Accepted Manuscript Carotid Endarterectomy versus Carotid Artery Stenting: No Difference in 30-Day PostProcedure Readmission Rates Erin K. Greenleaf, David C. Han, Christopher S. Hollenbeak PII:
S0890-5096(15)00564-6
DOI:
10.1016/j.avsg.2015.05.013
Reference:
AVSG 2453
To appear in:
Annals of Vascular Surgery
Received Date: 21 January 2015 Revised Date:
5 May 2015
Accepted Date: 19 May 2015
Please cite this article as: Greenleaf EK, Han DC, Hollenbeak CS, Carotid Endarterectomy versus Carotid Artery Stenting: No Difference in 30-Day Post-Procedure Readmission Rates, Annals of Vascular Surgery (2015), doi: 10.1016/j.avsg.2015.05.013. 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.
ACCEPTED MANUSCRIPT 1 Carotid Endarterectomy versus Carotid Artery Stenting: No Difference in 30-Day PostProcedure Readmission Rates
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Erin K. Greenleaf,a David C. Han,a and Christopher S. Hollenbeaka,b a
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Corresponding Author: Christopher S. Hollenbeak, PhD The Pennsylvania State University College of Medicine Department of Surgery 500 University Drive, H151 Hershey, PA 17033-0850 Tel #: +1 717 531 5890 Fax #: +1 717 531 4464 E-mail:
[email protected]
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Department of Surgery, The Pennsylvania State University, College of Medicine 500 University Drive, Hershey, PA 17033-0850, USA E-mail:
[email protected];
[email protected] b Department of Public Health Sciences, The Pennsylvania State University, College of Medicine 500 University Drive, Hershey, PA 17033-0850, USA Email:
[email protected]
Conflict of Interest: None
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Funding Source: None
ACCEPTED MANUSCRIPT 2 ABSTRACT
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Objective: In the United States, ischemic stroke is a major cause of morbidity and mortality,
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precipitated by carotid artery stenosis in one out of every five individuals who suffer a stroke.
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Carotid endarterectomy (CEA) and carotid artery stenting (CAS) are two proven means of
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intervening on this disease process, with similar patient outcomes. Little is known about the
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burden of readmission following each of these procedures. We hypothesized that no difference in
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readmission rates within 30 days would exist for these two procedures, in spite of baseline
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differences that might exist between the two patient populations.
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Methods: Using the Pennsylvania Health Care Cost Containment Council (PHC4) database, we
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identified 4,319 people who underwent CEA (N=3,640) or CAS (N=679) in Pennsylvania in
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2011. Univariate analyses were performed to compare patient characteristics and outcomes,
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including reasons for readmission, between patients who underwent CEA and those who
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underwent CAS. Logistic regression was used to estimate the effect of intervention on 30-day
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readmission, after controlling for potential confounders. Time to readmission was analyzed using
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the Kaplan-Meier method.
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Results: Patients who underwent CEA and CAS differed in a few notable ways, including age,
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race, admission type, and comorbid conditions such as CHF, hemiplegia and paraplegia, and
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renal disease. The unadjusted rate of 30-day readmission was 9.37% for CEA and 10.75% for
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CAS (P=0.26). After controlling for patient and procedure characteristics, differences between
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30-day readmission rates were still not statistically significant (odds ratio=1.13; P=0.39). Finally,
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time to readmission was similar for those who underwent CEA and those who underwent CAS
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(P=0.19). Complications associated with surgery comprised less than 10% of primary
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readmission diagnoses for both groups.
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ACCEPTED MANUSCRIPT 3 Conclusions: Readmission rates following CEA and CAS for carotid artery stenosis are
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approximately 10%. In spite of differences between patients with carotid stenosis who are
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selected for endarterectomy and stenting, the choice of procedure does not appear to be
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associated with different readmission rates or time to readmission, even after controlling for
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patient characteristics.
