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Preoperative pulmonary function tests do not predict the development of pulmonary complications after elective major abdominal surgery: A prospective cohort study
Journal Pre-proof Preoperative pulmonary function tests do not predict the development of pulmonary complications after elective major abdominal surgery: A prospective cohort study Shinichiro Yokota, Masaru Koizumi, Kazutomo Togashi, Mitsuaki Morimoto, Yoshikazu Yasuda, Naohiro Sata, Alan Kawarai Lefor PII:
S1743-9191(19)30355-3
DOI:
https://doi.org/10.1016/j.ijsu.2019.11.032
Reference:
IJSU 5167
To appear in:
International Journal of Surgery
Received Date: 22 July 2019 Revised Date:
23 October 2019
Accepted Date: 25 November 2019
Please cite this article as: Yokota S, Koizumi M, Togashi K, Morimoto M, Yasuda Y, Sata N, Lefor AK, Preoperative pulmonary function tests do not predict the development of pulmonary complications after elective major abdominal surgery: A prospective cohort study, International Journal of Surgery, https:// doi.org/10.1016/j.ijsu.2019.11.032. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. 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. © 2019 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.
Original article
PREOPERATIVE PULMONARY FUNCTION TESTS DO NOT PREDICT THE DEVELOPMENT OF PULMONARY COMPLICATIONS AFTER ELECTIVE MAJOR ABDOMINAL SURGERY: A PROSPECTIVE COHORT STUDY
Shinichiro Yokota1,2, Masaru Koizumi1, Kazutomo Togashi1, 3, Mitsuaki Morimoto1, Yoshikazu Yasuda1, Naohiro Sata1, Alan Kawarai Lefor1
1Department of Surgery, Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, 329-0498, Japan 2Department of Surgery, Allegheny General Hospital, 320 East North Avenue, Pittsburgh, PA, USA 15212 3Department of Coloproctology, Aizu Medical Center Fukushima Medical University, 21 Kawahigashi, Aizuwakamatsu, 969-3492, Japan
Corresponding author: Shinichiro Yokota, MD, PhD Department of Surgery, Jichi Medical University 3311-1 Yakushiji, Shimotsuke,329-0498, Japan Tel. +81 285 58 7371, Fax. +81 285 44 3234, Email: [email protected]
Conflicts of interest: The authors have no conflict of interest to declare. 1
International Journal of Surgery Author Disclosure Form The following additional information is required for submission. Please note that failure to respond to these questions/statements will mean your submission will be returned. If you have nothing to declare in any of these categories, then this should be stated. Please state any conflicts of interest The authors have no conflict of interest to declare.
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Please state whether Ethical Approval was given, by whom and the relevant Judgement’s reference number This study was approved by the Ethics Committee at Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, 329-0498, Japan
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1. Name of the registry: the University Hospital Medical Information Network (UMIN) in Japan 2. Unique Identifying number or registration ID: UMIN ID: UMIN000002753. 3. Hyperlink to the registration (must be publicly accessible): https://upload.umin.ac.jp/cgi-openbin/ctr/ctr_his_list.cgi?recptno=R000003321
1
Author contribution Please specify the contribution of each author to the paper, e.g. study design, data collections, data analysis, writing. Others, who have contributed in other ways should be listed as contributors. SY, TK, YY, NS and AKL conceived of and designed the study. SY and MK performed data extraction. SY, TK, and MM performed the data analysis and interpreted the results. SY and AKL wrote the manuscript. SY, MK, TK, MM, AKL, YY, and NS revised the manuscript.
Guarantor The Guarantor is the one or more people who accept full responsibility for the work and/or the conduct of the study, had access to the data, and controlled the decision to publish. Please note that providing a guarantor is compulsory. Shinichiro Yokota and Alan Kawarai Lefor
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2 1
Abstract (200 words)
2
Background: Data describing the association of preoperative pulmonary function testing (PFT) with
3
postoperative pulmonary complications (PPC) are inconsistent. We conducted this prospective study to
4
determine the ability of PFT to predict PPC.
5
Materials and Methods: Data were prospectively collected from 676 patients who underwent elective
6
abdominal surgery (emergency and thoracic operations excluded). The primary outcome was the occurrence
7
of PPC within 30 days. Patient and procedure-related factors were examined as risk factors. Multivariate
8
logistic regression analysis was performed using risk factors identified with univariate analysis and area
9
under the curve (AUC) analysis performed.
10
Results: PPC occurred in 29 patients (4.9%). History of smoking or abnormal physical examination were
11
not significantly associated. Multivariate analysis identified age (p=0.03), operative time (p=0.02), blood
12
transfusions (p=0.002), and %VC (p=0.001) as significant risk factors. AUC with a model including age,
13
operative time, and blood transfusion was 0.83. The addition of %VC to these three variables increased the
14
AUC to 0.89 (p=0.1).
15
Conclusions: Age, operative time, blood transfusion, and %VC are significantly associated with an
16
increased risk of PPC. The addition of %VC to other risk factors did not significantly improve the ability to
17
predict PPC, showing that preoperative PFT is not helpful to predict PPC.
18 19
2
3 20
Keywords:
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Complications; Pulmonary Function Test; Preoperative Care.
Elective
Surgical
Procedures;
Abdominal
22 23
3
Surgery;
Postoperative
Pulmonary
4 24
1. Introduction
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Abdominal surgery is associated with relatively high rates of postoperative pulmonary
26
complications (PPC)[1]. PPC are as common as cardiovascular complications and similarly contribute to
27
morbidity, mortality, and hospital length of stay[2, 3]. Preoperative evaluation of risk factors associated with
28
developing PPC is as important as preoperative cardiac evaluation.
29
While preoperative pulmonary function testing (PFT) before thoracic surgery is well accepted, data
30
regarding its necessity before non-thoracic surgery is inconsistent [4]. In 2006, the American College of
31
Physicians (ACP) published the first clinical guidelines for preoperative risk assessment to prevent PPC for
32
patients undergoing non-cardiothoracic surgery[5]. This document emphasizes clinical evaluation to identify
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patient- and procedure-related risk factors. The guideline recommends against routine PFT prior to surgery
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because a systematic review of the literature did not show PFT to be superior to history and physical
35
examination in predicting which patients will develop PPC[2, 5, 6]. However several subsequent studies
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have shown an association between the preoperative PFT and development of PPC among patients
37
undergoing abdominal surgery [7-12].
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A lack of consensus regarding the predictive value of preoperative PFT may cause confusion on a
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practical level and lead to the continued use of routine PFT before abdominal surgery under general
40
anesthesia despite the recommendation in the ACP guidelines[13]. In fact, preoperative PFT is performed
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routinely in Japan for preoperative pulmonary evaluation of all patients before elective abdominal surgery
42
under general anesthesia[9, 10, 14]. In addition, there are only a few studies in the literature that directly 4
5 43
compared predictive values of clinical risk factors and PFT in patients undergoing elective abdominal
44
surgery [15]. Thus, it is still not clear whether clinical evaluation alone, such as history and physical
45
examination, can sufficiently and accurately predict the risk of PPC following various types of abdominal
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surgery under general anesthesia. The existing literature is not clear whether PFT contribute to the ability to
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predict the development of PPC.
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The aim of this prospective study is to evaluate whether the history and physical examination are
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equally or more predictive of clinically significant PPC than PFT among patients undergoing elective
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abdominal surgery under general anesthesia at a tertiary referral center in Japan.
51 52
2. Material and methods
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2.1. Selection of study subjects
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We conducted this prospective study from November 2009 to March 2011 at an 1130-bed teaching
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hospital and a tertiary referral center. Patients scheduled to undergo elective abdominal surgery under
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general anesthesia during the study period were registered as study subjects. Patients were included in the
57
study if the surgery involved the manipulation of an abdominal organ. We excluded patients who were
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undergoing elective surgery for inguinal hernia and ventral hernia[16]. We also excluded patients who
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underwent intrathoracic surgery such as esophagectomy or emergency operations. This study was approved
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by the Ethics Committee. The study was registered at the University Hospital Medical Information Network
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(UMIN) at www.umin.ac.jp (UMIN ID: UMIN000002753. ) 5
6 62
The work has been reported in line with the STROCSS criteria [27].
