This study compares the postoperative mortality risk among patients with vs without heart failure who undergo elective ambulatory surgery.
Key Points
Question
What is the association between severity of heart failure and risk of postoperative mortality among patients undergoing ambulatory surgery?
Findings
In this cohort study of 355 121 patients undergoing ambulatory surgery, the crude 90-day mortality was 2.00% among patients with heart failure and 0.39% among patients without heart failure. The crude risk of 30-day postoperative complications was 5.7% among patients with heart failure and 2.7% among patients without heart failure.
Meaning
Heart failure with or without symptoms was associated with increased risk of 90-day mortality and 30-day postoperative complications.
Abstract
Importance
Heart failure is an established risk factor for postoperative mortality, but how heart failure is associated with operative outcomes specifically in the ambulatory surgical setting is not well characterized.
Objective
To assess the risk of postoperative mortality and complications in patients with vs without heart failure at various levels of echocardiographic (left ventricular systolic dysfunction) and clinical (symptoms) severity who were undergoing ambulatory surgery.
Design, Setting, and Participants
In this US multisite retrospective cohort study of all adult patients undergoing ambulatory, elective, noncardiac surgery in the Veterans Affairs Surgical Quality Improvement Project database during fiscal years 2009 to 2016, a total of 355 121 patient records were identified and analyzed with 1 year of follow-up after surgery (final date of follow-up September 1, 2017).
Exposures
Heart failure, left ventricular ejection fraction, and presence of signs or symptoms of heart failure within 30 days of surgery.
Main Outcomes and Measures
The primary outcomes were postoperative mortality at 90 days and any postoperative complication at 30 days.
Results
Among 355 121 total patients, outcome data from 19 353 patients with heart failure (5.5%; mean [SD] age, 67.9 [10.1] years; 18 841 [96.9%] male) and 334 768 patients without heart failure (94.5%; mean [SD] age, 57.2 [14.0] years; 301 198 [90.0%] male) were analyzed. Compared with patients without heart failure, patients with heart failure had a higher risk of 90-day postoperative mortality (crude mortality risk, 2.00% vs 0.39%; adjusted odds ratio [aOR], 1.95; 95% CI, 1.69-2.44), and risk of mortality progressively increased with decreasing systolic function. Compared with patients without heart failure, symptomatic patients with heart failure had a greater risk of mortality (crude mortality risk, 3.57%; aOR, 2.76; 95% CI, 2.07-3.70), as did asymptomatic patients with heart failure (crude mortality risk, 1.85%; aOR, 1.85; 95% CI, 1.60-2.15). Patients with heart failure had a higher risk of experiencing a 30-day postoperative complication than did patients without heart failure (crude risk, 5.65% vs 2.65%; aOR, 1.10; 95% CI, 1.02-1.19).
Conclusions and Relevance
In this study, among patients undergoing elective, ambulatory surgery, heart failure with or without symptoms was significantly associated with 90-day mortality and 30-day postoperative complications. These data may be helpful in preoperative discussions with patients with heart failure undergoing ambulatory surgery.
Introduction
Heart failure is an established risk factor for postoperative mortality across a broad range of surgical specialties.1,2,3,4,5,6 Consequently, most commonly used risk prediction tools, such as the American College of Surgeons (ACS) Surgical Risk Calculator, include heart failure as a predictor of adverse postoperative events.7 Much of the work documenting this association, however, has been derived from studies focused on major high-risk operations,1,3 with a paucity of medical literature describing outcomes in an ambulatory setting. As improved medical care has substantially increased survival after heart failure diagnosis,8 patients with heart failure are now increasingly undergoing elective ambulatory procedures. This situation has resulted in an increasing need to better understand and quantify the degree to which postoperative risk is influenced by heart failure in the outpatient setting to optimize clinical decision making and improve preoperative counseling.
