was used to determine any bivariate associations of independent variables
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with wound infection. Odds ratios were used to quantify the magnitude and direction of any
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significant associations. The significant (p<0.05) independent variables from the bivariate
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ACCEPTED MANUSCRIPT 8 analysis were then used in a process of stepwise selection to find the group of variables
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collectively that were most significantly associated with significant post operative complications
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in a multivariable logistic regression model. With so many variables and a large sample size, a
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more stringent entry criteria of p<0.05 and a stay criteria of p<0.05 were used for the stepwise
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process of variable selection to be more conservative. Forward and backward selection methods
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were also employed to check for other potential models, but the three approaches resulted in
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similar reduced models. The fit of the final model was checked using the Hosmer and
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Lemeshow goodness-of-fit test (p=0.1017). The c-statistic (c=0.753) was used to estimate the
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prediction strength of the final model. All analyses were performed using SAS version 9.4 (SAS
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Institute, Cary, NC).
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Demographics and preoperative comorbidities: A total of 2,646 patients (65% Males, 35%
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Females) underwent lower extremity revascularization operations in the year 2013. Mean age
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was 67.7 (± 11.3) years. Median length of hospital stay was 6 days.
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Post-operative complications: The incidence of post-operative complications are as follows:
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wound infection (13.7%), untreated loss of patency (1.9%), urinary tract infection (1.7%), wound
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disruption/dehiscence (1.6%), DVT/Thrombophlebitis (0.9%), organ space SSI (0.6%),
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pulmonary embolism (0.2%), post-op bleeding requiring a transfusion (17.2%), MI/stroke
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(3.1%), myocardial infarction (2.3%), pneumonia (1.3%), cardiac arrest requiring CPR (0.8%),
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progressive renal insufficiency (0.6%), acute renal failure (0.6%), stroke/CVA (0.6%).(Table I).
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Timing of complications after lower extremity bypass surgery: The three significant wound
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complications (p<0.05) occurred well after the median discharge of 6 days: Wound infection
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occurred at day 15 after surgery (range: 10-22 days), wound disruption/dehiscence also at day
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15.0 (range: 14.0, 21.0) and organ space SSI at 16.0 days following surgery (range: 14.0, 23.0)
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(Table I).
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Independen t variables associated with wound infection: Since wound infection was the most
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common complication after lower extremity bypass surgery, attention was focused on the
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patients who developed this complication. Patients were divided into two groups: no wound
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ACCEPTED MANUSCRIPT 10 infection (N=2284) and wound infection (N=361) groups. The following variables were found
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to have a significant association with wound infection: higher BMI 30-<40 (OR 1.88 CI 1.41-
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2.51), BMI ≥40 (OR 2.37, CI 1.37-4.12, p<0.05), non-insulin dependent diabetes mellitus (OR
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1.37, CI 1.06-1.77, p<0.05), severe COPD (defined as emphysema and/or chronic bronchitis
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resulting in any one or more of the following: -Functional disability from COPD (e.g., dyspnea,
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inability to perform ADLs) -Hospitalization in the past for treatment of COPD -Requires chronic
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bronchodilator therapy with oral or inhaled agents. -An FEV1 of <75% of predicted on
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pulmonary function testing) (OR 1.51, CI 1.12-2.03, p<0.05), hypertension requiring medication
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(OR 1.5, CI 1.08-2.08, p<0.05), contaminated wound classification (OR 2.15, CI 1.00-4.61),
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open wound at the time of operation (OR 1.43, CI 1.14- 1.79, p<0.05), longer operative times
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(for operative time more than 300 minutes, OR 2.16, CI 1.57-2.97, p<0.05), cardiac surgery as
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surgeon’s specialty (OR 12.43, CI 2.27-68.13, p<0.05), length of hospital stay ≥ 28 days (OR
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2.88, CI 1.70-4.90, p<0.05), need for amputation (OR 1.78, CI 1.07-2.95, p<0.05), post operative
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bleeding (OR 2.42, CI 1.88-3.12, p<0.05), combined MI and stroke (OR 1.85, CI 1.08-3.16,
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p<0.05), untreated loss of patency (OR 2.52, CI 1.35-4.72, p<0.05), need for re-operation (OR
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4.52, CI 3.53-5.77, p<0.05), wound disruption/dehiscence (OR 17.78, CI 9.04-34.96, p<0.05),
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organ space SSI (OR 15.66, CI 5.48-44.70, p<0.05), progressive renal insufficiency (OR 2.90, CI
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1.00-8.40, p<0.05), post-operative UTI (OR 3.26, CI 1.74-6.12, p<0.05) and re-admission (OR
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8.54, CI 6.68-10.92, p<0.05) (Table II).