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1. INTRODUCTION Cerebrovascular disease was among the top five causes of death in the United States in
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2010.1 Among those who survive, stroke is linked to long-term physical and cognitive disability.2
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The incidence of stroke in the US has been declining over the past three decades, a trend that
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may be related to improved diagnostic methods and treatment options.3 Indeed, carotid
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endarterectomy (CEA) and carotid artery stenting (CAS) are two interventions with proven
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benefit in appropriately selected patients.4-7
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In a milieu in which national annual expenditures on health care are measured on a scale
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of trillions, accounting for nearly one fifth of the gross domestic product, the 2010 Patient
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Protection and Affordable Care Act was passed.8 Section 3025 of the Act established the
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Hospital Readmissions Reduction Program. The program required the Centers for Medicare and
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Medicaid Services (CMS) to reduce payments to Medicare Inpatient Prospective Payment
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System (IPPS) hospitals with excess readmissions.9 In fiscal year 2015, these readmission
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penalties apply to five conditions—acute myocardial infarction, heart failure, pneumonia, total
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hip arthroplasty and total knee arthroplasty.10 It is expected that within only a few years,
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penalties will expand to readmissions following various procedures, including those of vascular
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surgery, and potential penalties will total approximately $1 billion.11,12
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In such an environment, it is important to understand variation in rates of readmission
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and risk factors for readmission for vascular surgery procedures. Such data form the foundation
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for initiatives to prevent their occurrence. The purpose of this study was to determine rates and
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risk factors for readmission following two commonly performed vascular procedures, CEA and
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CAS.
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2. METHODS
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2.1 Data
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This study was a retrospective cohort study using administrative data collected between 2011 and 2012 by the Pennsylvania Health Care Cost Containment Council (PHC4), an
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independent state agency mandated by law to address state health care costs. PHC4 collects
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detailed discharge data, including demographics, utilization, and source of admission
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information, on all inpatient and outpatient ambulatory procedure records annually from
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Pennsylvania hospitals and freestanding ambulatory surgery centers. Data on patients with
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formal admissions, including those for observation only, were included. Within this database,
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each patient is assigned a unique personal identifier, allowing readmissions to be tracked to a
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corresponding individual across Pennsylvania hospitals, even when readmission occurred at a
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facility different from that of the index admission.
We queried the PHC4 dataset to identify patients who underwent carotid endarterectomy
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and carotid artery stenting (N = 4,712) using International Classification of Disease, 9th Revision,
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Clinical Modification (ICD-9-CM) procedure codes for carotid endarterectomy (38.12) and
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carotid artery stenting (00.63). Patients who died during their index hospital admission were not
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included in the sample. After excluding 387 patients for missing covariates or outcome data and
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6 patients for undergoing both procedures, there were 3,640 index admissions for patients who
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underwent carotid endarterectomy and 679 who underwent carotid artery stenting.
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Analyses controlled for several patient level variables, including demographics (age,
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gender, and race), type of admission (elective, urgent, emergent), primary payer (Medicare,
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commercial, self-pay, HMO), and comorbidities (history of acute myocardial infarction,
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congestive heart failure, peripheral vascular disease, chronic obstructive pulmonary disease,
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diabetes, hemiplegia/paraplegia, renal disease, and cancer). Comorbidities were identified using
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ICD-9-CM diagnosis codes and were restricted to those available within the PHC4 database,
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coded according to the Charlson Comorbidity Index.13
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The primary outcome of interest in this study was 30-day readmission. PHC4 defines
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“readmission” as repeat hospitalization occurring less than 30 days after a patient is discharged
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alive.
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2.2 Statistical Analysis
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Statistical analysis was used to determine predictors of 30-day readmission after carotid
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endarterectomy and after carotid stenting, while controlling for the covariates described above.
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Baseline patient characteristics and comorbidities were compared between patients who
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underwent endarterectomy and patients who underwent stenting utilizing chi-square tests for
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binary and categorical variables and t-tests for continuous variables. We reported means or
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proportions with associated P-values.
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Logistic regression was used to model the effects of baseline characteristics and comorbidities on 30-day readmission. We report odds ratios with associated 95% confidence
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intervals. Goodness of fit of the logistic regression model was measured as the area under the
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receiver operating characteristic (ROC) curve. Odds ratios of readmission between patients
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undergoing endarterectomy and stenting were compared. Logistic regression was then used to
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generate coefficients for each covariate, for application in a decision-making model predicting
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likelihood of readmission in any patient with a known set of risk factors.
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Percent not readmitted was defined as patients who were not readmitted to the hospital
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within 30 days following discharge from their index hospitalization. After stratifying patients
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according to intervention, time-to-event analyses were performed using Kaplan-Meier
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CM codes and categorized according to body system, if not clearly a complication related to a
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recent procedure. A unique category for post-procedural complications was used for
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classification of these diagnoses. This study was deemed to be exempt from IRB approval by the
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Human Subjects Protection Office at Penn State College of Medicine. All analyses were
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performed using STATA software (version 12, College Station, TX). Statistical significance for
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all analyses was defined as a P-value <.05.