We recently reported that systolic function as measured by left ventricular ejection fraction (LVEF) and the presence of heart failure symptoms in the 30 days before surgery were associated with significantly increased 90-day postoperative mortality compared with patients without heart failure among a cohort of more than 600 000 veterans undergoing elective noncardiac surgery.9 In addition, all patients with heart failure, including those with no clinical symptoms and preserved ejection fraction, were at higher risk of postoperative mortality than were those without heart failure. Ambulatory surgery procedures are perceived as very low risk. Mortality and morbidity outcomes in patients with heart failure in the ambulatory surgical setting have not been previously reported to our knowledge. Whether the trends and associations seen in the larger cohort persist in the ambulatory setting and whether they vary by surgical subspecialty is unknown. The purpose of this study was to assess the 90-day postoperative mortality risk among patients with heart failure compared with patients without heart failure who were undergoing elective ambulatory surgery. We hypothesized that all patients with symptomatic and asymptomatic heart failure undergoing ambulatory surgery would have elevated crude and adjusted risk of postoperative mortality compared with those without heart failure.
Methods
Data Sources and Study Population
This cohort study was approved by the Stanford University Institutional Review Board and Department of Veterans Affairs, and a waiver of informed consent was obtained because patient data were deidentified. Two national Veterans Affairs (VA) databases were used to assemble the cohort. The VA Surgical Quality Improvement Program (VASQIP) has trained data extractors who sample a fraction of cases at individual facilities and enter detailed clinical information into a centralized database.10,11 The VASQIP nurse reviewers abstracted postoperative data from a random sample of operations according to the VASQIP sampling framework: every 8 days, the first 36 consecutive operations were reviewed, with limitations on how many high-volume, low-risk procedures were assessed.12 When certain pertinent information was not available from VASQIP, the VA Corporate Data Warehouse was used, which extracts data directly from the VA electronic medical records system. Medical comorbidities for each participant were extracted from VASQIP (hypertension, stroke, chronic obstructive pulmonary disease, peripheral vascular disease, and disseminated cancer) and from VA Corporate Data Warehouse diagnostic codes (atrial fibrillation, diabetes, asthma, aortic stenosis, mitral regurgitation, pulmonary hypertension, and obstructive sleep apnea). The LVEFs were obtained from echocardiogram reports using a previously validated natural language processing algorithm.13,14 Follow-up data were available for each participant for a minimum of 1 year.
All VASQIP-sampled outpatient operations (standard and intermediate complexity) during fiscal years 2009 to 2016 were eligible for inclusion, with a final date of follow-up of September 1, 2017. Cardiac operations, emergency operations, and nonsurgical procedures (ie, bronchoscopy, pacemaker insertion, and endoscopy) were excluded. All patients undergoing multiple eligible operations within the study period contributed only their index procedure.
Classification of Heart Failure and Subpopulations
The classification of heart failure by diagnostic codes in the VA health care system is highly specific (>95%) and has good sensitivity (75%-90%).15,16,17,18 Patients were classified as having heart failure if they had 1 or more inpatient admission or 2 or more outpatient clinic visits with a diagnosis of heart failure by International Classification of Diseases, Ninth Revision code within 3 years of surgery.19 These criteria properly excluded patients with a single outpatient visit for whom heart failure was excluded after evaluation. Patients with heart failure were further subdivided by LVEF (if an echocardiogram within 5 years of surgery was available) and presence of heart failure signs and symptoms. The following established cutoffs were used for LVEF: preserved, 50% or more; mildly reduced, 40% to 49%; moderately reduced, 30% to 39%; and severely reduced, less than 30%.20 Patients were classified as having symptomatic heart failure by the ACS-NSQIP definition: newly diagnosed or chronic heart failure with signs or symptoms within 30 days of surgery.21
Surgical Complexity
To adjust for the type of operation performed on patients with and without heart failure, all operations were classified by the VA Surgical Complexity Matrix. The VA health care system uses this matrix to designate which facilities can perform which surgical procedures.22,23 The system assigns a complexity level (standard, intermediate, or complex) to every Current Procedural Terminology code based on intraoperative and postoperative risk inherent to the procedure (eTable 1 in the Supplement). Procedures that were coded as complex (n = 1580 [0.4%]) were excluded. These procedures were likely incorrectly coded as ambulatory because these operations always result in hospital admission. Surgical complexity was included as a covariate in the final multivariable models.
Outcomes
The primary outcomes of this study were 30-day complication rate and 90-day all-cause postoperative mortality. Secondary outcomes included 30-day postoperative cardiac arrest, myocardial infarction, stroke, surgical site infection, urinary tract infection, and 72-hour postoperative bleeding event (defined as transfusion for any reason of >4 U of packed red blood cells or whole blood after the patient has left the operating room). Date of death was determined using the Social Security Administration Death Master Files.