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The following factors were found to have no significant association with wound infection: age,
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gender, race, presenting symptoms, high risk physiologic factors, pre-operative use of aspirin,
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pre-operative use of beta blockers, pre-operative use of statins, dialysis dependence, emergency
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operation, history of congestive heart failure, smoking, transfer status, pre-operative urinary tract
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ACCEPTED MANUSCRIPT 11 infection, albumin levels, number of days from hospital admission to operation, presence of high
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risk anatomic factors, ASA class, blood transfusion prior to surgery, cardiac arrest, post
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operative MI, acute renal failure, post operative pneumonia and re-intubation (Table II).
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Multivariable analysis for wound infection; Stringent entry and stay criteria of p<0.05 were used
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for the stepwise process of variable selection to determine the best multivariable logistic
6
regression model that included the factors most significantly associated with 30-day wound
7
infection. The following factors were found to have significant associations with wound
8
infection: wound disruption/dehiscence (OR 16, CI 7.09-36.07, p <0.05), organ space SSI (OR
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9.63, CI 2.71-34.25, p<0.05), unplanned reoperation (OR 3.86, CI 2.85-5.24, p<0.05), UTI (OR
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2.79, CI 1.28-6.05, p<0.05), BMI≥40 vs. <25 (OR 2.28, CI 1.18-4.39, p< 0.05), post operative
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bleeding requiring a transfusion (OR 2.03, CI 1.49-2.78, p<0.05), operation time >300 minutes
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vs. 0-170 minutes (OR 1.98, CI 1.32-2.96, p<0.05, prior ipsilateral percutaneous intervention
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involving currently treated segment (OR 1.98, CI 1.30-3.01, p<0.05), history of COPD (OR
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1.73, CI 1.21-2.48, p<0.05) and length of hospital stay ≥28 days (OR 1.21, CI 0.60-2.48, p<0.05)
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(Table III).
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Predicted probability of wound infection: The probability of wound infection was calculated for
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all of the factors identified to be significant in the multivariable analysis, either alone or
18
combined, using the prediction equation generated from the model parameter estimates. The
19
probability of wound infection was 3.21% for patients whose length of hospital stay was ≥ 28
20
days, 4.51% for patients with history of COPD, 5.13% for patients with a prior ipsilateral
21
percutaneous intervention involving currently treated segment, 5.13% for patients with an
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operative time >300 minutes, 5.27% for patients who had significant bleeding requiring a
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transfusion post operatively, 5.87% for patients with BMI≥40, 7.08% for patients with a post-
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operative UTI, 9.55% for patients who needed an unplanned re-operation, 20.84% for patients
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with organ space SSI, 30.42% for patients who developed wound disruption/dehiscence and
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99.94% for patients who had all of these risk factors (Table IV).