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We developed a standardized preoperative 10-point checklist. To complete the checklist, residents
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conducted a standardized history and physical examination for each patient during a preoperative visit
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usually within one week prior to surgery. This 10 point checklist included potential patient-related risk
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factors described in the ACP guidelines[2]: 1) age, 2) previously diagnosed chronic obstructive pulmonary
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disease (COPD), 3) previously diagnosed asthma, 4) previously diagnosed chronic heart failure, 5) the
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American Society of Anesthesiologists (ASA) classification, 6) Functional Dependency, 7) Smoking History,
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8) Body Mass Index (BMI), 9) preoperative albumin level, and 10) physical examination. We used the ASA
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classification as recorded in the anesthesiology record. Functional dependency was the need for equipment
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such as a cane or others in activities of daily living[2]. Functional dependency was classified into categories
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(e.g. none, partial, and total). Smoking history was classified into three categories (e,g. never smoked, recent
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smoker (stopped over 4 weeks prior to operation), and current smoker (within 4 weeks of operation)). BMI
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and preoperative serum albumin level data were available for all patients. Physical examination was
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classified as normal or abnormal after performing three specific maneuvers: cough test, wheeze test, and
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forced expiratory time as described in detail by McAlister et al[8]. We routinely perform preoperative PFT
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for patients undergoing abdominal surgery under general anesthesia at our hospital and PFT data were
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available for all patients. We collected intraoperative data such as operative time, duration of anesthesia,
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incision site (upper or lower abdominal)/type of surgery (open or laparoscopic), crystalloid replacement
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volume, urine output, blood transfusion volume, and estimated blood loss from the operative record for all 6
7 81
patients. Patients were divided into 3 groups based on the location of the incision and the type of surgery:
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open surgery with an upper abdominal incision (i.e. above the umbilicus), open surgery with lower
83
abdominal incision (i.e. below the umbilicus), and laparoscopic surgery.
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The primary outcome was the occurrence of PPC within 30 days following surgery. We adopted explicit
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definitions for clinically significant PPC described by McAlister et al. [8] including: (1) respiratory failure
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requiring mechanical ventilation, (2) pneumonia (defined using the Centers for Disease Control and
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Prevention definition for postoperative pneumonia), (3) atelectasis requiring bronchoscopy, or (4)
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pneumothorax or pleural effusion requiring percutaneous intervention. The decision to use interventions
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such as mechanical ventilation, bronchoscopy, or others was left to the discretion of the attending
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physician[8]. We collected data on the occurrence of PPC through a review of the medical chart, laboratory,
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and radiology data. Only the first PPC occurring in any one patient was analyzed.
92 93 94
2.2 Statistical Analysis Data were described non-parametrically, analyzed using two-sided statistics, and considered
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significant with p< 0.05. Univariate analysis of data was performed using the chi-square and Fisher`s exact
96
tests for categorical data, and the Mann-Whitney U tests for continuous data. Variables considered
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significant (p<0.05) in univariate analyses were then confirmed by the coefficient of association for strong
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linear correlation[9]. Variables with a correlation coefficient of >0.7 were considered to have a strong linear
99
correlation and excluded from multivariate logistic regression analyses. Variables included in multivariate 7
8 100
logistic regression analyses were dichotomized based on cut-off points calculated using a receiver operator
101
characteristics (ROC) curve. To compare the predictive ability of multivariate models, ROC curves were
102
tested for statistically significant differences[17]. In addition, sensitivity, specificity, positive predictive
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value, negative predictive value, diagnostic accuracy, positive likelihood ratio, and negative likelihood ratio
104
were calculated for models developed using independent risk factors identified with multivariate
105
analysis[18]. Statistical analyses were performed using EZR (Easy R)[19].
106 107 108
3. Results A total of 983 patients were eligible for the study (Figure). Of these, 307 (31%) patients were
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excluded for the following reasons: 49 (5.0%) because surgery was delayed or canceled; 244 (24%) due to
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incomplete preoperative checklist or missing data; eight (0.8%) due to the addition of intrathoracic incision
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during operation; six (0.6%) patients lost to follow up. Finally, 676 (69%) patients were enrolled in the study.
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The majority of patients underwent abdominal surgery: 243 patients (36.0%) had colon and rectum surgery,
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208 (30.8%) had gastric surgery, 149 (22.0%) had hepatobiliary / pancreas surgery, and 76 (11%) had other
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abdominal surgery, of organs such as the spleen, adrenal gland, and kidney. Laparoscopic surgery was
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performed in 259 patients (38.3%).
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A total of 29 PPC occurring in 676 patients (Incidence of PPC: 4.3%) were recorded including nine
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patients with pneumonia, eight with pleural effusions, seven with respiratory failure, and five with
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atelectasis (Table 1). Length of stay was significantly longer for patients with PPC compared to patients
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without PPC, median 22 days (interquartile range (IQR) 7) versus 12 days (IQR 13) (p=5.51E-08). 8
9 120
Among the patient-related factors (Table 2), age (p=6.E-05), ASA classification (p=0.015), and
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serum albumin level (p=0.002) were considered potential risk factors following univariate analyses. Gender,
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past medical history of cardiopulmonary diseases (COPD, asthma, or congestive heart failure), functional
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status, smoking history, BMI, and abnormal physical examination were not statistically significant variables.
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Preoperative PFT parameters (Table 3) with p<0.05 in univariate analyses included vital capacity
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(VC) (p=0.004), percent predicted VC (%VC) (p=5.32E-05), forced vital capacity (FVC) (p=0.003), and
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forced expiratory volume in 1 second (FEV1) (p=0.003).
127
Overall, the median duration of surgery was 246 min (IQR 147) (Table 4). Comparison of
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intraoperative variables between patients with PPC and without PPC showed duration of surgery (p=0.0007),
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duration of general anesthesia (p=0.0004), bleeding volume (p=0.0004), blood transfusion volume
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(p=3E-11), crystalloid replacement volume (p=0.004), and incision site (p=0.006) to be possible risk factors
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for the development of PPC with p<0.05.
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Examination of correlation coefficients among significant variables following univariate analysis
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revealed five variables with strong linear correlations (correlation coefficient > 0.7) (Supplementary Table 1).
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These variables (VC, FVC, duration of general anesthesia, bleeding volume, crystalloid volume) were
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excluded. The eight remaining variables included in the multivariable logistic regression analyses included
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1) age, 2) ASA classification, 3) serum albumin, 4) FEV1, 5) %VC, 6) duration of surgery, 7) blood
137
transfusion, and 8) incision site/ type of surgery. Among these variables, age (OR 2.97 for age≥70 years,
138
p=0.026), %VC (OR 4.53 for %VC<104.5, p=0.001), duration of surgery (OR 3.27 for duration of 9
10 139
surgery≥401min, p=0.015), blood transfusion (OR 4.55 for blood transfusion≥241ml p=0.002) were
140
identified as the best independent predictors of PPC (Table 5).
141
ROC curves were constructed for 10 models with different numbers of variables and the AUC for each
142
model was calculated (Table 6). Model 1 with all four variables had the highest AUC with 0.89. However,
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Model 2 with three variables (Age, duration of surgery, and blood transfusion, but without %VC) yielded a
144
similar, non-inferior AUC of 0.83 without a statistically significant difference (p=0.108). % VC Models 3
145
and 4, both containing three variables also resulted in similar AUC (0.86, 0.88, respectively). Model 5 with
146
preoperative variables alone (age and %VC) or Model 6 with intraoperative variables alone (duration of
147
surgery and blood transfusion) had significantly lower AUC (0.77, 0.72, respectively) when compared to
148
Model 1. Models 7-10 with single predictive variables also had significantly lower AUC.
149
When a cut-off value of %VC<80 (commonly used to define a restrictive pattern) was used for
150
multivariate analysis, the same four independent variables (age≥70 years, %VC<80, duration of
151
surgery≥401min, and blood transfusion≥241ml) were identified as significant (data not shown).
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Comparison of the AUC between Model 1 and Model 2 with a cut off value %VC<80 showed a similar
153
result (0.87, 0.83, respectively with p=0.21) as Table 6.
154 155 156 157
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11 158 159
4. Discussion
160
PPC are equally prevalent as cardiac complications and similarly influence postoperative morbidity,
161
mortality, and length of stay[2, 4, 13]. In 2006, the American College of Physicians (ACP) published a
162
clinical guideline for preoperative pulmonary risk stratification for patients undergoing non-cardiothoracic
163
surgery, which recommended against “routine” use of PFT preoperatively as the data are mixed regarding its
164
predictive value in the existing body of literature[2]. Although many studies have analyzed risk factors to
165
predict the development of PPC in the last 20 years[7-10, 12, 13, 20, 21], results varied considerably across
166
studies partly because of differences in study populations, outcomes definitions, and study designs[13]. Thus,
167
there is still inconsistency in the data regarding the predictive value of PFT before elective major abdominal
168
surgery under general anesthesia[9, 10, 12, 20]. There is a major difference in the use of preoperative PFT in
169
Japan compared to many western countries. Reports indicate that preoperative PFT are performed
170
routinely[10] or before over 70% of low-risk operations under general anesthesia in Japan[14], while a
171
similar report from Canada indicated that preoperative PFT was performed in less than 8% of patients[22].
172
This striking contrast in the use of PFT demonstrates the lack of a global consensus for preoperatively
173
predicting the risk of developing PPC.
174
In this study, we conducted a single institution, prospective cohort study in Japan, including 676
175
patients who underwent major abdominal surgery under general anesthesia, to determine the incidence and
176
best predictors of PPC in this population. We also compared PFT data with clinical data, which were
11
12 177
obtained through a standardized history and physical examination, as few studies have made such direct
178
comparisons in the past[2]. In doing so, we aimed to answer the question of whether or not the practice of
179
routine preoperative PFT should be continued for patients undergoing major abdominal surgery under
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general anesthesia. The strengths of this present study are its prospective study design, clear inclusion and
181
exclusion criterion, a well-defined study population, and explicit definitions of clinically significant PPC
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which required interventions based on a prior study[8]. Every patient in this study group underwent
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preoperative PFT as it is the standard of care.