Statistical Analysis
Demographic and clinical characteristics of patients with and without heart failure were compared with χ2 tests for categorical variables and unpaired, 2-tailed t tests for continuous variables. Odds ratios were generated using simple or multivariable logistic regression and 95% CIs computed with the Wald χ2 test. Potential confounders were assessed based on a priori knowledge and the literature.6,24 The following factors were considered: sex, race/ethnicity, age, body mass index, smoking, alcohol use, hypertension, atrial fibrillation, diabetes, coronary artery disease, history of stroke, asthma, chronic obstructive pulmonary disease, peripheral vascular disease, disseminated cancer, surgical complexity level, American Society of Anesthesiologists (ASA) class (the classification is a subjective assessment of a patient’s overall health by a physician that ranges from 1 [a healthy patient] to 5 [a moribund patient who is not expected to survive without the operation]),25 aortic stenosis, mitral regurgitation, pulmonary hypertension, obstructive sleep apnea, VA facility, preoperative creatinine level, and preoperative hematocrit. Covariates were screened by individual addition to the univariable model, and those that altered the exposure estimate by 10% or more were included in the final model.
Race/ethnicity is associated with long-term survival in patients with heart failure and was thus included as a covariate.26 Race/ethnicity classification was determined by the participant and was based on a fixed-category questionnaire.
The final analysis consisted of 3 multivariable mixed-effects logistic regression models with random intercepts to account for clustering by VA facility. Each model used patients without heart failure as the reference group but organized patients with heart failure using a different, preplanned classification scheme. The first model compared the postoperative mortality risk among all patients with and without heart failure. The second model classified patients with heart failure (the primary exposure) by their LVEF (4 levels). The third model classified patients with heart failure by the presence of heart failure symptoms (2 levels). The expect (E) value represents the minimum magnitude of association required between an unmeasured confounder and the exposure and outcome, conditional on measured covariates, to fully attenuate the observed exposure-outcome association.27 An E value was calculated for the observed overall association between heart failure and postoperative mortality using a publicly available online calculator.28 Relevant P values for trend were calculated with the Wald χ2 test after converting the categorical LVEF or symptoms variables into a continuous variable; 2-sided P < .05 was considered to be statistically significant.
Analyses of the association between heart failure and postoperative complications were conducted using multivariable logistic regression adjusted for the confounders identified above. The proportion of missing nonlaboratory, nonimaging covariates was less than 1%; thus, patients with missing nonlaboratory, nonimaging covariates were excluded from the analysis. Missing preoperative laboratory values (approximately 9%) were imputed with a single conditional imputation approach using age- and sex-adjusted norms. As measured by echocardiography, LVEF was missing in 678 patients with heart failure (3.5%), and patients with missing LVEF were excluded from subset analyses pertaining to left ventricular systolic function.
On the basis of the sample size of the cohort included in this analysis (N = 355 121; 19 353 [5.5%] with heart failure), this study had 99.9% power to detect odds ratios greater than 1.5 for the association between heart failure and postoperative mortality at α = .05.3,29 SAS statistical software, version 9.4 (SAS Institute Inc) was used for all analyses.
Results
Cohort Characteristics
Among 355 121 total patients, outcome data from 19 353 patients with heart failure (5.5%; mean [SD] age, 67.9 [10.1] years; 18 841 [96.9%] male) and 334 768 patients without heart failure (94.5%; mean [SD] age, 57.2 [14.0] years; 301 198 [90.0%] male) were analyzed; 23.2% of patients with heart failure were classified as having ASA class 4 disease (Table 1). Patients with heart failure were more likely to have ASA class 3 or higher disease than patients without heart failure (18 584 [95.1%] vs 190 771 [56.6%]). At the time of surgery, patients with heart failure vs those without heart failure had higher creatinine levels (median, 1.10 vs 0.98 mg/dL [to convert to micromoles per liter, multiply by 88.4]) and lower hematocrit (mean, 40.1% vs 42.5% [to convert to proportion of 1.0, multiply by 0.01]).