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3. RESULTS
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3.1 Patient characteristics
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Inpatient admissions to all non-VA Pennsylvania hospitals and free-standing surgical institutions during 2011 were included in the PHC4 database. The analysis sample included
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4,319 admissions for patients who underwent a carotid intervention after excluding admissions
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for which data regarding readmission status was missing (N = 387) as well as for patients who
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underwent both endarterectomy and stenting on their index admission (N = 6). Of these patients,
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3,640 underwent CEA and 679 underwent CAS. Demographic statistics are shown in Table I.
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Compared to patients who underwent CEA, patients who underwent stenting were more likely to
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be younger (P = .041), non-White (P < .0001), admitted non-electively (P < .0001), and have
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shorter length of stay (P=.015). Patients who underwent stenting had greater numbers of
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comorbidities, such as CHF (P < .0001), PVD (P = .004), hemiplegia and paraplegia (P = .011),
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and renal disease (P = .014), relative to patients who underwent endarterectomy (Table II).
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3.2 30-day readmission
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Table III presents the results of the logistic regression model of 30-day readmission, controlling for covariates. There was no statistically significant difference in likelihood of
ACCEPTED MANUSCRIPT 8 readmission based on intervention alone. However, there was a significantly lower likelihood of
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readmission of patients of non-white and non-black race (odds ratio [OR] 0.49, 95% CI 0.24-
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0.98). There was a significantly higher likelihood of readmission of patients admitted emergently
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(OR 1.35, 95% CI 1.02-1.79) or discharged to a facility other than home (OR 1.71, 95% CI 1.33-
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2.20). Having hemiplegia or paraplegia (OR 2.18, 95% CI 1.17-4.08), renal disease (OR 1.75,
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95% CI 1.30-2.34), and cancer (OR 2.19, 95% CI 1.17-4.10) prior to discharge were
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significantly associated with greater risk of readmission when all receiving CEA and CAS were
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considered jointly. Fig. 1 presents the odds ratios of readmission, comparing covariates when
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patients were segregated according to intervention. When modeled against each other, CAS
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patients were more likely than similar CEA patients to be readmitted if they were older than 80
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years old or female. They were less likely than similar CEA patients to be readmitted if they had
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a history of hemiplegia or paraplegia. There were no covariates for which CEA patients were
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more likely to be readmitted relative to comparable CAS patients.
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Coefficients generated from logistic regression were used to create a predictive model for readmission using equation 1.
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(1)
The probability of readmission following carotid intervention can be estimated for any patient
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following either CEA or CAS, provided a complete profile of information on age, sex, race,
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admission type, payer type, discharge destination, and pre-existing comorbidities. For example,
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the probability of readmission for a 75-year-old Hispanic female with Medicare and a history of
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diabetes and congestive heart failure admitted electively and discharged with home health care
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following CAS would be:
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(2)
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where the values in equation 2 are the coefficients found in Table III. Therefore, the probability
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of readmission would be 0.0796 or 7.96% following discharge. Note that coefficients for
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reference variables are not included in the computation of risk of readmission since they are
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already captured in the intercept term.
Primary diagnoses for readmission are presented in Table IV. After categorization of
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primary readmission diagnoses, both CEA and CAS patients were most often readmitted
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secondary to cerebrovascular etiologies (CEA 23.41%, CAS 30.76%). Central cardiovascular-
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related diagnoses (e.g. coronary atherosclerosis, atrial fibrillation) accounted for the next largest
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proportion of readmission diagnoses for both intervention groups (CEA 20.78%, CAS 23.06%).
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In spite of the known presence of vascular disease inherent to patients with carotid artery
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stenosis, patients were less frequently readmitted for peripheral vascular-related diagnoses (CEA
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4.45%, CAS 5.12%). Post-procedural complications accounted for 8.68% of readmissions
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following CEA and 7.68% of readmissions following CAS.
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3.3 Survival Analysis
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Results of Kaplan-Meier analysis are presented in Fig. 2. Of those patients who were readmitted within 30 days, time to readmission was not significantly different between those who
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underwent endarterectomy and those who underwent stenting (P = .19).