184
This study found an incidence of PPC (4.3%) comparable to that in previous reports (2.7-8%),
185
including the study by McAlister, which used the same definition of PPC[2, 7-9]. PPC identified in this
186
study were indeed clinically significant considering the difference in the length of stay found between
187
patients with and without PPC. A total of 26 variables (18 patient-related risk factors and 8 procedure-related
188
risk factors) were examined as potential predictors of PPC. Two patient-related risk factors (age≥70
189
years, %VC<104.5) and two procedure-related risk factors (duration of surgery ≥401min and blood
190
transfusion ≥241ml) were identified as the best predictors of PPC after multivariate analysis. These cut-off
191
values for variables in multivariate analysis were calculated based on ROC curves to achieve objectivity
192
and consistency. Older age, prolonged duration of surgery, and blood transfusion have been identified as
193
risk factors of PPC previously and this study is consistent with existing literature[2].
194
Interestingly, %VC, one of the variables detected by preoperative PFTs, was identified as a
195
significant independent risk factor in this study. Previously, patients with COPD or an obstructive pattern 12
13 196
with a lower FVC and a lower FEV1 were considered at high risk of developing PPC even among patients
197
undergoing non-cardiothoracic surgery[2, 23-26]. The finding that %VC is a significant risk factor for the
198
development of PPC is inconsistent with the ACP clinical guidelines, partially because there were no studies
199
available at the time of their publication that stratified the risk of patients with restrictive pulmonary
200
disease[2]. However, it is consistent with two large retrospective studies recently conducted in Japan,
201
including one study with 1053 patients who underwent radical gastrectomy for gastric cancer[9] and another
202
with 1236 patients who underwent colorectal cancer surgery[10]. These studies similarly found a
203
lower %VC (<80%) to be an independent risk factor for the development of PPC. Another retrospective
204
study conducted in Mexico with 602 patients undergoing bariatric surgery (97% of patients with
205
laparoscopic Roux-en-Y gastric bypass surgery) also found that PPC occurred more frequently among
206
patients with a restrictive pattern than the normal group or the obstructive group[11]. The present study and
207
these three studies may have been able to detect a lower %VC as an important predictor of PPC because
208
these studies commonly had all eligible patients undergo preoperative PFT with similar study populations
209
undergoing major abdominal surgery. Another prospective study with 1055 patients with the same explicit
210
definition of PPC, but with a heterogeneous patient population (including orthopedic surgery, neurosurgical
211
procedures, and other non-thoracic procedures such as urology, plastic surgery, ophthalmologic procedures)
212
and selective use of preoperative PFT, did not find PFT to be associated with an increased risk of PPC[8].
213
It is interesting to note that other patient-related risk factors such as chronic lung disease (COPD,
214
asthma), congestive heart failure, ASA class, functional status, smoking history, serum albumin level, 13
14 215
abnormal physician examination, which were deemed important risk factors in previous reports[2, 7, 8],
216
were not identified as independent risk factors in this study. Although age was the only information obtained
217
as a part of the medical history which was found to be an independent risk factor after multivariate analysis,
218
the odds ratio for age (OR2.97) was lower than for %VC (OR 4.53) in this study. Thus, we conclude that
219
history and physical examination may be predictive of but are not superior to preoperative PFT when
220
comparing the odds ratio of each variable identified in the present study.
221
The question remains whether PFT would significantly improve the ability to predict the
222
development of PPC when added to other significant predictors. The present study shows that %VC is one
223
of the four best predictors of developing PPC in patients undergoing major abdominal surgery. However, it
224
did not significantly increase the AUC with ROC curve when %VC was added to a model (Model 2)
225
containing the three other predictors (age, duration of surgery, and blood transfusion). Even though Model 1,
226
with all four variables, did have a higher sensitivity and negative predictive value, it also had a lower
227
specificity, diagnostic accuracy, and positive likelihood ratio compared to Model 2. Taken together, these
228
results indicate that the model containing three predictors (age, duration of surgery, and blood transfusion)
229
without %VC has a similar and non-inferior ability to predict developing PPC compared to a model
230
containing all four of the predictors identified in this study. These results support the omission of
231
preoperative PFT before abdominal surgery under general anesthesia, as it does not provide a significant
232
improvement in the predictive ability of PPC when three other predictors (age, duration of surgery, and
233
blood transfusion) are available. 14
15 234
There are several acknowledged limitations to this study. The study design is a single institution
235
study with a selected patient population. Although the study was prospectively conducted and a relatively
236
large sample size with over 600 patients, the study population is limited to patients undergoing elective
237
abdominal surgery under general anesthesia at a single institution in Japan. The results still need external
238
validation, preferably by a multicenter study, to confirm the findings and generalizability to a larger
239
population. In addition, the definition of PPC was limited to pneumonia, pleural effusion, respiratory failure,
240
and atelectasis. This study did not detect other PPC such as bronchospasm or hypoxia requiring oxygen
241
therapy (but not requiring mechanical ventilation) which are deemed important by some investigators[13].
242
Although the definition of pneumonia was based on the well-accepted definition from the US Centers for
243
Disease Control, the decision to make a clinical intervention for pleural effusion, respiratory failure, and
244
atelectasis was left to the discretion of the attending physician. Even though these definitions were based on
245
a previous study with a large prospective cohort population by McAlister et al[8], there is a subjective
246
component that could lead to variability of results when applied to different study populations.
247
In conclusion, this prospective study with 676 patients undergoing elective abdominal surgery
248
under general anesthesia found age, %VC, duration of surgery, and blood transfusion to be the best
249
predictors for developing PPC. Other than age, history and physical examination were not useful to predict
250
PPC. Age, duration of surgery, and blood transfusion with and without %VC had a similar predictive value
251
of PPC based on AUC with ROC curve, suggesting that preoperative PFT does not significantly improve
252
the ability to predict the development of PPC. These results support discontinuing the practice of routine 15
16 253
preoperative PFT without compromising the ability to predict the occurrence of PPC.
254
Figure Legend
255 256
Figure. Study patient enrollment.
257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 16
17 290 291 292 293
Acknowledgments: We gratefully acknowledge the contributions of Ms.Yasuko Saikai for providing a great
294
deal of time and effort for the organization and management of data for this project. We acknowledge
295
Hisanaga Horie, MD, Ph.D., Yoshinori Hosoya, MD, Ph.D., and Yasunaru Sakuma MD, Ph.D. for providing
296
constructive suggestions and valuable guidance in the conduct of this study. We also acknowledge the
297
contribution of surgery residents at Department of Surgery, *** Medical University in retrieving patients'
298
information for this project.
299 300
Funding source: This research did not receive any specific grant from funding agencies in the public,
301
commercial, or not-for-profit sectors.
302 303
Provenance and peer review
304
Not commissioned, externally peer-reviewed
305 306 307
17
18 308
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337 338
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335 336
Inokuchi, M., et al., Risk factors for post-operative pulmonary complications after gastrectomy for gastric
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333 334
McAlister, F.A., et al., Incidence of and risk factors for pulmonary complications after nonthoracic surgery. Am J Respir Crit Care Med, 2005. 171(5): p. 514-7. 171
331 332
McAlister, F.A., et al., Accuracy of the preoperative assessment in predicting pulmonary risk after
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347 348
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liver disease score is superior to Child-Turcotte-Pugh classification in predicting outcome. Arch Surg,
350
2005. 140(7): p. 650-4; discussion 655. 140
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354 355
Kanda, Y., Investigation of the freely available easy-to-use software 'EZR' for medical statistics. Bone
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Fernandez-Bustamante, A., et al., Postoperative Pulmonary Complications, Early Mortality, and Hospital
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357
Investigators. JAMA Surg, 2017. 152(2): p. 157-166. 152
358
[22]
359 360
Med, 2015. 175(8): p. 1410-2. 175 [23]
361 362
[24]
367
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363 364
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368
[27] Agha RA, Borrelli MR, Vella-Baldacchino M, Thavayogan R and Orgill DP, for the STROCSS
369
STROCSS Statement: Strengthening the Reporting of Cohort Studies in Surgery.
370
of Surgery 2017;46:198-202.
371 372 373
19
Group.