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Patients undergoing lower extremity open revascularization in the current times likely represent a
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cohort of patients with the severest forms of atherosclerotic burden with poorly controlled risk
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factors and are at a high risk for developing surgical site infections. During the hospital stay,
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early signs of wound complications such has wound disruption or dehiscence, erythema,
13
tenderness or low grade fevers may be easily detected on daily rounds and can be easily treated
14
before they progress to a severe, deep wound infection and sepsis. Focused physical
15
examinations after lower extremity bypass surgery are of paramount importance. Close
16
attentions should be paid to the appearance of the surgical incisions. Minor wound disruptions
17
should be closely monitored, as these superficial wound disruptions can lead to complete wound
18
dehiscence and our data clearly shows that such patients are at an extremely high risk for
19
developing subsequent wound infections. Incidence of surgical site infections after lower
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extremity bypass in reported literature varies from 11%22 to 20%23. With bundle payment
21
models for treatment of surgical patients, physicians and hospitals are under increasing pressure
22
to reduce the length of hospital stay. Several surgical disciplines have devised new protocols to
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reduce the hospital stay24,25. While reducing the hospital stay is associated with advantages, such
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ACCEPTED MANUSCRIPT 13 as reduce postoperative pain and early return to work for majority of the patients; it carries with
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it the inherent disadvantage of patients not being examined by surgical team on a daily basis.
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This continued monitoring by health care providers ceases once patients leave the hospitals.
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Usually, the first postoperative appointment with surgical service is scheduled two to three
5
weeks after discharge from the hospital26. Whitby et al27 have shown that patients in general
6
lack clinical acumen and expertise to diagnose wound complications at an early stage. Despite
7
education and teaching about recognizing early signs of complications, majority of the patients
8
are unable to detect such complications at an early stage.
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Our study shows that the incidence of wound infections after lower extremity bypass is 13.7%
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and the median time for the diagnosis was 15 days. Our cohort shows the median length of
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hospital stay after lower extremity bypass surgery at 6 days. Other significant complications
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such as wound disruption/dehiscence and organ space SSI also occurred after the median length
13
of stay at 15 and 16 days respectively following surgical bypass (Table I). As noted, the onset
14
of any of these complications was apparent after a considerable time period following discharge
15
from the hospital. Most of the prior literature has focused on determining the risk factors for
16
developing wound complications after lower extremity bypass, during the hospital stay7,28-30. Our
17
analysis aims to compare all patients with wound infections as a separate group and compares it
18
to the group of patients with no wound infection to determine the factors associated with
19
increased risk of post operative complications after lower extremity bypass surgery. The
20
multivariable analysis (Table III) shows that wound disruption/dehiscence puts a patient at a 16-
21
fold risk for developing a wound infection. Similarly, occurrence of postoperative bleeding puts
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a patient at 2.4 fold risk for developing a wound infection and BMI≥40 increases the risk of
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developing post operative wound infection by 2.28 fold. Previously published studies have also
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ACCEPTED MANUSCRIPT 14 shown that morbid obesity is associated with an increased risk of developing surgical site
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infections1,30,31,32. Several factors may predispose obese patients to higher risk of infection:
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increased thickness of subcutaneous tissue, traction related injury to adipose tissue and high
4
bacterial count in deep groin creases. It is an established fact that morbidly obese patients have
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altered levels of leptin and adiponectin33 which predispose these patients to be at a higher risk for
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developing infections.
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days) to be associated with increased risk for developing surgical site infections. Our data also
8
shows that increased LOS is associated with development of such complications, however, in our
9
analysis, LOS greater than or equal to 28 days was found to be a significant predictor for
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Likewise, Wiseman et al34 have identified prolonged hospital stay (≥14
developing postoperative infections. Our group14 has previously shown that unplanned
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reoperation after lower extremity surgical bypass is associated with increased risk of
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readmission; this study shows that need for unplanned reoperation also puts patients at risk for
13
developing wound infections after lower extremity bypass surgery. Association between
14
reoperation and wound infection have been reported in prior reports as well34. Similarly, our
15
findings of association between postoperative bleeding requiring blood transfusion and wound
16
infection are consistent with previously published literature35. Cardiac surgery literature shows
17
an increased incidence of sternal wound infections among patients who receive blood
18
transfusions36. The association between blood transfusions and infection after cardiac and
19
vascular surgeries37-39 is considered to be dose dependent, suggesting that transfusions may
20
suppress the immune system. Basic science research suggests that blood transfusions may
21
downregulate macrophages and T-cell immunity40 and affect immunomodulation41.
