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Original Research: COPD |

Impact of COPD on Postoperative OutcomesCOPD and Postoperative Outcomes: Results From a National Database FREE TO VIEW

Himani Gupta, MD; Bala Ramanan, MBBS; Prateek K. Gupta, MD; Xiang Fang, PhD; Ann Polich, MD; Ariel Modrykamien, MD, FCCP; Dan Schuller, MD, FCCP; Lee E. Morrow, MD, FCCP
Author and Funding Information

From the Department of Medicine (Dr H. Gupta), William S. Middleton Memorial Veterans Hospital, Madison, WI; Department of Surgery (Dr Ramanan), Biostatistical Core (Dr Fang), Department of Medicine (Dr Polich), and Division of Pulmonary, Critical Care and Sleep Medicine (Drs Modrykamien, Schuller, and Morrow), Creighton University, Omaha, NE; and the Department of Surgery (Dr P. Gupta), University of Wisconsin Hospital and Clinics, Madison, WI.

Correspondence to: Prateek K. Gupta, MD, Department of Surgery, University of Wisconsin Hospital and Clinics, 600 Highland Ave, Madison, WI 53792; e-mail: pgupta@uwhealth.org


Part of this article was presented at the CHEST Annual Meeting, October 26-31, 2010, Vancouver, BC, Canada.

Funding/Support: The authors have reported to CHEST that no funding was received for this study.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians. See online for more details.


Chest. 2013;143(6):1599-1606. doi:10.1378/chest.12-1499
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Published online

Background:  Although COPD affects large sections of the population, its effects on postoperative outcomes have not been rigorously studied. The objectives of this study were to describe the prevalence of COPD in patients undergoing surgery and to analyze the associations between COPD and postoperative morbidity, mortality, and hospital length of stay.

Methods:  Patients with COPD who underwent surgery were identified from the National Surgical Quality Improvement Program database (2007-2008). Univariate and multivariate analyses were performed on this multicenter, prospective data set (N = 468,795).

Results:  COPD was present in 22,576 patients (4.82%). These patients were more likely to be older, men, white, smokers, and taking corticosteroids and had a lower BMI (P < .0001 for each). Median length of stay was 4 days for patients with COPD vs 1 day in those without COPD (P < .0001). Thirty-day morbidity rates were 25.8% and 10.2% for patients with and without COPD, respectively (P < .0001). Thirty-day death rates were 6.7% and 1.4% for patients with and without COPD, respectively (P < .0001). After controlling for > 50 comorbidities through logistic regression modeling, COPD was independently associated with higher postoperative morbidity (OR, 1.35; 95% CI, 1.30-1.40; P < .0001) and mortality (OR, 1.29; 95% CI, 1.19-1.39; P < .0001). Multivariate analyses with each individual postoperative complication as the outcome of interest showed that COPD was associated with increased risk for postoperative pneumonia, respiratory failure, myocardial infarction, cardiac arrest, sepsis, return to the operating room, and renal insufficiency or failure (P < .05 for each).

Conclusions:  COPD is common among patients undergoing surgery and is associated with increased morbidity, mortality, and length of stay.

COPD is a debilitating disease that causes significant morbidity and mortality, and despite being a preventable disease, its prevalence is rising because of the smoking epidemic.1 It is the fourth most common cause of death worldwide, and the World Health Organization estimates it to become the third by 2030.2 In 2008, 12.1 million US adults were estimated to have COPD,3 and it is a common comorbidity among surgical patients.

As a consequence of increasing prevalence of COPD, prolonged life expectancy, and greater needs for invasive procedures, surgeons are encountering large numbers of high-risk pulmonary patients.4,5 It is, therefore, imperative that we fully understand the surgical risks associated with pulmonary disease processes. Despite the prevalence of COPD, its effects on postoperative outcomes have not been rigorously studied. Our objectives were to describe the prevalence of COPD in patients undergoing surgery and to assess the association between COPD and 30-day postoperative morbidity, mortality, and hospital length of stay (LOS).