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4. DISCUSSION
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In our study of 30-day readmissions, we found no statistically significant difference in
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30-day readmission rates between patients who underwent CEA and CAS. Moreover, odds of
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readmission were similar between patients undergoing either intervention, as was time to
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readmission within 30 days. When the intervention groups were modeled as a single sample, the
ACCEPTED MANUSCRIPT 10 odds of readmission were greater if patients were admitted emergently, discharged to a
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destination other than home, or had a history of hemiplegia or paraplegia, renal disease, or
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cancer. Other (non-white, non-black) race was protective for readmission. When risk was
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modeled separately for CEA and CAS patients, we found that risk factors for readmission were
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similar for both procedures, with few exceptions. CAS patients were more likely than CEA
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patients to be readmitted if they were older than 80 years old or female but less likely than CEA
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patients to be readmitted if they had histories of hemiplegia or paraplegia. When studying the
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CEA sample separately, none of the observed covariates were associated with significantly
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different risk of readmission relative to the CAS sample. Primary diagnoses for readmission were
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predominantly cerebrovascular and cardiovascular for patients who underwent CEA and CAS,
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with diagnoses unambiguously related to post-procedural complications ranking third and fourth,
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respectively, in frequency of readmission diagnoses.
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Most previous studies of readmission rates following CEA report a rate between 6% and
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11.2%, which is consistent with the estimate of readmission of 9.4% in our patient population.14-
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previously published estimates. Galinanes et al. report a 30-day readmission rate of 11.11%, a
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0.31 percentage point difference relative to the present study that may be of limited clinical
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significance.14 Yet, our finding of no statistically significant difference in periprocedural
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readmission between CEA and CAS is in contrast to the Galinanes study, which showed
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significantly greater readmission rates after CAS relative to CEA at 30, 60, and 90 days
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following interventions.14 Although both our study and Galinanes et al. demonstrated higher
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absolute readmission rates for CAS relative to CEA, the difference between studies in
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statistically significant findings may illustrate the variation in practice patterns, and therefore
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ACCEPTED MANUSCRIPT 11 thresholds for readmission, across a national sample as in Galinanes et al. and a statewide sample
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in the present study. Like the present study, although not in patients undergoing carotid
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intervention specifically, other studies have failed to detect a consistent statistically significant
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benefit of open vascular surgery relative to endovascular techniques with respect to readmission
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rates.20,21
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Our study found that for all carotid interventions, the odds of readmission were lower in
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patients who were in the “other” race category, which is consistent with previous studies.14,17,22
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Also similar to previous studies, we found that patients admitted on an emergent basis or
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discharged to a destination other than home were more likely to be readmitted within 30
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days.13,15,23 With regard to patient comorbidities, many studies identify comorbidities
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contributing to readmission in general, but fewer have investigated comorbidities that affect
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readmission following carotid intervention.14-16,18,24 In an analysis of Medicare claims data,
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Jencks et al. identified the majority of their studied comorbidities, including congestive heart
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failure, chronic obstructive pulmonary disease, diabetes mellitus, coagulopathy, peripheral
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vascular disease, pulmonary disease and renal disease, as contributors to greater odds of
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readmission.25 We found, among a population of patients of all ages undergoing carotid
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intervention, history of hemiplegia or paraplegia, renal disease and cancer were significantly
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associated with greater odds of 30 day readmission. The present study is consistent with previous
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studies looking at CEA, if not both CEA and CAS, exclusively.14-16,18
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A further analysis of risk factors for readmission, stratified according to intervention
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type, interestingly demonstrated that age over 80 years old and female gender contributed to a
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greater likelihood of readmission for patients undergoing CAS, but not for those undergoing
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CEA. A history of hemiplegia or paraplegia was actually associated with lower odds of
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level of elevated risk, such as in CAS patients, and an incapacitating neurologic deficit, thereby
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increasing the likelihood of a highly supportive home environment capable of managing post-
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procedure sequelae, which might otherwise be cause for readmission. Yet although it is plausible