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Surgical Care Improvement Project (SCIP) and many other national and institutional initiatives
23
have focused on standardizing surgical care to minimize the risk of perioperative infections.
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ACCEPTED MANUSCRIPT 15 These measures include, but are not limited to administration of preoperative antibiotics within
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one hour of surgical incision42-44. Some authors have reviewed the impact of showering with
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antiseptic solutions prior to surgery on the occurrence of post operative wound infections45.
4
Likewise, some surgical disciplines have investigated the use of chlorhexidine for cleansing the
5
skin prior to surgery and a randomized controlled trial showed that it reduced the surgical site
6
infection rate from 16.1% to 9.5%46. The protection against occurrence of surgical site infection
7
in these cases may be attributable to chlorhexidine’s rapid onset of action and persistence of its
8
antimicrobial effect despite being exposed to different body fluids. Gynecological literature47
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shows that chlorhexidine gluconate based preparations reduce the number of surgical site
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infections when compared to povidone based solutions. Likewise, orthopedic studies48 show
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superiority of 2% chlorhexidine gluconate with 70% alcohol over 0.7% iodine and 74%
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isopropyl alcohol. Patients with critical limb ischemia suffer from poor blood flow to the lower
13
extremities and it is quite possible that lack of blood flow to an extremity may reduce the
14
bioavailability of antibiotics to the surgical incision site, although there is no scientific evidence
15
to prove or disprove this hypothesis. For vascular surgery operations, it has been shown that the
16
development of postoperative infection is associated with three-time increase in the hospital
17
costs49.
18
Based on our analysis, we have developed a probability model for risk of developing a wound
19
infection after a lower extremity bypass surgery (Table IV). With further validation, it can be a
20
useful tool for prevention of wound infections in the future. It also allows for the identification
21
of patients who are at a high risk for developing wound infections. After identifying such
22
patients, clinicians can make the patients aware of their risk for developing wound infection after
23
lower extremity bypass operations. Patients who are at an extremely high risk for developing
AC C
EP
TE D
10
ACCEPTED MANUSCRIPT 16 such wound complications may then be given additional directions to examine their wounds on a
2
regular basis to detect early signs of infection and clinicians may choose to follow the selected
3
group of patients in clinic at a shorter time interval as compared to other patients. This
4
probability model is based on ACS-NSQIP, which is one of the best-standardized surgical
5
databases in the world, however we caution against the routine use of such models until they are
6
validated in prospective studies. Needless to say, predictability models like this provide a
7
framework for future research studies.
8
The results of this analyses should be interpreted in the context of several limitations. It is a
9
retrospective analysis of a large, national surgical database. It only includes variables that are
10
included in NSQIP database. It is important to point out that this database does not record the
11
type of preparation used to clean the skin before surgery. Despite being the largest surgical
12
database, hospital participation in NSQIP is voluntary and the results of this study may not be
13
generalized to all the hospitals. Lastly, this database does not record outcomes beyond thirty
14
days and any wound infection that occurs after thirty days will not be included in it. The
15
strength of this study is that NSQIP database is the largest and the most comprehensive surgical
16
database in the US.
17
and previously published results based this database have been validated.
18
To summarize, a significant number of wound disruptions after lower extremity bypass occur
19
after discharge from the hospital and predispose these patients to development of more serious
20
complications. Our predictability model identifies the patients who are at the highest risk for
21
developing wound infections and who would benefit from close monitoring by health care
22
providers.
23
TE D
M AN U
SC
RI PT
1
AC C
EP
The quality of this dataset is assured by the American College of Surgeons
ACCEPTED MANUSCRIPT 17 1 2 3
RI PT
4 5 6
SC
7 8
M AN U
9 10 11 12 13 14 15
1.