Table 1. Demographics and Medical History of Patients With and Without Heart Failure Undergoing Outpatient Surgerya.
| Variable | Heart Failure | No Heart Failure |
|---|---|---|
| Total | 19 353 (5.5) | 334 768 (94.5) |
| Sex | ||
| Male | 18 841 (96.9) | 301 198 (90.0) |
| Female | 612 (3.2) | 33 570 (10.0) |
| Race/ethnicity | ||
| White, non-Hispanic | 13 328 (68.9) | 214 804 (64.2) |
| Black, non-Hispanic | 2792 (14.4) | 48 537 (14.5) |
| Hispanic | 816 (4.2) | 18 023 (5.4) |
| Other | 144 (0.7) | 4372 (1.3) |
| Not reported | 2273 (11.7) | 49 032 (14.7) |
| Age, mean (SD), y | 67.9 (10.1) | 57.2 (14.0) |
| BMI, mean (SD) | 30.2 (6.7) | 29.0 (5.6) |
| Current smoker | 5097 (26.3) | 105 588 (31.5) |
| Current alcohol use | 927 (4.8) | 22 724 (6.8) |
| Medical historyb | ||
| Hypertension | 16 787 (86.8) | 175 584 (52.5) |
| Coronary artery disease | 12 706 (65.6) | 56 127 (16.8) |
| Diabetes mellitus | 10 735 (55.5) | 92 577 (27.7) |
| Atrial fibrillation | 7376(38.1) | 23 689 (7.1) |
| Chronic obstructive pulmonary disease | 5068 (26.2) | 29 612 (8.9) |
| History of stroke | 1965 (10.2) | 10 676 (3.2) |
| Peripheral vascular disease | 1187 (6.1) | 4788 (1.4) |
| Asthma | 1945 (10.1) | 27 385 (8.2) |
| Aortic stenosis | 1393 (7.2) | 5021 (1.5) |
| Mitral regurgitation | 965 (5.0) | 3014 (0.9) |
| Pulmonary hypertension | 735 (3.8) | 1340 (0.4) |
| Disseminated cancer | 146 (0.8) | 1365 (0.4) |
| ASA classc | ||
| 1 | 24 (0.1) | 14 841 (4.4) |
| 2 | 905 (4.7) | 131 178 (39.2) |
| 3 | 13 958 (72.1) | 179 555 (53.6) |
| 4 | 4462 (23.1) | 9178 (2.7) |
| 5 | 4 (0.0) | 16 (0.0) |
| Laboratory valuesd | ||
| Preoperative creatinine level, median (IQR), mg/dL | 1.10 (0.90-1.40) | 0.98 (0.83-1.10) |
| Preoperative hematocrit, mean (SD), % | 40.1 (5.1) | 42.5 (4.1) |
| Anesthesia techniquee | ||
| General | 14 673 (75.8) | 286 085 (85.5) |
| Epidural or spinal | 1151(7.5) | 14 142(4.2) |
| Monitored anesthesia care | 2389 (12.4) | 23 690 (7.1) |
| Local | 332 (1.7) | 3347 (1.0) |
| Other | 502 (2.6) | 7425 (2.2) |
| Surgical complexityf | ||
| Standard | 15 052 (77.8) | 280 905 (83.9) |
| Intermediate | 43,01 (22.2) | 53 863 (16.1) |
Abbreviations: ACE, angiotensin-converting enzyme; ARB, angiotensin receptor blocker; ASA, American Society of Anesthesiologists; BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); IQR, interquartile range.
SI conversion factors: to convert creatinine to micromoles per liter, multiply by 88.4; hematocrit to proportion of 1.0, multiply by 0.01.
Data are presented as number (percentage) of patients unless otherwise indicated. P < .001 for all comparisons.
Medical comorbidities were derived from medical record extraction by trained Veterans Affairs Surgical Quality Improvement Program nurses (hypertension, stroke, chronic obstructive pulmonary disease, peripheral vascular disease, and disseminated cancer) and International Classification of Diseases, Ninth Revision diagnostic codes in the electronic medical record (atrial fibrillation, diabetes, asthma, aortic stenosis, mitral regurgitation, and pulmonary hypertension).
The ASA Physical Status Classification system is a subjective assessment of a patient’s overall health by a physician. The classification ranges from ASA class 1 (a healthy patient) to ASA class 5 (a moribund patient who is not expected to survive without the operation).