The
International Journal
Table 1. Postoperative pulmonary complications Complication
Number
%
Pneumonia
9
31
Effusion
8
28
Respiratory failure
7
24
Atelectasis
5
17
Total
29
100
Table 2. Associations of Patient-related factors with PPC Patient-related factors
Overall
No PPC
PPC
Incidence (%)
p-value
Age, median (IQR)
62 (17)
62 (18)
75 (17)
-
6.E-05
≦49
116 (17.2%)
113
3
2.6
50-59
152 (22.5%)
150
2
1.3
60-69
211 (31.2%)
206
5
2.4
70-79
149 (22.0%)
138
11
7.4
≧80
48 (7.1%)
40
8
16.7
Male, (%)
406 （60.1）
386
20
4.9
Female, (%)
270 （39.9）
261
9
3.4
656 （97.0%）
629
27
4.1
Previously Diagnosed
20 （3.0%）
18
2
10.0
No
657 (97.1%)
628
29
4.4
19 (2.9%)
19
0
0.0
665（98.4%）
637
28
4.2
11（1.6%）
10
1
9.1
1
187 (27.7%)
185
2
1.1
2
403 (59.6%)
382
21
5.2
3
86 (12.7%)
80
6
7.0
4
0 (0%)
0
0
-
Gender 0.34
Chronic Obstructive Pulmonary Disease No
0.21
Asthma Previously Diagnosed
1
Congestive Heart Failure No Previously Diagnosed
0.39
American Society of Anesthesiologists Class, (%)
0.015
Functional Status Independent
643 (95.1%)
617
26
4.0
33 (4.9%)
30
3
9.1
Never
291 (43.0%)
279
12
4.1
Former smoker
326 (48.2%)
310
16
4.9
Current Smoker
59 (8.7%)
58
1
1.7
Brinkman Index, median (IQR)
120 (700)
500 (1000)
-
0.21
Body Mass Index, kg/m2, median (IQR)
22.9(4.9)
22.8(4.3)
-
0.83
Serum albumin level, g/dl, median (IQR)
4.1(0.6)
3.8 (0.5)
-
0.002
Partially/totally dependent
0.16
Smoking History
≦1.9
2 （0.3%）
2
0
0.0
2.0-2.9
22 （3.3%）
21
1
4.5
3.0-3.9
226 （33.4%）
209
17
7.5
≧4.0
426 （63.0%）
415
11
2.6
651 (96.3%)
624
27
4.1
25 (3.7%)
23
2
8.0
0.6
Physical Examination Normal Abnormal
Abbreviations: IQR, interquartile range; PPC, postoperative pulmonary complications.
0.29
Table 3. Association of preoperative PFT data with PPC Preoperative PFT Data
Overall
No PPC (N=647)
PPC (N=29)
p-value
VC, L, median (IQR)
3.5 (1.3)
3.5 (1.3)
2.77 (1.6)
0.004
% VC, median (IQR)
116.1(23.1)
116.6 (22.3)
102.2 (33.3)
5.32E-05
FVC, L, median (IQR)
3.5 (1.3)
3.5 (1.3)
2.77 (1.5)
0.003
FEV1, L, median (IQR)
2.6 (1.0)
2.6 (1.0)
2.2 (1.4)
0.003
% FEV1, median (IQR)
111.0 (25.8)
111.5 (25.6)
107.6 (23.3)
0.16
FEV1/FVC, median (IQR)
76.0 (11.1)
76.1 (11.2)
73.1 (9.9)
0.13
% FEV1/FVC, median (IQR)
103.7 (14.7)
103.7 (14.5)
111.4 (18.0)
0.64
Abbreviations:
FEV1, forced expiratory volume in 1 second; % FEV1, percent predicted FEV1;
FVC, forced vital capacity; IQR, interquartile range; PFT, pulmonary function testing; PPC, postoperative pulmonary complications; VC, vital capacity; %VC, percent predicted VC.
Table 4. Association of Intraoperative variables with PPC Overall
No PPC (N=647)
PPC (N=29)
p-value
Duration of Surgery, min, median (IQR)
246 (147)
244 (144.5)
305 (221)
0.0007
Duration of General Anesthesia, min, median (IQR)
309 (158)
307 (156.5)
386 (253)
0.0004
130 (481.3)
130 (457.5)
870 (1850)
0.0004
350 (471)
345 (465)
485 (550)
0.155
0 (0)
0 (0)
0 (560)
3.E-11
3200 (2000)
3150 (1925)
4360 (3950)
0.004
Laparoscopic (%)
259 （38.3）
253
6
Open Lower (%)
125 （18.5）
123
2
Open Upper (%)
292 （43.2）
271
21
Intraoperative variables
Bleeding volume, mL, median (IQR) Urine output volume, mL, median (IQR) Blood transfusion volume, mL, median (IQR) Crystalloid replacement volume, mL, median (IQR) Incision site/ type of surgery
Abbreviations: IQR, interquartile range; PPC, postoperative pulmonary complications.
0.006
Table 5. Variables associated with PPC after multivariable analysis Variables
OR
Age, ≥ 70 y
2.97 0.96 1.24 1.12
American Society of Anesthesiologists Class, ≥3 Serum albumin, ≤ 4 g/dL FEV1, ≤ 2.4 L % VC, ≤ 104.5 % Duration of surgery, ≥ 401 min Blood transfusion, ≥ 241 mL Incision site/ type of surgery, Open upper incision
4.53 3.27 4.55 1.58
95% CI 1.14
7.76
0.34 0.47 0.41 1.82 1.25 1.74
2.74 3.24 3.05 11.20 8.55 11.90
0.60
4.16
p-value 0.026 0.95 0.66 0.83 0.001 0.015 0.002 0.35
Abbreviations: FEV1, forced expiratory volume in 1 second; IQR, interquartile range; OR, odds ratio; PPC, postoperative pulmonary complications; %VC, percent predicted vital capacity.
Table 6. Comparison of 10 multivariable models to predict PPC p-value Model No.
# of
Variablesa
AUC
vs
Sensitivity %
Specificity % PPV
Diagnostic
Positive
Negative
Accuracy
LR
LR
NPV
variables Model 1 Age + %VC + Duration of Surgery +
1
4
0.89
-
100.0
52.2
8.6
100.0
54.3
2.1
0.0
0.83
0.11
89.7
63.2
9.8
99.3
64.3
2.4
0.2
Blood Transfusion Age + Duration of Surgery + Blood 2 transfusion 3 3
Age + %VC + Duration of Surgery
0.86
0.19
96.6
54.6
8.7
99.7
56.4
2.1
0.1
4
Age + %VC + Blood Transfusion
0.88
0.28
100.0
56.6
9.4
100.0
58.4
2.3
0.0
5
Age + %VC
0.77
0.02
82.8
60.0
8.5
98.7
60.9
2.1
0.3
0.72
6.9.E-06
55.2
86.4
15.4
97.7
85.1
4.1
0.5
Age
0.69
2.5.E-04
65.5
72.5
9.6
97.9
72.2
2.4
0.5
%VC
0.70
4.3.E-05
62.1
79.1
11.8
79.1
78.4
3.0
0.5
9
Duration of Surgery
0.66
8.0.E-09
41.4
90.9
16.9
97.2
88.8
4.5
0.6
10
Blood Transfusion
0.67
5.2.E-08
41.4
92.7
20.3
97.2
90.5
5.7
0.6
2
Duration of Surgery + Blood
6 Transfusion 7 8 1
Abbreviations:
AUC, area under the curve; LR, likelihood ratio; PPC, postoperative pulmonary complications; PPV, positive predictive values; NPV, negative
predictive values; %VC, percent predicted vital capacity. a
Age ≥ 70 years, %VC<104.5, duration of surgery≥401 min, blood transfusion ≥ 241 ml
Supplementary Table 1. Correlation coefficient among significant variables following univariate analysis ASA Variables
Age
VC Class
Duration
Duration of
of
General
Surgery
Anesthesia
Serum %VC
FVC
albumin
FEV1
Blood
Blood
Crystalloid
Incision
loss
transfusion
volume
site
0.29
-0.29
-0.40
-0.11
-0.40
-0.56
-0.01
-0.01
0.02
0.05
-0.05
0.12
ASA Class
-
-0.24
-0.20
-0.25
-0.18
-0.27
0.02
0.03
0.03
0.06
-0.02
0.06
Serum albumin
-
-
0.19
0.11
0.19
0.21
-0.05
-0.04
-0.09
-0.08
-0.03
-0.05
VC
-
-
-
0.62
0.99
0.88
0.09
0.08
0.08
0.00
0.12
-0.06
%VC
-
-
-
-
0.62
0.50
0.00
-0.01
-0.02
-0.02
0.03
0.20
FVC
-
-
-
-
-
0.89
0.09
0.08
0.07
-0.01
0.13
0.12
FEV1
-
-
-
-
-
-
0.06
0.06
0.07
-0.02
0.09
-0.10
Duration of Surgery
-
-
-
-
-
-
-
0.99
0.56
0.35
0.77
0.18
Duration of General Anesthesia
-
-
-
-
-
-
-
-
0.55
0.36
0.77
0.14
Blood loss
-
-
-
-
-
-
-
-
-
0.83
0.58
0.52
Blood transfusion
-
-
-
-
-
-
-
-
-
-
0.36
0.18
Crystalloid volume
-
-
-
-
-
-
-
-
-
-
-
0.19
Abbreviations: predicted VC.
ASA, American Society of Anesthesiologists; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; VC, vital capacity; %VC, percent
Highlights Predicting postoperative pulmonary complications is clinically important. Spirometry is widely used but unproven to predict pulmonary complications. This study evaluated clinical risk factors for developing pulmonary complications. Age, duration of surgery, transfusion together predict pulmonary complications. Addition of spirometry did not improve the predictive ability. Spirometry may be omitted from preoperative pulmonary evaluation.