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that those with a history of hemiplegia or paraplegia have a strong established support system, it
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is also plausible that the protective role of hemiplegia or paraplegia is a spurious artifact born
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from multivariable analysis on a large data set.26
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When reasons for readmission were identified, cerebrovascular and central cardiovascular diagnoses accounted for approximately half of all diagnoses for 30-day readmission among
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patients who underwent either CEA or CAS. Reasons for readmission that were unambiguously
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procedure-related comprised only 8.68% and 7.68% of all readmission diagnoses for CEA and
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CAS patients, respectively. While it may be expected that patients requiring carotid intervention
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for carotid artery stenosis also have extensive cardiovascular pathology for which subsequent
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hospital admissions would be warranted, readmission diagnoses related to peripheral vascular
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diagnoses comprised only 4.45% of readmission diagnoses for CEA patients and 5.12% of
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readmission diagnoses for CAS patients. Previous studies of patients undergoing carotid
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intervention corroborate the finding of cardiac-related diagnoses as the most common cause of
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unplanned readmission.14,16
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Readmission diagnoses that are unequivocally associated with the index procedure are of
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particular interest to providers as they represent an opportunity for preemptive intervention. In an
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analysis of 30-day readmission diagnoses for all patients who underwent any inpatient surgery
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within the Veterans Health Administration, patients who underwent peripheral vascular surgery
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were most often readmitted for infection, commonly of an implanted prosthesis or otherwise
ACCEPTED MANUSCRIPT 13 localized to the surgical site.27 In the current study, however, post-procedural complications,
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including infection, did not predominate among readmission diagnoses for patients undergoing
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either CEA or CAS, whereas cardiovascular and cerebrovascular causes were more commonly
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implicated in unplanned readmissions following both interventions. This may be related to the
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typically clean nature of neck procedures and surgical wounds. Unfortunately, we were limited
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in knowing whether patients with cerebrovascular-related diagnosis codes, which described the
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most common readmission diagnoses, were actually readmitted for complications directly related
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to their carotid interventions. The ambiguity in ICD-9-CM coding limits our confidence in the
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reliability of readmission diagnoses.
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This is a retrospective analysis of administrative data, which carries some inherent limitations. First, there are variables that were not available in the data set that may be potential
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confounders and could not be controlled. For example, presence and severity of neurologic
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symptoms upon presentation at index admission is not captured in the PHC4 dataset, although it
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may modulate relationships between predictive factors and readmission. Information on
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preoperative functional status was also not part of the dataset. This additional information could
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have potentially informed expectations for patient convalescence and likelihood of readmission.
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Second, many of our variables, including the identification of CEA and CAS procedures, were
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identified using diagnosis and procedure codes. There is always the potential for coding errors,
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although it is unlikely that such errors would be systematic. Third, the PHC4 data set includes
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only inpatient admission to acute care hospitals in Pennsylvania, which may not be
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representative of all patients undergoing carotid interventions. Because patients are not tracked
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beyond state borders, readmission to a non-Pennsylvania hospital would be outside of the scope
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of this data set because of geographic limitations. Moreover, specific data regarding primary
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diagnosis for readmission may not be reliably reported and coded, contributing to ambiguity
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regarding the relationship between carotid intervention and readmission.
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5. CONCLUSION We conclude based on this statewide analysis of discharge data that 30-day readmission
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rates are similar for patients undergoing CEA and CAS. Other factors, however, are related to
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readmission for both procedures, such as urgency of admission and comorbidities. Thirty-day
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readmissions have been under more intense scrutiny since the HRRP in 2010.9 Given the
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forthcoming expansion of penalties for readmissions to include those within 30 days after
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vascular surgery, it is crucial to determine targets for change for patients undergoing CEA and
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CAS.8,11,12 Future efforts should be directed toward elucidating costs associated with
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readmission, determining readmission and complication rates over a longer post-operative
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interval, and ultimately, assessing the effectiveness of interventions to reduce readmissions in
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this patient population.