Data were missing for 9.0% of patients for creatinine level and 9.6% for patients for hematocrit.
Does not include 85 patients with missing anesthesia technique.
Surgical complexity reflects assignment in the Veterans Affairs Surgical Complexity matrix, which assigns every surgical procedure (by Current Procedural Terminology code) a value of standard, intermediate, or complex by its intraoperative and perioperative risk to the patient.
Data on LVEF were available for 18 873 patients with heart failure (96.5%); 8.8% had active signs or symptoms of heart failure in the 30 days before surgery (eTable 2 in the Supplement). A total of 11 839 (60.6%) had documented preserved systolic function (LVEF≥50%), and 7034 (36.0%) had reduced LVEF—3085 (15.8%) with mild (LVEF, 40%-49%), 2379 (12.2%) with moderate (LVEF, 30%-39%), and 1570 (8.0%) with severe (LVEF<30%) systolic depression.
Review of pharmacy records suggested optimal medical management for most patients with heart failure, with 17 763 (90.8%) receiving a β-blocker and 17 918 (91.7%) receiving an angiotensin-converting enzyme inhibitor (eTable 2 in the Supplement). A total of 6712 patients with heart failure (34.7%) received a potassium-sparing diuretic. Patients in each LVEF subgroup received standard and intermediate complexity–level operations (eTable 3 in the Supplement).
Postoperative Mortality and Complications
The crude 90-day postoperative mortality risk among patients with a history of heart failure was 2.00% compared with 0.39% among patients without heart failure. Heart failure was significantly associated with postoperative mortality after multivariable adjustment for clinical, demographic, and surgical factors (adjusted odds ratio [aOR], 1.95; 95% CI, 1.69-2.44) (Table 2). Risk of mortality progressively increased with decreased systolic function, with all ejection fraction groups (preserved and reduced) having a higher risk than patients without heart failure. Compared with patients without heart failure, asymptomatic (aOR, 1.85; 95% CI, 1.60-2.15) and symptomatic (aOR, 2.76; 95% CI, 2.07-3.70) patients with heart failure had a higher risk of postoperative mortality. The E value for the heart failure postoperative mortality point estimate was high (3.31), as was the E value for the 95% CI (2.77), indicating that it is unlikely that an unmeasured variable explained the observed association between heart failure and mortality. Patients undergoing ambulatory general (aOR, 2.05; 95% CI, 1.19-2.54), vascular (aOR, 2.00; 95% CI, 1.36-2.96), urologic (aOR, 2.29; 95% CI, 1.71-3.04), otolaryngologic (aOR, 2.30; 95% CI, 1.28-4.16), and orthopedic (aOR 2.06; 95% CI, 1.33-3.17) surgery had a higher risk of postoperative mortality than patients without heart failure undergoing surgery in the same specialty (Table 3).
Table 2. The ORs of 90-Day Postoperative Mortality Between Patients With and Without Heart Failure Undergoing Outpatient Surgery.
| Variable | No. of Patients | Crude Mortality, % | OR (95% CI) | |
|---|---|---|---|---|
| Crude | Adjusteda | |||
| Model 1: Heart Failure (Overall) | ||||
| No heart failure | 334 768 | 0.39 | 1 [Reference] | 1 [Reference] |
| Heart failure | 19 353 | 2.00 | 5.20 (4.64-5.82) | 1.95 (1.69-2.44) |
| Model 2: Heart Failure Defined by Systolic Functionb | ||||
| No heart failure | 334 768 | 0.39 | 1 [Reference] | 1 [Reference] |
| Heart failure | ||||
| With preserved LVEF, ≥50% | 11 721 | 1.80 | 4.67 (4.02-5.39) | 1.80 (1.53-2.12) |
| With mildly reduced LVEF, 40%-49% | 3057 | 2.19 | 5.70 (4.44-7.29) | 2.04 (1.51-2.76) |
| With moderately reduced LVEF, 30%-39% | 2356 | 2.21 | 5.73 (4.33-7.59) | 2.20 (1.68-2.89) |
| With severely reduced LVEF, <30% | 1549 | 2.65 | 6.91 (5.04-9.46) | 2.46 (1.76-3.43) |
| Model 3: Heart Failure Defined by Presence of Recent Symptomsc | ||||
| No heart failure | 334 768 | 0.39 | 1 [Reference] | 1 [Reference] |
| Heart failure | ||||
| Asymptomatic | 17 642 | 1.85 | 4.80 (4.24-5.42) | 1.85 (1.60-2.15) |
| Symptomatic | 1711 | 3.57 | 9.39 (7.23-12.20) | 2.76 (2.07-3.70) |
Abbreviations: LVEF, left ventricular ejection fraction; OR, odds ratio.