Data Statement
The data that support the findings of this study are available on request. The data are not publicly available due to information that could compromise the privacy of research participant.
Credit Author Statement
Author contribution: SY, TK, YY, NS, and AKL conceived of and designed the study. SY and MK performed data extraction. SY, TK, and MM performed the data analysis and interpreted the results. SY and AKL wrote the manuscript. SY, MK, TK, MM, AKL, YY, and NS revised the manuscript.
Guarantor: Shinichiro Yokota and Alan Kawarai Lefor
S1743-9191(19)30355-3
DOI:
https://doi.org/10.1016/j.ijsu.2019.11.032
Reference:
IJSU 5167
To appear in:
International Journal of Surgery
Received Date: 22 July 2019 Revised Date:
23 October 2019
Accepted Date: 25 November 2019
Please cite this article as: Yokota S, Koizumi M, Togashi K, Morimoto M, Yasuda Y, Sata N, Lefor AK, Preoperative pulmonary function tests do not predict the development of pulmonary complications after elective major abdominal surgery: A prospective cohort study, International Journal of Surgery, https:// doi.org/10.1016/j.ijsu.2019.11.032. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. 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. © 2019 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.
Original article
PREOPERATIVE PULMONARY FUNCTION TESTS DO NOT PREDICT THE DEVELOPMENT OF PULMONARY COMPLICATIONS AFTER ELECTIVE MAJOR ABDOMINAL SURGERY: A PROSPECTIVE COHORT STUDY
Shinichiro Yokota1,2, Masaru Koizumi1, Kazutomo Togashi1, 3, Mitsuaki Morimoto1, Yoshikazu Yasuda1, Naohiro Sata1, Alan Kawarai Lefor1
1Department of Surgery, Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, 329-0498, Japan 2Department of Surgery, Allegheny General Hospital, 320 East North Avenue, Pittsburgh, PA, USA 15212 3Department of Coloproctology, Aizu Medical Center Fukushima Medical University, 21 Kawahigashi, Aizuwakamatsu, 969-3492, Japan
Corresponding author: Shinichiro Yokota, MD, PhD Department of Surgery, Jichi Medical University 3311-1 Yakushiji, Shimotsuke,329-0498, Japan Tel. +81 285 58 7371, Fax. +81 285 44 3234, Email: [email protected]
Conflicts of interest: The authors have no conflict of interest to declare. 1
International Journal of Surgery Author Disclosure Form The following additional information is required for submission. Please note that failure to respond to these questions/statements will mean your submission will be returned. If you have nothing to declare in any of these categories, then this should be stated. Please state any conflicts of interest The authors have no conflict of interest to declare.
Please state any sources of funding for your research No funding for this current work
Please state whether Ethical Approval was given, by whom and the relevant Judgement’s reference number This study was approved by the Ethics Committee at Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, 329-0498, Japan
Research Registration Unique Identifying Number (UIN) Please enter the name of the registry, the hyperlink to the registration and the unique identifying number of the study. You can register your research at http://www.researchregistry.com to obtain your UIN if you have not already registered your study. This is mandatory for human studies only.
1. Name of the registry: the University Hospital Medical Information Network (UMIN) in Japan 2. Unique Identifying number or registration ID: UMIN ID: UMIN000002753. 3. Hyperlink to the registration (must be publicly accessible): https://upload.umin.ac.jp/cgi-openbin/ctr/ctr_his_list.cgi?recptno=R000003321
1
Author contribution Please specify the contribution of each author to the paper, e.g. study design, data collections, data analysis, writing. Others, who have contributed in other ways should be listed as contributors. SY, TK, YY, NS and AKL conceived of and designed the study. SY and MK performed data extraction. SY, TK, and MM performed the data analysis and interpreted the results. SY and AKL wrote the manuscript. SY, MK, TK, MM, AKL, YY, and NS revised the manuscript.
Guarantor The Guarantor is the one or more people who accept full responsibility for the work and/or the conduct of the study, had access to the data, and controlled the decision to publish. Please note that providing a guarantor is compulsory. Shinichiro Yokota and Alan Kawarai Lefor
2
2 1
Abstract (200 words)
2
Background: Data describing the association of preoperative pulmonary function testing (PFT) with
3
postoperative pulmonary complications (PPC) are inconsistent. We conducted this prospective study to
4
determine the ability of PFT to predict PPC.
5
Materials and Methods: Data were prospectively collected from 676 patients who underwent elective
6
abdominal surgery (emergency and thoracic operations excluded). The primary outcome was the occurrence
7
of PPC within 30 days. Patient and procedure-related factors were examined as risk factors. Multivariate
8
logistic regression analysis was performed using risk factors identified with univariate analysis and area
9
under the curve (AUC) analysis performed.
10
Results: PPC occurred in 29 patients (4.9%). History of smoking or abnormal physical examination were
11
not significantly associated. Multivariate analysis identified age (p=0.03), operative time (p=0.02), blood
12
transfusions (p=0.002), and %VC (p=0.001) as significant risk factors. AUC with a model including age,
13
operative time, and blood transfusion was 0.83. The addition of %VC to these three variables increased the
14
AUC to 0.89 (p=0.1).
15
Conclusions: Age, operative time, blood transfusion, and %VC are significantly associated with an
16
increased risk of PPC. The addition of %VC to other risk factors did not significantly improve the ability to
17
predict PPC, showing that preoperative PFT is not helpful to predict PPC.
18 19
2
3 20
Keywords:
21
Complications; Pulmonary Function Test; Preoperative Care.
Elective
Surgical
Procedures;
Abdominal
22 23
3
Surgery;
Postoperative
Pulmonary
4 24
1. Introduction
25
Abdominal surgery is associated with relatively high rates of postoperative pulmonary
26
complications (PPC)[1]. PPC are as common as cardiovascular complications and similarly contribute to
27
morbidity, mortality, and hospital length of stay[2, 3]. Preoperative evaluation of risk factors associated with
28
developing PPC is as important as preoperative cardiac evaluation.
29
While preoperative pulmonary function testing (PFT) before thoracic surgery is well accepted, data
30
regarding its necessity before non-thoracic surgery is inconsistent [4]. In 2006, the American College of
31
Physicians (ACP) published the first clinical guidelines for preoperative risk assessment to prevent PPC for
32
patients undergoing non-cardiothoracic surgery[5]. This document emphasizes clinical evaluation to identify
33
patient- and procedure-related risk factors. The guideline recommends against routine PFT prior to surgery
34
because a systematic review of the literature did not show PFT to be superior to history and physical
35
examination in predicting which patients will develop PPC[2, 5, 6]. However several subsequent studies
36
have shown an association between the preoperative PFT and development of PPC among patients
37
undergoing abdominal surgery [7-12].
38
A lack of consensus regarding the predictive value of preoperative PFT may cause confusion on a
39
practical level and lead to the continued use of routine PFT before abdominal surgery under general
40
anesthesia despite the recommendation in the ACP guidelines[13]. In fact, preoperative PFT is performed
41
routinely in Japan for preoperative pulmonary evaluation of all patients before elective abdominal surgery
42
under general anesthesia[9, 10, 14]. In addition, there are only a few studies in the literature that directly 4
5 43
compared predictive values of clinical risk factors and PFT in patients undergoing elective abdominal
44
surgery [15]. Thus, it is still not clear whether clinical evaluation alone, such as history and physical
45
examination, can sufficiently and accurately predict the risk of PPC following various types of abdominal
46
surgery under general anesthesia. The existing literature is not clear whether PFT contribute to the ability to
47
predict the development of PPC.
48
The aim of this prospective study is to evaluate whether the history and physical examination are
49
equally or more predictive of clinically significant PPC than PFT among patients undergoing elective
50
abdominal surgery under general anesthesia at a tertiary referral center in Japan.
51 52
2. Material and methods
53
2.1. Selection of study subjects
54
We conducted this prospective study from November 2009 to March 2011 at an 1130-bed teaching
55
hospital and a tertiary referral center. Patients scheduled to undergo elective abdominal surgery under
56
general anesthesia during the study period were registered as study subjects. Patients were included in the
57
study if the surgery involved the manipulation of an abdominal organ. We excluded patients who were
58
undergoing elective surgery for inguinal hernia and ventral hernia[16]. We also excluded patients who
59
underwent intrathoracic surgery such as esophagectomy or emergency operations. This study was approved
60
by the Ethics Committee. The study was registered at the University Hospital Medical Information Network
61
(UMIN) at www.umin.ac.jp (UMIN ID: UMIN000002753. ) 5
6 62
The work has been reported in line with the STROCSS criteria [27].