Data Set

Data were extracted from the 2007 and 2008 American College of Surgeons National Surgical Quality Improvement Program (NSQIP) Participant Use Data Files.6 These are multicenter, prospective databases of 183 (year 2007) and 211 (year 2008) participating academic and private US hospitals. In 2007, NSQIP collected data on 136 variables (135 in 2008) for patients who underwent major surgical procedures in both the inpatient and the outpatient setting. In NSQIP, a participating hospital’s surgical clinical reviewer (SCR) captures the data. The data are collected on the basis of strict criteria formulated by a definition committee. To ensure collection of high-quality data, the American College of Surgeons developed a host of different training mechanisms for the SCR and conducts an interrater reliability audit of NSQIP participating sites.6 The processes of SCR training, interrater reliability auditing, data collection, and sampling methodology have been previously described in detail.69 The combined results of the audits revealed an overall disagreement rate of approximately 1.99% for all assessed program variables. Trauma patients, transplant patients, and patients aged < 16 years are excluded from the NSQIP database. Because this study uses a publicly available national data set, it is exempt from institutional review board approval.

Patients

Patients who underwent the surgeries listed in Table 1 were studied (n = 211,410 in the 2007 data set; n = 257,385 in the 2008 data set). Data included demographic, lifestyle, comorbidity, and other variables. The list of variables extracted is provided in e-Appendix 1. The definitions for variables collected in the NSQIP database have been described in previous reports.610 Laboratory values were categorized as normal and abnormal according to NSQIP definitions, and missing data comprised an indicator variable as a third categorical level.11 It should be noted that except for laboratory variables for which clinical issues have a substantial impact on the ordering of tests, missing values are virtually nonexistent for NSQIP predictors.

Table Graphic Jump Location
Table 1 —Univariate Analysis of Preoperative Demographics

Data are presented as median. ASA = American Society of Anesthesiologists; ENT = ear, nose, and throat; FG/HPB = foregut and hepatopancreatobiliary; GBAAS = gall bladder, appendix, adrenals, and spleen; VA = Veterans Administration.

Definition of COPD

NSQIP defines COPD (eg, emphysema, chronic bronchitis) as resulting in any one or more of the following: (1) functional disability from COPD (eg, dyspnea, inability to perform activities of daily living); (2) hospitalization in the past for treatment of COPD requiring long-term bronchodilator therapy with oral or inhaled agents; and (3) an FEV1 < 75% predicted on pulmonary function testing. Patients whose only pulmonary disease is asthma, an acute and chronic inflammatory disease of the airways resulting in bronchospasm, are not included. Patients with diffuse interstitial fibrosis or sarcoidosis are not included.

Outcome

Outcome variables were total hospital LOS in days, major morbidity, and mortality. The postoperative complications comprising major morbidity in the data set were deep wound infection, organ and space infection, wound disruption and dehiscence, pneumonia, reintubation, failure to wean from ventilator within 48 h, pulmonary embolism, DVT and thrombophlebitis, renal insufficiency with creatinine level rising to > 2 mg/dL but no dialysis, acute renal failure (ARF) requiring dialysis, stroke, coma for > 24 h, postoperative transfusion of > 4 units packed RBCs, cardiac arrest requiring CPR, myocardial infarction, sepsis, septic shock, graft and prosthesis failure, nerve deficit, and return to the operating room. Urinary tract infection and superficial wound infection comprised minor morbidity. Outcomes are assessed for up to 30 postoperative days in NSQIP.

Statistical Analysis

Univariate exploratory analysis was performed using Pearson χ2 test and Fisher exact test for categorical variables and the T and F test for continuous variables. Total hospital LOS in days was analyzed using an analysis of covariance model. Multivariate logistic regression analyses assessed risk factors for major morbidity, mortality, and each major postoperative complication. The model selection for the regression analyses was based on a stepwise procedure, which alternates between dropping the least significant variable from the model and then reconsidering all potential variables for reintroduction into the model until no more variables can be added. A variable that is individually predictive of adverse events may not be selected by the stepwise procedure when adding the variable does not significantly improve the predictive power of the existing model.12,13

The accuracy of the logistic regression models were assessed by measuring the discrimination. If discrimination is perfect, then for all pairs, the predicted risk will be greater for the case than for the noncase and the C statistic will equal 1.0. If discrimination is no better than chance, the C statistic will equal 0.50. All statistical analyses were performed using SAS, version 9.2 (SAS Institute, Inc) software.