16
complications in continuous infrainguinal incisions after lower limb arterial reconstruction:
17
incidence, risk factors, and cost. Surgery 1996;119:378-83.
18
2.
19
readmission after lower extremity bypass. Journal of vascular surgery 2013;57:955-62.
20
3.
21
surgical site infection, 1999. Hospital Infection Control Practices Advisory Committee. Infection
22
control and hospital epidemiology 1999;20:250-78; quiz 79-80.
TE D
References
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McPhee JT, Barshes NR, Ho KJ, et al. Predictive factors of 30-day unplanned
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11
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14
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Iodine for Surgical-Site Antisepsis. The New England journal of medicine 2010;362:18-26.
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Uchiyama K, Takifuji K, Tani M, et al. Prevention of postoperative infections by
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Webster J, Osborne S. Preoperative bathing or showering with skin antiseptics to prevent
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2
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3
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5
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7
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9
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EP
TE D
10
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ACCEPTED MANUSCRIPT
Table 1. Complications After lower extremity bypass surgery and their relation to the time of development after the operation P value to median length of stay (6 days) <.0001 0.6271 0.0660 <.0001 0.0525 0.0023 0.1250 <.0001 <.0001 <.0001 0.0294 0.5034 0.1185 0.7905 0.4240
RI PT
Days from operation Median (Q1, Q3) 15.0 (10.0, 22.0) 6.5 (2.0, 16.0) 10.0 (3.0, 14.0) 15.0 (14.0, 21.0) 11.0 (5.50, 20.0) 16.0 (14.0, 23.0) 15.0 (9.0, 20.0) 1.0 (0, 3.0) 3.0 (1.0, 5.0) 2.0 (1.0, 4.0) 3.0 (2.0, 9.0) 4.0 (2.0, 14.0) 3.0 (2.0, 9.5) 4.0 (3.0, 12.0) 4.0 (1.0, 8.0)
M AN U
SC
Incidence N (%)/2646 361 (13.70) 50 (1.89) 45 (1.70) 43 (1.63) 24 (0.91) 17 (0.64) 5 (0.19) 455 (17.20) 81 (3.10) 62 (2.34) 33 (1.25) 21 (0.79) 16 (0.60) 15 (0.57) 15 (0.57)
Complication Deep Wound infection Untreated loss of Patency Urinary tract infection Wound disruption complications DVT/Thrombophlebitis Organ space SSI Pulmonary embolism Post-op bleeding requiring a transfusion MI/Stroke Myocardial infarction Pneumonia Cardiac arrest requiring CPR Progressive renal insufficiency Acute renal failure Stroke/CVA
AC C
EP
TE D
Complications reported within 30 days following lower extremity bypass surgery. Each complication shows the number of patients as well as the number of days from bypass. Those values were then compared to the median discharge date to evaluate the significance of the complication as it relates to the hospital discharge. The table above shows 3 major variables with significance post hospital discharge. Significant variables have a median of approximately 15 days following a lower extremity bypass. The median length of hospital stay for these patients is 6 days, indicating that patients should be closely monitored following hospital discharge to prevent wound infections or complications.