63
We developed a standardized preoperative 10-point checklist. To complete the checklist, residents
64
conducted a standardized history and physical examination for each patient during a preoperative visit
65
usually within one week prior to surgery. This 10 point checklist included potential patient-related risk
66
factors described in the ACP guidelines[2]: 1) age, 2) previously diagnosed chronic obstructive pulmonary
67
disease (COPD), 3) previously diagnosed asthma, 4) previously diagnosed chronic heart failure, 5) the
68
American Society of Anesthesiologists (ASA) classification, 6) Functional Dependency, 7) Smoking History,
69
8) Body Mass Index (BMI), 9) preoperative albumin level, and 10) physical examination. We used the ASA
70
classification as recorded in the anesthesiology record. Functional dependency was the need for equipment
71
such as a cane or others in activities of daily living[2]. Functional dependency was classified into categories
72
(e.g. none, partial, and total). Smoking history was classified into three categories (e,g. never smoked, recent
73
smoker (stopped over 4 weeks prior to operation), and current smoker (within 4 weeks of operation)). BMI
74
and preoperative serum albumin level data were available for all patients. Physical examination was
75
classified as normal or abnormal after performing three specific maneuvers: cough test, wheeze test, and
76
forced expiratory time as described in detail by McAlister et al[8]. We routinely perform preoperative PFT
77
for patients undergoing abdominal surgery under general anesthesia at our hospital and PFT data were
78
available for all patients. We collected intraoperative data such as operative time, duration of anesthesia,
79
incision site (upper or lower abdominal)/type of surgery (open or laparoscopic), crystalloid replacement
80
volume, urine output, blood transfusion volume, and estimated blood loss from the operative record for all 6
7 81
patients. Patients were divided into 3 groups based on the location of the incision and the type of surgery:
82
open surgery with an upper abdominal incision (i.e. above the umbilicus), open surgery with lower
83
abdominal incision (i.e. below the umbilicus), and laparoscopic surgery.
84
The primary outcome was the occurrence of PPC within 30 days following surgery. We adopted explicit
85
definitions for clinically significant PPC described by McAlister et al. [8] including: (1) respiratory failure
86
requiring mechanical ventilation, (2) pneumonia (defined using the Centers for Disease Control and
87
Prevention definition for postoperative pneumonia), (3) atelectasis requiring bronchoscopy, or (4)
88
pneumothorax or pleural effusion requiring percutaneous intervention. The decision to use interventions
89
such as mechanical ventilation, bronchoscopy, or others was left to the discretion of the attending
90
physician[8]. We collected data on the occurrence of PPC through a review of the medical chart, laboratory,
91
and radiology data. Only the first PPC occurring in any one patient was analyzed.
92 93 94
2.2 Statistical Analysis Data were described non-parametrically, analyzed using two-sided statistics, and considered
95
significant with p< 0.05. Univariate analysis of data was performed using the chi-square and Fisher`s exact
96
tests for categorical data, and the Mann-Whitney U tests for continuous data. Variables considered
97
significant (p<0.05) in univariate analyses were then confirmed by the coefficient of association for strong
98
linear correlation[9]. Variables with a correlation coefficient of >0.7 were considered to have a strong linear
99
correlation and excluded from multivariate logistic regression analyses. Variables included in multivariate 7
8 100
logistic regression analyses were dichotomized based on cut-off points calculated using a receiver operator
101
characteristics (ROC) curve. To compare the predictive ability of multivariate models, ROC curves were
102
tested for statistically significant differences[17]. In addition, sensitivity, specificity, positive predictive
103
value, negative predictive value, diagnostic accuracy, positive likelihood ratio, and negative likelihood ratio
104
were calculated for models developed using independent risk factors identified with multivariate
105
analysis[18]. Statistical analyses were performed using EZR (Easy R)[19].
106 107 108
3. Results A total of 983 patients were eligible for the study (Figure). Of these, 307 (31%) patients were
109
excluded for the following reasons: 49 (5.0%) because surgery was delayed or canceled; 244 (24%) due to
110
incomplete preoperative checklist or missing data; eight (0.8%) due to the addition of intrathoracic incision
111
during operation; six (0.6%) patients lost to follow up. Finally, 676 (69%) patients were enrolled in the study.
112
The majority of patients underwent abdominal surgery: 243 patients (36.0%) had colon and rectum surgery,
113
208 (30.8%) had gastric surgery, 149 (22.0%) had hepatobiliary / pancreas surgery, and 76 (11%) had other
114
abdominal surgery, of organs such as the spleen, adrenal gland, and kidney. Laparoscopic surgery was
115
performed in 259 patients (38.3%).
116
A total of 29 PPC occurring in 676 patients (Incidence of PPC: 4.3%) were recorded including nine
117
patients with pneumonia, eight with pleural effusions, seven with respiratory failure, and five with
118
atelectasis (Table 1). Length of stay was significantly longer for patients with PPC compared to patients
119
without PPC, median 22 days (interquartile range (IQR) 7) versus 12 days (IQR 13) (p=5.51E-08). 8
9 120
Among the patient-related factors (Table 2), age (p=6.E-05), ASA classification (p=0.015), and
121
serum albumin level (p=0.002) were considered potential risk factors following univariate analyses. Gender,
122
past medical history of cardiopulmonary diseases (COPD, asthma, or congestive heart failure), functional
123
status, smoking history, BMI, and abnormal physical examination were not statistically significant variables.
124
Preoperative PFT parameters (Table 3) with p<0.05 in univariate analyses included vital capacity
125
(VC) (p=0.004), percent predicted VC (%VC) (p=5.32E-05), forced vital capacity (FVC) (p=0.003), and
126
forced expiratory volume in 1 second (FEV1) (p=0.003).
127
Overall, the median duration of surgery was 246 min (IQR 147) (Table 4). Comparison of
128
intraoperative variables between patients with PPC and without PPC showed duration of surgery (p=0.0007),
129
duration of general anesthesia (p=0.0004), bleeding volume (p=0.0004), blood transfusion volume
130
(p=3E-11), crystalloid replacement volume (p=0.004), and incision site (p=0.006) to be possible risk factors
131
for the development of PPC with p<0.05.
132
Examination of correlation coefficients among significant variables following univariate analysis
133
revealed five variables with strong linear correlations (correlation coefficient > 0.7) (Supplementary Table 1).
134
These variables (VC, FVC, duration of general anesthesia, bleeding volume, crystalloid volume) were
135
excluded. The eight remaining variables included in the multivariable logistic regression analyses included
136
1) age, 2) ASA classification, 3) serum albumin, 4) FEV1, 5) %VC, 6) duration of surgery, 7) blood
137
transfusion, and 8) incision site/ type of surgery. Among these variables, age (OR 2.97 for age≥70 years,
138
p=0.026), %VC (OR 4.53 for %VC<104.5, p=0.001), duration of surgery (OR 3.27 for duration of 9
10 139
surgery≥401min, p=0.015), blood transfusion (OR 4.55 for blood transfusion≥241ml p=0.002) were
140
identified as the best independent predictors of PPC (Table 5).
141
ROC curves were constructed for 10 models with different numbers of variables and the AUC for each
142
model was calculated (Table 6). Model 1 with all four variables had the highest AUC with 0.89. However,
143
Model 2 with three variables (Age, duration of surgery, and blood transfusion, but without %VC) yielded a
144
similar, non-inferior AUC of 0.83 without a statistically significant difference (p=0.108). % VC Models 3
145
and 4, both containing three variables also resulted in similar AUC (0.86, 0.88, respectively). Model 5 with
146
preoperative variables alone (age and %VC) or Model 6 with intraoperative variables alone (duration of
147
surgery and blood transfusion) had significantly lower AUC (0.77, 0.72, respectively) when compared to
148
Model 1. Models 7-10 with single predictive variables also had significantly lower AUC.
149
When a cut-off value of %VC<80 (commonly used to define a restrictive pattern) was used for
150
multivariate analysis, the same four independent variables (age≥70 years, %VC<80, duration of
151
surgery≥401min, and blood transfusion≥241ml) were identified as significant (data not shown).
152
Comparison of the AUC between Model 1 and Model 2 with a cut off value %VC<80 showed a similar
153
result (0.87, 0.83, respectively with p=0.21) as Table 6.
154 155 156 157
10
11 158 159
4. Discussion
160
PPC are equally prevalent as cardiac complications and similarly influence postoperative morbidity,
161
mortality, and length of stay[2, 4, 13]. In 2006, the American College of Physicians (ACP) published a
162
clinical guideline for preoperative pulmonary risk stratification for patients undergoing non-cardiothoracic
163
surgery, which recommended against “routine” use of PFT preoperatively as the data are mixed regarding its
164
predictive value in the existing body of literature[2]. Although many studies have analyzed risk factors to
165
predict the development of PPC in the last 20 years[7-10, 12, 13, 20, 21], results varied considerably across
166
studies partly because of differences in study populations, outcomes definitions, and study designs[13]. Thus,
167
there is still inconsistency in the data regarding the predictive value of PFT before elective major abdominal
168
surgery under general anesthesia[9, 10, 12, 20]. There is a major difference in the use of preoperative PFT in
169
Japan compared to many western countries. Reports indicate that preoperative PFT are performed
170
routinely[10] or before over 70% of low-risk operations under general anesthesia in Japan[14], while a
171
similar report from Canada indicated that preoperative PFT was performed in less than 8% of patients[22].