Multivariable mixed-effects logistic regression model adjusted for sex, age, body mass index, alcohol consumption, comorbidities (hypertension, atrial fibrillation, diabetes, coronary artery disease, stroke, chronic obstructive pulmonary disease, and peripheral vascular disease), preoperative creatinine level, preoperative hematocrit, American Society of Anesthesiologists class and surgical complexity, and Veterans Affairs facility.
The OR compares patients with heart failure with the given LVEF with patients without heart failure. Does not include 678 patients with missing LVEF. P for trend <.001.
Classified per the American College of Surgeons Surgical Risk Calculator and Veterans Affairs Surgical Quality Improvement Program definitions of symptomatic congestive heart failure: the presence of dyspnea, orthopnea, paroxysmal nocturnal dyspnea, increased jugular venous distension, or pulmonary rales within 30 days of surgery.
Table 3. The ORs of 90-Day Postoperative Mortality Between Patients With and Without Heart Failure in Selected Surgical Specialties.
| Surgical Specialty | No. of Patients | Mortality, % | OR (95% CI) | |||
|---|---|---|---|---|---|---|
| Heart Failure | No Heart Failure | Heart Failure | No Heart Failure | Crude | Adjusteda | |
| General | 7262 | 127 022 | 1.68 | 0.39 | 4.40 (3.61-5.38) | 2.05 (1.19-2.54) |
| Vascular | 1741 | 9496 | 3.50 | 1.09 | 3.31 (2.40-4.56) | 2.00 (1.36-2.96) |
| Urology | 4153 | 40 138 | 2.34 | 0.64 | 3.57 (2.82-4.52) | 2.29 (1.71-3.04) |
| Otolaryngology | 868 | 13 300 | 2.53 | 0.45 | 5.74 (3.50-9.40) | 2.30 (1.28-4.16) |
| Orthopedic | 3379 | 105 196 | 1.09 | 0.17 | 6.50 (4.55-9.26) | 2.06 (1.33-3.17) |
| Plastics | 539 | 10 999 | 1.11 | 0.21 | 5.37 (2.18-13.43) | 2.31 (0.76-7.01) |
Abbreviation: OR, odds ratio.
Multivariable mixed-effects logistic regression model adjusted for sex, age, body mass index, alcohol consumption, comorbidities (hypertension, atrial fibrillation, diabetes, coronary artery disease, stroke, chronic obstructive pulmonary disease, and peripheral vascular disease), preoperative creatinine level, preoperative hematocrit, American Society of Anesthesiologists class and surgical complexity, and Veterans Affairs facility.
Patients with heart failure had a 5.65% crude risk of experiencing a postoperative complication within 30 days, and patients without heart failure had a crude risk of 2.65% (Table 4). Heart failure was significantly associated with the risk of developing any postoperative complication (aOR, 1.10; 95% CI, 1.02-1.19) after multivariable adjustment. Heart failure was also associated specifically with 30-day postoperative cardiac arrest (aOR, 1.54; 95% CI, 1.12-2.12) and superficial surgical site infection (aOR, 1.31; 95% CI, 1.10-1.56).
Table 4. The ORs of Selected 30-Day Complication Risks Between Patients With and Without Heart Failure.