Demographics

Of the 468,795 patients who underwent surgery, 57.3% were women, and the mean age was 55.0 ± 17.0 years. The overall mean BMI was 30.8 ± 11.2 kg/m2 (interquartile range [IQR], 25.0-34.6 kg/m2); patients with COPD had a significantly lower BMI (P < .0001) and tended to be older than patients without COPD (P < .0001) (Table 2).

Table Graphic Jump Location
Table 2 —Univariate Analysis of Preoperative Comorbidities

SIRS = systemic inflammatory response syndrome.

Preoperative Comorbidities and Therapy Characteristics

Cardiovascular, renal, neurologic, infectious, liver, and respiratory comorbidities were more commonly seen in patients with COPD than in those without COPD (P < .0001) (Table 2). They also had relatively higher rates of diabetes and were more functionally dependent (P < .0001 for both). Patients with COPD had a higher percentage of emergency cases (P < .0001). Variations in surgeries were observed (Table 2). Patients with COPD had longer operative times (P < .0001) (Table 3).

Table Graphic Jump Location
Table 3 —Univariate Analysis of Intraoperative and Postoperative Events

Data are presented as mean ± SD or median. LOS = length of stay.

Postoperative Outcomes (Univariate Analyses)

Patients with COPD had significantly higher rates of cardiovascular, graft, renal, neurologic, infectious, wound, and respiratory complications (P < .0001) (Table 3). LOS was significantly longer for patients with COPD (mean, 7.4 ± 11.8 days; median, 4 days) vs those without COPD (mean, 3.5 ± 7.2 days; median, 1 day). The 30-day overall morbidity rate was 25.8% for patients with COPD vs 10.2% for those without (P < .0001). The 30-day mortality rate was also higher for patients with COPD (6.7% vs 1.4%; P < .0001).

Postoperative Outcomes (Multivariate Analyses)

On multivariate logistic regression, after controlling for > 50 comorbidities and type of surgery, COPD was independently associated with higher postoperative morbidity (OR, 1.35; 95% CI, 1.30-1.40; P < .0001) and mortality (OR, 1.29; 95% CI, 1.19-1.39; P < .0001; C statistic, 0.80 vs 0.94 for morbidity and mortality, respectively).

To study the specific impact of COPD on LOS, multivariate analysis of covariance was conducted, controlling for all comorbidities and type of surgery. Compared with the absence of COPD, the presence of COPD was independently associated with a 0.75-day longer hospital stay (P < .0001).

A series of logistic regression models were subsequently used to assess the independent effect of COPD on each of the 20 major complications. COPD was associated with a higher risk for postoperative pneumonia (OR, 1.71; 95% CI, 1.59-1.83; P < .0001), reintubation (OR, 1.54; 95% CI, 1.42-1.66; P < .0001), failure to wean from ventilator within 48 h (OR, 1.45; 95% CI, 1.35-1.56; P < .0001), renal insufficiency with creatinine level > 2 mg/dL but no dialysis (OR, 1.17; 95% CI, 1.0-1.36; P = .046), ARF requiring dialysis (OR, 1.28; 95% CI, 1.13-1.46; P = .0001), cardiac arrest (OR, 1.29; 95% CI, 1.13-1.47; P = .0002), myocardial infarction (OR, 1.25; 95% CI, 1.02-1.54; P = .03), postoperative wound dehiscence (OR, 1.45; 95% CI, 1.28-1.63; P < .0001), sepsis (OR, 1.13; 95% CI, 1.05-1.22; P = .001), and septic shock (OR, 1.44; 95% CI, 1.33-1.56; P < .0001).

The prevalence of COPD is higher among surgical candidates than among age-matched population groups.5 There is, however, a paucity of high-quality studies addressing the association of complications in patients with COPD undergoing surgery. Some studies have shown adverse postoperative outcomes in patients with COPD,1416 but these studies have been limited to certain surgical subspecialties with a small number of patients.