172
This striking contrast in the use of PFT demonstrates the lack of a global consensus for preoperatively
173
predicting the risk of developing PPC.
174
In this study, we conducted a single institution, prospective cohort study in Japan, including 676
175
patients who underwent major abdominal surgery under general anesthesia, to determine the incidence and
176
best predictors of PPC in this population. We also compared PFT data with clinical data, which were
11
12 177
obtained through a standardized history and physical examination, as few studies have made such direct
178
comparisons in the past[2]. In doing so, we aimed to answer the question of whether or not the practice of
179
routine preoperative PFT should be continued for patients undergoing major abdominal surgery under
180
general anesthesia. The strengths of this present study are its prospective study design, clear inclusion and
181
exclusion criterion, a well-defined study population, and explicit definitions of clinically significant PPC
182
which required interventions based on a prior study[8]. Every patient in this study group underwent
183
preoperative PFT as it is the standard of care.
184
This study found an incidence of PPC (4.3%) comparable to that in previous reports (2.7-8%),
185
including the study by McAlister, which used the same definition of PPC[2, 7-9]. PPC identified in this
186
study were indeed clinically significant considering the difference in the length of stay found between
187
patients with and without PPC. A total of 26 variables (18 patient-related risk factors and 8 procedure-related
188
risk factors) were examined as potential predictors of PPC. Two patient-related risk factors (age≥70
189
years, %VC<104.5) and two procedure-related risk factors (duration of surgery ≥401min and blood
190
transfusion ≥241ml) were identified as the best predictors of PPC after multivariate analysis. These cut-off
191
values for variables in multivariate analysis were calculated based on ROC curves to achieve objectivity
192
and consistency. Older age, prolonged duration of surgery, and blood transfusion have been identified as
193
risk factors of PPC previously and this study is consistent with existing literature[2].
194
Interestingly, %VC, one of the variables detected by preoperative PFTs, was identified as a
195
significant independent risk factor in this study. Previously, patients with COPD or an obstructive pattern 12
13 196
with a lower FVC and a lower FEV1 were considered at high risk of developing PPC even among patients
197
undergoing non-cardiothoracic surgery[2, 23-26]. The finding that %VC is a significant risk factor for the
198
development of PPC is inconsistent with the ACP clinical guidelines, partially because there were no studies
199
available at the time of their publication that stratified the risk of patients with restrictive pulmonary
200
disease[2]. However, it is consistent with two large retrospective studies recently conducted in Japan,
201
including one study with 1053 patients who underwent radical gastrectomy for gastric cancer[9] and another
202
with 1236 patients who underwent colorectal cancer surgery[10]. These studies similarly found a
203
lower %VC (<80%) to be an independent risk factor for the development of PPC. Another retrospective
204
study conducted in Mexico with 602 patients undergoing bariatric surgery (97% of patients with
205
laparoscopic Roux-en-Y gastric bypass surgery) also found that PPC occurred more frequently among
206
patients with a restrictive pattern than the normal group or the obstructive group[11]. The present study and
207
these three studies may have been able to detect a lower %VC as an important predictor of PPC because
208
these studies commonly had all eligible patients undergo preoperative PFT with similar study populations
209
undergoing major abdominal surgery. Another prospective study with 1055 patients with the same explicit
210
definition of PPC, but with a heterogeneous patient population (including orthopedic surgery, neurosurgical
211
procedures, and other non-thoracic procedures such as urology, plastic surgery, ophthalmologic procedures)
212
and selective use of preoperative PFT, did not find PFT to be associated with an increased risk of PPC[8].
213
It is interesting to note that other patient-related risk factors such as chronic lung disease (COPD,
214
asthma), congestive heart failure, ASA class, functional status, smoking history, serum albumin level, 13
14 215
abnormal physician examination, which were deemed important risk factors in previous reports[2, 7, 8],
216
were not identified as independent risk factors in this study. Although age was the only information obtained
217
as a part of the medical history which was found to be an independent risk factor after multivariate analysis,
218
the odds ratio for age (OR2.97) was lower than for %VC (OR 4.53) in this study. Thus, we conclude that
219
history and physical examination may be predictive of but are not superior to preoperative PFT when
220
comparing the odds ratio of each variable identified in the present study.
221
The question remains whether PFT would significantly improve the ability to predict the
222
development of PPC when added to other significant predictors. The present study shows that %VC is one
223
of the four best predictors of developing PPC in patients undergoing major abdominal surgery. However, it
224
did not significantly increase the AUC with ROC curve when %VC was added to a model (Model 2)
225
containing the three other predictors (age, duration of surgery, and blood transfusion). Even though Model 1,
226
with all four variables, did have a higher sensitivity and negative predictive value, it also had a lower
227
specificity, diagnostic accuracy, and positive likelihood ratio compared to Model 2. Taken together, these
228
results indicate that the model containing three predictors (age, duration of surgery, and blood transfusion)
229
without %VC has a similar and non-inferior ability to predict developing PPC compared to a model
230
containing all four of the predictors identified in this study. These results support the omission of
231
preoperative PFT before abdominal surgery under general anesthesia, as it does not provide a significant
232
improvement in the predictive ability of PPC when three other predictors (age, duration of surgery, and
233
blood transfusion) are available. 14
15 234
There are several acknowledged limitations to this study. The study design is a single institution
235
study with a selected patient population. Although the study was prospectively conducted and a relatively
236
large sample size with over 600 patients, the study population is limited to patients undergoing elective
237
abdominal surgery under general anesthesia at a single institution in Japan. The results still need external
238
validation, preferably by a multicenter study, to confirm the findings and generalizability to a larger
239
population. In addition, the definition of PPC was limited to pneumonia, pleural effusion, respiratory failure,
240
and atelectasis. This study did not detect other PPC such as bronchospasm or hypoxia requiring oxygen
241
therapy (but not requiring mechanical ventilation) which are deemed important by some investigators[13].
242
Although the definition of pneumonia was based on the well-accepted definition from the US Centers for
243
Disease Control, the decision to make a clinical intervention for pleural effusion, respiratory failure, and
244
atelectasis was left to the discretion of the attending physician. Even though these definitions were based on
245
a previous study with a large prospective cohort population by McAlister et al[8], there is a subjective
246
component that could lead to variability of results when applied to different study populations.
247
In conclusion, this prospective study with 676 patients undergoing elective abdominal surgery
248
under general anesthesia found age, %VC, duration of surgery, and blood transfusion to be the best
249
predictors for developing PPC. Other than age, history and physical examination were not useful to predict
250
PPC. Age, duration of surgery, and blood transfusion with and without %VC had a similar predictive value
251
of PPC based on AUC with ROC curve, suggesting that preoperative PFT does not significantly improve
252
the ability to predict the development of PPC. These results support discontinuing the practice of routine 15
16 253
preoperative PFT without compromising the ability to predict the occurrence of PPC.
254
Figure Legend
255 256
Figure. Study patient enrollment.
257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 16
17 290 291 292 293
Acknowledgments: We gratefully acknowledge the contributions of Ms.Yasuko Saikai for providing a great
294
deal of time and effort for the organization and management of data for this project. We acknowledge
295
Hisanaga Horie, MD, Ph.D., Yoshinori Hosoya, MD, Ph.D., and Yasunaru Sakuma MD, Ph.D. for providing
296
constructive suggestions and valuable guidance in the conduct of this study. We also acknowledge the
297
contribution of surgery residents at Department of Surgery, *** Medical University in retrieving patients'
298
information for this project.
299 300
Funding source: This research did not receive any specific grant from funding agencies in the public,
301
commercial, or not-for-profit sectors.
302 303
Provenance and peer review
304
Not commissioned, externally peer-reviewed
305 306 307
17
18 308
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309 310
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369
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370
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371 372 373
19
Group.
The
International Journal
Table 1. Postoperative pulmonary complications Complication
Number
%
Pneumonia
9
31
Effusion
8
28
Respiratory failure
7
24
Atelectasis
5
17
Total
29
100
Table 2. Associations of Patient-related factors with PPC Patient-related factors
Overall
No PPC
PPC
Incidence (%)
p-value
Age, median (IQR)
62 (17)
62 (18)
75 (17)
-
6.E-05
≦49
116 (17.2%)
113
3
2.6
50-59
152 (22.5%)
150
2
1.3
60-69
211 (31.2%)
206
5
2.4
70-79
149 (22.0%)
138
11
7.4
≧80
48 (7.1%)
40
8
16.7
Male, (%)
406 （60.1）
386
20
4.9
Female, (%)
270 （39.9）
261
9
3.4
656 （97.0%）
629
27
4.1
Previously Diagnosed
20 （3.0%）
18
2
10.0
No
657 (97.1%)
628
29
4.4
19 (2.9%)
19
0
0.0
665（98.4%）
637
28
4.2
11（1.6%）
10
1
9.1
1
187 (27.7%)
185
2
1.1
2
403 (59.6%)
382
21
5.2
3
86 (12.7%)
80
6
7.0
4
0 (0%)
0
0
-
Gender 0.34
Chronic Obstructive Pulmonary Disease No
0.21
Asthma Previously Diagnosed
1
Congestive Heart Failure No Previously Diagnosed
0.39
American Society of Anesthesiologists Class, (%)
0.015
Functional Status Independent
643 (95.1%)
617
26
4.0
33 (4.9%)
30
3
9.1
Never
291 (43.0%)
279
12
4.1
Former smoker
326 (48.2%)
310
16
4.9
Current Smoker
59 (8.7%)
58
1
1.7
Brinkman Index, median (IQR)
120 (700)
500 (1000)
-
0.21
Body Mass Index, kg/m2, median (IQR)
22.9(4.9)
22.8(4.3)
-
0.83
Serum albumin level, g/dl, median (IQR)
4.1(0.6)
3.8 (0.5)
-
0.002
Partially/totally dependent
0.16
Smoking History
≦1.9
2 （0.3%）
2
0
0.0
2.0-2.9
22 （3.3%）
21
1
4.5
3.0-3.9
226 （33.4%）
209
17
7.5
≧4.0
426 （63.0%）
415
11
2.6
651 (96.3%)
624
27
4.1
25 (3.7%)
23
2
8.0
0.6
Physical Examination Normal Abnormal
Abbreviations: IQR, interquartile range; PPC, postoperative pulmonary complications.