ACCEPTED MANUSCRIPT
Table II. Univariate Analysis of factors contributing to wound infection Wound Infection
(N=2284)
(N=361)
≤75
1701 (86.4)
267 (13.6)
>75-85
456 (86.9)
69 (13.1)
>85
127 (83.6)
25 (16.4)
Female
790 (84.7)
143 (15.3)
Male
1494 (87.3)
Variable
SC
Age (years)
M AN U
Sex
Race
OR (95% CI)*
RI PT
No Wound Infection
Reference
1.24 (0.99, 1.56)
218 (12.7)
Reference
18 (14.6)
1.15 (0.68, 1.93)
68 (15.0)
1.18 (0.88, 1.58)
4 (11.1)
0.84 (0.29, 2.39)
Non-Hispanic Black
386 (85.0)
Non-Hispanic Other
32 (88.9)
Non-Hispanic White
1505 (87.0)
225 (13.0)
Reference
<25
796 (89.7)
91 (10.3)
Reference
25-<30
770 (87.8)
107 (12.2)
1.22 (0.90, 1.64)
601 (82.3)
129 (17.7)
1.88 (1.41, 2.51)
70 (78.7)
19 (21.3)
2.37 (1.37, 4.12)
51 (92.7)
4 (7.3)
Reference
619 (90.6)
64 (9.4)
1.32 (0.46, 3.77)
CLI – Rest Pain
725 (85.9)
119 (14.1)
2.09 (0.74, 5.90)
CLI – Tissue Loss
861 (83.4)
171 (16.6)
2.53 (0.90, 7.10)
Symptoms Asymptomatic Claudication
EP AC C
>40
TE D
105 (85.4)
30-<40
High risk physiologic
0.568
0.96 (0.73, 1.28) 1.25 (0.80, 1.96)
Hispanic
BMI (kg/m^2)
P-value*
0.064
0.678
<0.001
<0.001
0.604
ACCEPTED MANUSCRIPT
factors Present
480 (85.6)
81 (14.4)
1.07 (0.82, 1.40)
1768 (86.4)
278 (13.6)
Reference
1840 (86.1)
298 (13.9)
429 (87.7)
60 (12.3)
1372 (85.4)
234 (14.6)
1.20 (0.95, 1.51)
886 (87.6)
126 (12.5)
Reference
260 (14.3)
1.19 (0.93, 1.52)
100 (12.4)
Reference
Pre-procedural medication – Aspirin Yes No
No Pre-procedural medication – Statin
1556 (85.7)
Yes
1.16 (0.86, 1.56)
None
597 (84.0)
114 (16.0)
Reference
Non-insulin dependent
1292 (87.8)
180 (12.2)
1.37 (1.06, 1.77)
Insulin dependent
395 (85.5)
67 (14.5)
1.22 (0.90, 1.65)
19 (12.9)
0.94 (0.57, 1.54)
2156 (86.3)
342 (13.7)
Reference
127 (84.7)
23 (15.3)
1.16 (0.73, 1.83)
2157 (86.5)
338 (13.6)
Reference
Dialysis dependent
No
128 (87.1)
AC C
Yes
0.332
Reference
EP
Diabetes mellitus
TE D
709 (87.6)
No
M AN U
Yes
SC
Pre-procedural medication Beta blocker
RI PT
Absent
0.126
0.179
0.045
0.793
Emergency operation Yes No
0.536
History of CHF 30 days prior to surgery Yes
0.271
ACCEPTED MANUSCRIPT
No
59 (81.9)
13 (18.1)
1.41 (0.77, 2.60)
2225 (86.5)
348 (13.5)
Reference
Yes
286 (81.7)
64 (18.3)
1.51 (1.12, 2.03)
No
1998 (87.1)
297 (12.9)
1883 (85.6)
316 (14.4)
401 (89.9)
45 (10.1)
Yes No
SC
Hypertension requiring medication
937 (86.3)
No
1347 (86.4)
M AN U
Smoking Yes
RI PT
History of severe COPD
Reference
1.50 (1.08, 2.08)
1.01 (0.81, 1.27)
212 (13.6)
Reference
35 (12.2)
0.87 (0.60, 1.26)
326 (13.8)
Reference
9 (81.8)
2 (18.2)
1.41 (0.30, 6.55)
2275 (86.4)
359 (13.6)
Reference
2160 (86.6)
335 (13.4)
Reference
52 (82.5)
11 (17.5)
1.36 (0.71, 2.64)
27 (75.0)