In the present study, we included patients from all specialties of surgery as shown in Table 1. Cardiovascular, renal, neurologic, infectious, liver, and respiratory comorbidities were more commonly seen in patients with COPD than in those without COPD (P < .0001) (Table 2). This finding is similar to those in relatively smaller studies that showed a high incidence of comorbidities in patients with COPD.17,18 Recognition of these conditions is important in order to preoperatively optimize these high-risk patients for surgery because comorbidities are associated with increased costs and mortality.19 Patients with COPD were older and had significantly lower BMI. The risk of developing COPD increases exponentially with age, with the incidence being more common after age 40.20 Lower BMI may be related to poor nutritional status in these patients. A number of observational studies2124 have shown that a low BMI is associated with a poor prognosis in patients with COPD independent of the degree of ventilatory impairment. Lower BMI often is associated with protein depletion, which in turn is associated with impairment of respiratory muscle strength, reduction in diaphragmatic muscular mass, and maximum voluntary ventilation, predisposing the patient to more pulmonary complications.25

In the present study, COPD was independently associated with postoperative 30-day morbidity and mortality on multivariable logistic regression analyses. Patients with COPD had an overall 30-day mortality rate of 6.7% compared with 1.4% in patients without COPD (P < .0001), which is comparable to findings in the literature from select surgical subspecialties.14,26 Manganas et al15 demonstrated a longer LOS in patients with severe COPD undergoing coronary artery bypass graft surgery, a finding that has also been seen after noncardiac surgery in the present study.

COPD was independently associated with postoperative pneumonia and respiratory failure (reintubation or failure to wean from ventilator within 48 h) in the present study. Previously published studies similarly have shown COPD to be a well-known risk factor for postoperative pulmonary complications, probably because of impairment in gas exchange and mucociliary clearance of aspirated bacteria.2730 Postoperative respiratory failure is one of the patient safety indicators developed by the Agency for Healthcare Research and Quality31 and is a major burden on health-care resources. Preoperative screening of these high-risk patients, optimization of organ function, and standardization of health-care processes may improve patient safety and surgical outcomes. Advances in anesthesia and surgery that have been beneficial in patients with COPD include minimally invasive procedures and selective nasogastric drainage, regional anesthetic blockade, and laryngeal masks to minimize airway instrumentation, low tidal volume ventilation, use of appropriate anesthetic agents, accurate physiologic monitoring, and prevention and treatment of atelectasis by lung recruitment maneuvers.5

COPD was found to be significantly associated with postoperative wound dehiscence, which is another patient safety indicator developed by the Agency for Healthcare Research and Quality. Few single-center retrospective studies have shown COPD to be associated with wound dehiscence after abdominal and cardiothoracic operations.3235 The high incidence of dehiscence in this patient population could be a result of coughing, hypoxemia, use of corticosteroids, and poor nutritional status, which are all risk factors for wound dehiscence.34 In the present study, COPD was also a significant factor influencing postoperative sepsis and septic shock, which has not previously been documented. Anergy on immunologic testing has been demonstrated in patients with COPD,36 and anergy with nutritional deficit is associated with increased sepsis-related deaths in elective surgical patients.37

Patients experiencing postoperative cardiac adverse events are known to have a high postoperative mortality rate.38 COPD was found to be independently associated with postoperative cardiac arrest and myocardial infarction in the present study, similar to previous smaller studies.39,40 Cardiac and pulmonary diseases share common risk factors, such as older age and smoking, and patients with COPD commonly have cardiovascular comorbidities such as hypertension, occlusive or aneurysmal arterial disease, heart failure, cardiac arrhythmia, conduction blockade, and ischemic heart disease. Implementation of cardioprotective strategies may help to prevent postoperative adverse cardiac events.5

Rodrigues et al41 found COPD to be a risk factor for ARF after cardiac surgery. To the best of our knowledge, the association between COPD and postoperative renal failure in noncardiac surgery patients has not been assessed. In the present study, COPD was significantly associated with both postoperative renal insufficiency and ARF requiring dialysis. Coronary artery disease, which is highly prevalent in patients with COPD, is associated with vascular kidney disease. Furthermore, both nicotine and selected heavy metals that are components of smoke are risk factors for kidney disease.42 Incalzi et al42 demonstrated a high prevalence of subclinical chronic renal failure in patients with COPD, which may be a contributing factor to the postoperative renal failure seen in the present study.