0.29
Table 3. Association of preoperative PFT data with PPC Preoperative PFT Data
Overall
No PPC (N=647)
PPC (N=29)
p-value
VC, L, median (IQR)
3.5 (1.3)
3.5 (1.3)
2.77 (1.6)
0.004
% VC, median (IQR)
116.1(23.1)
116.6 (22.3)
102.2 (33.3)
5.32E-05
FVC, L, median (IQR)
3.5 (1.3)
3.5 (1.3)
2.77 (1.5)
0.003
FEV1, L, median (IQR)
2.6 (1.0)
2.6 (1.0)
2.2 (1.4)
0.003
% FEV1, median (IQR)
111.0 (25.8)
111.5 (25.6)
107.6 (23.3)
0.16
FEV1/FVC, median (IQR)
76.0 (11.1)
76.1 (11.2)
73.1 (9.9)
0.13
% FEV1/FVC, median (IQR)
103.7 (14.7)
103.7 (14.5)
111.4 (18.0)
0.64
Abbreviations:
FEV1, forced expiratory volume in 1 second; % FEV1, percent predicted FEV1;
FVC, forced vital capacity; IQR, interquartile range; PFT, pulmonary function testing; PPC, postoperative pulmonary complications; VC, vital capacity; %VC, percent predicted VC.
Table 4. Association of Intraoperative variables with PPC Overall
No PPC (N=647)
PPC (N=29)
p-value
Duration of Surgery, min, median (IQR)
246 (147)
244 (144.5)
305 (221)
0.0007
Duration of General Anesthesia, min, median (IQR)
309 (158)
307 (156.5)
386 (253)
0.0004
130 (481.3)
130 (457.5)
870 (1850)
0.0004
350 (471)
345 (465)
485 (550)
0.155
0 (0)
0 (0)
0 (560)
3.E-11
3200 (2000)
3150 (1925)
4360 (3950)
0.004
Laparoscopic (%)
259 （38.3）
253
6
Open Lower (%)
125 （18.5）
123
2
Open Upper (%)
292 （43.2）
271
21
Intraoperative variables
Bleeding volume, mL, median (IQR) Urine output volume, mL, median (IQR) Blood transfusion volume, mL, median (IQR) Crystalloid replacement volume, mL, median (IQR) Incision site/ type of surgery
Abbreviations: IQR, interquartile range; PPC, postoperative pulmonary complications.
0.006
Table 5. Variables associated with PPC after multivariable analysis Variables
OR
Age, ≥ 70 y
2.97 0.96 1.24 1.12
American Society of Anesthesiologists Class, ≥3 Serum albumin, ≤ 4 g/dL FEV1, ≤ 2.4 L % VC, ≤ 104.5 % Duration of surgery, ≥ 401 min Blood transfusion, ≥ 241 mL Incision site/ type of surgery, Open upper incision
4.53 3.27 4.55 1.58
95% CI 1.14
7.76
0.34 0.47 0.41 1.82 1.25 1.74
2.74 3.24 3.05 11.20 8.55 11.90
0.60
4.16
p-value 0.026 0.95 0.66 0.83 0.001 0.015 0.002 0.35
Abbreviations: FEV1, forced expiratory volume in 1 second; IQR, interquartile range; OR, odds ratio; PPC, postoperative pulmonary complications; %VC, percent predicted vital capacity.
Table 6. Comparison of 10 multivariable models to predict PPC p-value Model No.
# of
Variablesa
AUC
vs
Sensitivity %
Specificity % PPV
Diagnostic
Positive
Negative
Accuracy
LR
LR
NPV
variables Model 1 Age + %VC + Duration of Surgery +
1
4
0.89
-
100.0
52.2
8.6
100.0
54.3
2.1
0.0
0.83
0.11
89.7
63.2
9.8
99.3
64.3
2.4
0.2
Blood Transfusion Age + Duration of Surgery + Blood 2 transfusion 3 3
Age + %VC + Duration of Surgery
0.86
0.19
96.6
54.6
8.7
99.7
56.4
2.1
0.1
4
Age + %VC + Blood Transfusion
0.88
0.28
100.0
56.6
9.4
100.0
58.4
2.3
0.0
5
Age + %VC
0.77
0.02
82.8
60.0
8.5
98.7
60.9
2.1
0.3
0.72
6.9.E-06
55.2
86.4
15.4
97.7
85.1
4.1
0.5
Age
0.69
2.5.E-04
65.5
72.5
9.6
97.9
72.2
2.4
0.5
%VC
0.70
4.3.E-05
62.1
79.1
11.8
79.1
78.4
3.0
0.5
9
Duration of Surgery
0.66
8.0.E-09
41.4
90.9
16.9
97.2
88.8
4.5
0.6
10
Blood Transfusion
0.67
5.2.E-08
41.4
92.7
20.3
97.2
90.5
5.7
0.6
2
Duration of Surgery + Blood
6 Transfusion 7 8 1
Abbreviations:
AUC, area under the curve; LR, likelihood ratio; PPC, postoperative pulmonary complications; PPV, positive predictive values; NPV, negative
predictive values; %VC, percent predicted vital capacity. a
Age ≥ 70 years, %VC<104.5, duration of surgery≥401 min, blood transfusion ≥ 241 ml
Supplementary Table 1. Correlation coefficient among significant variables following univariate analysis ASA Variables
Age
VC Class
Duration
Duration of
of
General
Surgery
Anesthesia
Serum %VC
FVC
albumin
FEV1
Blood
Blood
Crystalloid
Incision
loss
transfusion
volume
site
0.29
-0.29
-0.40
-0.11
-0.40
-0.56
-0.01
-0.01
0.02
0.05
-0.05
0.12
ASA Class
-
-0.24
-0.20
-0.25
-0.18
-0.27
0.02
0.03
0.03
0.06
-0.02
0.06
Serum albumin
-
-
0.19
0.11
0.19
0.21
-0.05
-0.04
-0.09
-0.08
-0.03
-0.05
VC
-
-
-
0.62
0.99
0.88
0.09
0.08
0.08
0.00
0.12
-0.06
%VC
-
-
-
-
0.62
0.50
0.00
-0.01
-0.02
-0.02
0.03
0.20
FVC
-
-
-
-
-
0.89
0.09
0.08
0.07
-0.01
0.13
0.12
FEV1
-
-
-
-
-
-
0.06
0.06
0.07
-0.02
0.09
-0.10
Duration of Surgery
-
-
-
-
-
-
-
0.99
0.56
0.35
0.77
0.18
Duration of General Anesthesia
-
-
-
-
-
-
-
-
0.55
0.36
0.77
0.14
Blood loss
-
-
-
-
-
-
-
-
-
0.83
0.58
0.52
Blood transfusion
-
-
-
-
-
-
-
-
-
-
0.36
0.18
Crystalloid volume
-
-
-
-
-
-
-
-
-
-
-
0.19
Abbreviations: predicted VC.
ASA, American Society of Anesthesiologists; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; VC, vital capacity; %VC, percent
Highlights Predicting postoperative pulmonary complications is clinically important. Spirometry is widely used but unproven to predict pulmonary complications. This study evaluated clinical risk factors for developing pulmonary complications. Age, duration of surgery, transfusion together predict pulmonary complications. Addition of spirometry did not improve the predictive ability. Spirometry may be omitted from preoperative pulmonary evaluation.
Data Statement
The data that support the findings of this study are available on request. The data are not publicly available due to information that could compromise the privacy of research participant.
Credit Author Statement
Author contribution: SY, TK, YY, NS, and AKL conceived of and designed the study. SY and MK performed data extraction. SY, TK, and MM performed the data analysis and interpreted the results. SY and AKL wrote the manuscript. SY, MK, TK, MM, AKL, YY, and NS revised the manuscript.
Guarantor: Shinichiro Yokota and Alan Kawarai Lefor