9 (25.0)
2.15 (1.00, 4.61)
45 (88.24)
6 (11.8)
0.86 (0.36, 2.03)
Yes
764 (83.5)
151 (16.5)
1.43 (1.14, 1.79)
No
1520 (87.9)
210 (12.1)
Reference
252 (87.8)
No
2032 (86.2)
Yes No Wound classification Clean
Contaminated Dirty/Infected
AC C
Clean/Contaminated
EP
Preoperative UTI
TE D
Yes
0.017
Reference
149 (13.7)
Transfer status
0.007
0.929
0.448
0.662
0.189
Open wound at time of operation
0.002
ACCEPTED MANUSCRIPT
Mean ± (standard deviation)
Mean ± (standard deviation)
3.56 (0.68)
3.51 (0.67)
Mean ± (standard deviation)
Mean ± (standard deviation)
2.01 (3.60)
1.87 (3.41)
0-170
611 (90.3)
66 (9.8)
170-225
563 (88.5)
73 (11.5)
225-300
568 (85.5)
96 (14.5)
1.57 (1.12, 2.18)
>300
541 (81.1)
126 (18.9)
2.16 (1.57, 2.97)
216 (13.6)
1.22 (0.95, 1.629)
69 (11.4)
Reference
76 (17.0)
1.60 (1.13, 2.27)
118 (87.4)
17 (12.6)
Reference
1681 (86.8)
256 (13.2)
1.06 (0.63, 1.79)
484 (84.6)
88 (15.4)
1.26 (0.72, 2.20)
Cardiac Surgery
2 (33.3)
4 (66.7)
12.43 (2.27, 68.13)
General Surgery
36 (97.3)
1 (2.7)
0.17 (0.02, 1.26)
Thoracic
57 (93.4)
4 (6.6)
0.44 (0.16, 1.21)
Days from hospital admission to operation
Absent Prior ipsilateral bypass involving currently treated segment
1377 (86.4)
Prior ipsilateral percutaneous intervention involving currently treated segment
370 (82.96)
No Disturbance-Mild Disturbance (1-2)
TE D
AC C
Severe Disturbance (3)
EP
ASA class
537 (88.6)
Life ThreateningMoribund (4-5)
M AN U
High risk anatomic factors
0.401
0.99 (0.96, 1.02)
0.499
Reference
SC
Operative time, minutes
0.91 (0.72, 1.14)
RI PT
Pre-op albumen level, mg/dl
1.20 (0.84, 1.71)
<0.001
0.031
0.388
Surgeon’s specialty:
0.008
ACCEPTED MANUSCRIPT
Vascular
2188 (86.1)
352 (13.9)
Reference
<7
1294 (87.9)
178 (12.1)
Reference
7-<13
638 (85.0)
113 (15.1)
14-<21
218 (85.5)
37 (14.5)
21-<28
81 (87.1)
12 (12.9)
>=28
53 (71.6)
21 (28.4)
Yes
73 (78.5)
20 (21.5)
1.78 (1.07, 2.95)
No
2211 (86.6)
341 (13.4)
Reference
109 (24.0)
2.42 (1.88, 3.12)
252 (11.5)
Reference
Yes
346 (76.0)
No
1938 (88.5)
SC
TE D
Combined MI and stroke
M AN U
Amputation
Bleeding
RI PT
Length of hospital stay, days
1.29 (0.99, 1.66) 1.23 (0.84, 1.81)
2.88 (1.70, 4.90)
Yes
63 (77.8)
18 (22.2)
1.85 (1.08, 3.16)
No
2221 (86.6)
343 (13.4)
Reference
36 (72.0)
14 (28.0)
2.52 (1.35, 4.72)
2248 (86.6)
347 (13.4)
Reference
19 (90.5)
2 (9.5)
0.67 (0.15, 2.87)
2265 (86.3)
359 (13.7)
Reference
281 (66.8)
140 (33.3)
EP
Untreated loss of patency Yes
AC C
No
0.002
1.08 (0.58, 2.01)
0.027
<0.001
0.025
0.004
Acute renal failure post operatively Yes No
2.865
Need for re-operation Yes
<0.001 4.52 (3.53, 5.77)
No
2003 (90.1)
221 (10.0)
ACCEPTED MANUSCRIPT
Transfusion >4 units PRBCs in 72hr before surgery