This NSQIP database study has many strengths not seen in other studies, including a large sample size and, thus, smaller CIs in the assessment of risk factors. The current study also presents one of the most representative estimates of the postoperative risks associated with COPD in a broad nationwide population setting. It is based on data obtained from both academic and community hospitals, includes data that have been independently validated and audited, and takes into account multiple preoperative variables.

The study has some limitations. It was a retrospective analysis of prospectively recorded data. We were unable to determine the severity of COPD from the database, which may have had an impact on outcomes. Preoperative pulmonary function tests, dependence on home oxygen, and the impact of preoperative optimization of COPD on surgical outcomes could not be studied. Obstructive sleep apnea is not a variable in NSQIP, and thus, its impact could not be studied. Data on medication use, besides long-term corticosteroids, are also not available in the NSQIP data set. The impact of COPD on surgical patients beyond 30 days cannot be determined through the NSQIP database.

In conclusion, patients with COPD are older, have a lower BMI, and have several comorbidities. COPD, as defined in NSQIP (without pulmonary function tests), is an independent predictor of postoperative mortality and morbidity, including wound dehiscence; sepsis; and pulmonary, cardiac, and renal complications. Knowledge of the increased risk associated with COPD may improve patient selection and the informed consent process. Perioperative optimization of these patients may help to improve outcomes and decrease health-care costs, and there is a need to study such strategies in multicenter, randomized prospective trials.

Author contributions: Dr P. Gupta had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Dr H. Gupta: contributed to all aspects of the manuscript.

Dr Ramanan: contributed to all aspects of the manuscript.

Dr P. Gupta: contributed to all aspects of the manuscript.

Dr Fang: contributed to all aspects of the manuscript.

Dr Polich: contributed to all aspects of the manuscript.

Dr Modrykamien: contributed to all aspects of the manuscript.

Dr Schuller: contributed to all aspects of the manuscript.

Dr Morrow: contributed to all aspects of the manuscript.

Financial/nonfinancial disclosures: The authors have reported to CHEST that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Other contributions: This work was performed at the University of Wisconsin-Madison and Creighton University, Omaha, NE. The ACS NSQIP and the hospitals participating in the ACS NSQIP are the source of the data used herein; they have not verified and are not responsible for the statistical validity of the data analysis or the conclusions derived by the authors. This study does not represent the views or plans of the ACS or the ACS NSQIP.

Additional information: The e-Appendix can be found in the “Supplemental Materials” area of the online article.

ARF

acute renal failure

IQR

interquartile range

LOS

length of stay

NSQIP

National Surgical Quality Improvement Program

SCR

surgical clinical reviewer

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Figures

Tables

Table Graphic Jump Location
Table 1 —Univariate Analysis of Preoperative Demographics

Data are presented as median. ASA = American Society of Anesthesiologists; ENT = ear, nose, and throat; FG/HPB = foregut and hepatopancreatobiliary; GBAAS = gall bladder, appendix, adrenals, and spleen; VA = Veterans Administration.

Table Graphic Jump Location
Table 2 —Univariate Analysis of Preoperative Comorbidities

SIRS = systemic inflammatory response syndrome.

Table Graphic Jump Location
Table 3 —Univariate Analysis of Intraoperative and Postoperative Events

Data are presented as mean ± SD or median. LOS = length of stay.

References

Nazir SA, Erbland ML. Chronic obstructive pulmonary disease: an update on diagnosis and management issues in older adults. Drugs Aging. 2009;26(10):813-831. [CrossRef] [PubMed]
 
World Health Organization.World Health Statistics. Geneva, Switzerland: World Health Organization; 2008.
 
Centers for Disease Control and Prevention. National Center for Health Statistics: National Health Interview Survey Raw Data, 2008;. Analysis performed by American Lung Association Research and Program Services using SPSS and SUDAAN software.
 
Halbert RJ, Natoli JL, Gano A, Badamgarav E, Buist AS, Mannino DM. Global burden of COPD: systematic review and meta-analysis. Eur Respir J. 2006;28(3):523-532. [CrossRef] [PubMed]
 
Licker M, Schweizer A, Ellenberger C, Tschopp JM, Diaper J, Clergue F. Perioperative medical management of patients with COPD. Int J Chron Obstruct Pulmon Dis. 2007;2(4):493-515. [PubMed]
 
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