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ACCEPTED MANUSCRIPT 19 Table I. Comparison of baseline demographic and clinical data of all patients undergoing carotid intervention stratified by intervention type CEA CAS Variable (n = 3,640) (n = 679) P value Age 0.041 18-64 23.9% 25.2% 65-74 36.0% 39.2% 75-79 18.5% 16.2% 80+ 21.6% 19.4% Sex 0.443 Male 58.2% 59.8% Female 41.8% 40.2% Race <0.0001 White 94.6% 86.3% Black 2.8% 4.7% Other 2.6% 9.0% Admission type <0.0001 Elective 79.4% 72.0% Urgent 6.8% 13.4% Emergent 13.8% 14.6% Payer type 0.056 Medicare 74.4% 70.7% Commercial 20.6% 23.9% Selfpay 0.3% 0.1% HMO 33.6% 28.9% Discharge destination 0.213 Home 82.5% 85.0% SNF 4.2% 4.9% Home health Care 13.2% 10.2% Other 0.0% 0.0% LOS 2.71 2.36 0.015 HMO: Health maintenance organization; SNF: Skilled nursing facility; LOS: Length of stay
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ACCEPTED MANUSCRIPT 20 Table II. Comparison of baseline comorbidities of all patients undergoing carotid intervention stratified by intervention type CEA CAS Variable (n = 3,640) (n = 679) P value AMI 12.0% 11.3% 0.652 CHF 5.5% 9.4% <0.0001 PVD 15.1% 19.6% 0.004 COPD 20.3% 21.4% 0.543 Diabetes 31.9% 33.4% 0.423 HP/PAPL 1.2% 2.5% 0.011 Renal Dz 9.5% 12.5% 0.014 Cancer 1.5% 1.9% 0.438 AMI: Acute myocardial infarction; CHF: Congestive heart failure; PVD: Peripheral vascular disease; COPD: Chronic obstructive pulmonary disease; HP/PAPL: Hemiplegia or Paraplegia
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Table III. Results of a logistic regression model of intervention type on 30-day readmission, controlling for other covariates (area under ROC curve = 0.6262) 95% Confidence Variable Odds Ratio Coefficient Lower Upper P value Intervention CEA REFERENCE Stent 1.15 0.14 0.88 1.52 0.310 Age 18-64 REFERENCE 65-74 1.16 0.14 0.83 1.60 0.385 75-79 1.12 0.11 0.77 1.63 0.549 80+ 1.20 0.18 0.83 1.73 0.326 Sex Male REFERENCE Female 1.15 0.14 0.93 1.42 0.191 Race White REFERENCE Black 1.19 0.17 0.69 2.02 0.533 Other 0.49 -0.72 0.24 0.98 0.043 Admission Type Elective REFERENCE Urgent 1.21 0.19 0.84 1.73 0.314 Emergent 1.35 0.30 1.02 1.79 0.036 Payer type Medicare REFERENCE Commercial 1.06 0.06 0.77 1.47 0.716 Selfpay 0.84 -0.18 0.10 6.82 0.867 HMO 1.03 0.03 0.83 1.28 0.796
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Discharge destination Home REFERENCE Other 1.71 0.54 1.33 2.20 <0.0001 Comorbidities AMI 1.09 0.09 0.80 1.49 0.566 CHF 1.10 0.10 0.75 1.63 0.613 PVD 1.15 0.14 0.88 1.51 0.314 COPD 1.26 0.23 0.99 1.62 0.060 DM 1.10 0.10 0.89 1.37 0.376 HP/PAPL 2.18 0.78 1.17 4.08 0.015 Renal Disease 1.75 0.56 1.30 2.34 <0.0001 Cancer 2.19 0.78 1.17 4.10 0.014 HMO: Health maintenance organization; AMI: Acute myocardial infarction; CHF: Congestive heart failure; PVD: Peripheral vascular disease; COPD: Chronic obstructive pulmonary disease; DM: Diabetes mellitus; HP/PAPL: Hemiplegia or Paraplegia
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Table IV. Comparison of primary diagnoses for 30-day readmission stratified by intervention type CEA CAS Primary Diagnosis (n = 3,910) (n = 415) Cerebrovascular 23.41% 30.76% Cardiovascular, Central 20.78% 23.06% Procedure-related Complication 8.68% 7.68% Pulmonary 8.39% 6.41% Genitourinary 5.51% 8.97% Cardiovascular, Peripheral 4.45% 5.12% Gastrointestinal 6.01% 6.40% Neurologic 3.93% 5.12% Endocrine 2.62% 1.28% Hematologic 5.52% 1.28% Other 7.04% 3.84%
ACCEPTED MANUSCRIPT 24 FIGURE LEGENDS Fig. 1. Forest plot for relation between carotid intervention and odds of readmission. Relative to similar CEA patients, CAS patients were more likely to be readmitted if they were older than 80
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Fig. 2. Time to readmission for patients undergoing carotid intervention based on intervention type. Of those patients who were readmitted within 30 days, there was no statistically significant
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