44 (93.6)
3 (6.4)
0.43 (0.13, 1.38)
2240 (86.22)
358 (13.8)
Reference
16 (76.2)
5 (23.8)
2268 (86.4)
356 (13.6)
Yes
49 (79.0)
13 (21.0)
No
2235 (86.5)
Yes
0.155
Yes No
31 (72.1)
17.78 (9.04, 34.96)
330 (12.7)
Reference
5 (29.4)
12 (70.6)
15.66 (5.48, 44.70)
2279 (86.7)
349 (13.3)
Reference
25 (75.8)
8 (24.2)
2.05 (0.92, 4.58)
2259 (86.5)
353 (13.5)
Reference
33 (78.6)
9 (21.4)
1.74 (0.83, 3.68)
2251 (86.5)
352 (13.5)
Reference
11 (68.8)
5 (31.3)
2.90 (1.00, 8.40)
2273 (86.5)
356 (13.5)
Reference
Yes No
EP
Postoperative pneumonia
TE D
2272 (87.3)
Organ space SSI
Yes
AC C
No
1.70 (0.92, 3.17) Reference
12 (27.9)
0.182
Reference
348 (13.5)
Wound disruption or dehiscence
No
M AN U
Post-operative MI
Yes
1.99 (0.73, 5.47)
SC
Cardiac arrest requiring CPR
RI PT
No
0.093
<0.001
<0.001
0.081
Need for re-intubation Yes No Progressive renal insufficiency (postoperative) Yes
0.144
0.049
ACCEPTED MANUSCRIPT
No
Yes
30 (66.7)
15 (33.3)
3.26 (1.74, 6.12)
No
2254 (86.7)
346 (13.3)
Reference
Yes
243 (57.2)
182 (42.8)
No
2041 (91.9)
179 (8.1)
RI PT
Postoperative UTI <0.001 Readmission
8.54 (6.68, 10.92)
<0.001
Reference
AC C
EP
TE D
M AN U
SC
* All odds ratios and p-values are from binomial logistic regression modeling wound infection, exact logistic regression used as needed. Odds ratios with 95% confidence limits not including 1 are considered significant.
ACCEPTED MANUSCRIPT
Table III. Multivariable model Risk Factor
Adjusted Odd’s Ratio P- Value
RI PT
(95% CI) 15.99 (7.09, 36.07)
<0.001
Organ space infection
9.63 (2.71, 34.25)
<0.001
Unplanned reoperation
3.86 (2.85, 5.24)
<0.001
Urinary tract infection (UTI)
2.79 (1.28, 6.05)
0.010
2.28 (1.18, 4.39)
<0.001
SC
Wound disruption/dehiscence
Post-operative bleeding requiring a transfusion
M AN U
BMI ≥40 vs. <25
Operation time >300 minutes vs. 0-170 minutes
2.03 (1.49, 2.78)
<0.001
1.98 (1.32, 2.96)
0.008
1.98 (1.30, 3.01)
0.004
1.73 (1.21, 2.48)
0.003
Total LOS ≥ 28 days vs. <7 days
1.21 (0.60, 2.48)
0.014
AC C
EP
TE D
Prior ipsilateral percutaneous intervention involving currently treated segment vs Prior ipsilateral bypass involving currently treated segment History of COPD
ACCEPTED MANUSCRIPT
TE D
EP AC C
+ +
SC
+ +
Unplanned Re-Operation
Organ Space Infection
Wound Disruption/ Dehiscence
+ +
+ +
+ +
RI PT
BMI≥40 Postoperative UTI
M AN U
Table 4: Predicted Probability of Deep Wound Infection LOS COPD Prior ipsilateral Operation Bleeding percutaneous ≥28 time >300 Requiring a intervention days minutes Transfusion involving currently treated segment + + + + + + + + + +
Probability of Surgical Wound Infection 3.21% 4.51% 5.13% 5.13% 5.27% 5.87% 7.08% 9.55% 20.84% 30.42% 99.94%