| Surgical Specialty | No. of Patients | Risk, % | OR (95% CI) | |||
|---|---|---|---|---|---|---|
| Heart Failure | No Heart Failure | Heart Failure | No Heart Failure | Crude | Adjusteda | |
| Any complicationb | 1093 | 8882 | 5.65 | 2.65 | 2.20 (2.06-2.34) | 1.10 (1.02-1.19) |
| Cardiac arrest | 67 | 231 | 0.35 | 0.07 | 5.03 (3.83-6.61) | 1.54 (1.12-2.12) |
| Myocardial infarction | 32 | 175 | 0.17 | 0.05 | 3.17 (2.17-4.62) | 0.83 (0.55-1.25) |
| Stroke | 30 | 161 | 0.16 | 0.05 | 3.23 (2.18-4.77) | 1.01 (0.65-1.56) |
| Bleed, >4 U within 72 h | 15 | 75 | 0.08 | 0.02 | 3.46 (1.99-6.02) | 1.06 (0.55-2.02) |
| Surgical site infection | ||||||
| Superficial | 181 | 1740 | 0.94 | 0.52 | 1.81 (1.54-2.11) | 1.31 (1.10-1.56) |
| Deep | 32 | 277 | 0.17 | 0.08 | 2.00 (1.39-2.88) | 1.15 (0.76-1.75) |
| Urinary tract infection | 165 | 1415 | 0.85 | 0.42 | 2.02 (1.72-2.38) | 0.94 (0.79-1.13) |
Abbreviation: OR, odds ratio.
Multivariable mixed-effects logistic regression model adjusted for sex, age, body mass index, alcohol consumption, comorbidities (hypertension, atrial fibrillation, diabetes, coronary artery disease, stroke, chronic obstructive pulmonary disease, and peripheral vascular disease), preoperative creatinine level, preoperative hematocrit, American Society of Anesthesiologists class and surgical complexity, and Veterans Affairs facility.
Cardiac arrest, myocardial infarction, other cardiac complication, cerebrovascular accident, stroke, coma, other central nervous system complication, peripheral nerve injury, bleeding, Clostridium difficile colitis, deep vein thrombosis, graft failure, postoperative sepsis, prolonged ileus, failure to wean from ventilator, pneumonia, other respiratory complication, pulmonary embolism, acute renal failure, urinary tract infection, surgical site infection, and wound dehiscence.
Discussion
More than 28 million patients receive ambulatory surgery every year, and these visits are estimated to represent more than half of all operations performed in the United States.30,31 Ambulatory surgery is no longer limited to minor, superficial procedures. As minimally invasive surgical techniques continue to improve, higher-complexity operations will occupy a continually larger percentage of operations in the ambulatory setting, and the number of outpatient operations is likely to continue to increase. Although many studies32,33 characterize the risk of postoperative mortality in the context-specific procedures, studies on overall ambulatory surgery outcomes are lacking, especially in the context of documenting overall mortality. The lack of such data has potentially serious implications for medically complex populations, such as those with heart failure.
The few studies34,35 that have examined postoperative mortality in ambulatory surgery have focused on outcomes in the short term (ie, 24-hour or 7-day mortality) or at readmission and reported almost nonexistent postoperative mortality risk. This finding and that, until recently, no large-scale data existed on the postoperative mortality risk among patients with asymptomatic or preserved ejection fraction heart failure could lead to the misconception that ambulatory surgery is generally safe in most patients with heart failure. The results of our study suggest that this is not the case and that mortality risk may be significantly higher among patients with low-mortality cases.
In this study, patients with heart failure experienced nearly 5 times the crude risk and nearly twice the adjusted odds of 90-day mortality after ambulatory surgery compared with patients without heart failure. Furthermore, this increased mortality risk persisted even in patients with medically managed, asymptomatic, well-compensated heart failure. Although the risk of postoperative mortality increased progressively with reduced systolic function and the presence of symptoms, patients with asymptomatic heart failure and patients with heart failure and preserved ejection fraction still experienced higher crude and adjusted risk.
Although the precise mechanisms underlying the increased postoperative mortality risk associated with heart failure remain unknown, complication rates in this population may provide a clue. In this study, patients with heart failure experienced twice the crude complication rate and a 9% increase in the adjusted odds of complications compared with those without heart failure. Although the overall rates of major complications, such as cardiac arrest, myocardial infarction, or hemorrhage, were low, rates of minor complications, such as surgical site infections, were nonnegligible. Compelling evidence exists that even minor postoperative complications may have substantial effects on postoperative mortality.36
The results of this study invite greater focus on which populations of patients are considered to be fit for ambulatory surgery. In this cohort, nearly a quarter (23.2%) of patients with heart failure were classified as having ASA class 4 disease (severe systemic disease that is a constant threat to life), and 8.8% had active signs or symptoms of heart failure in the 30 days before surgery (although not likely on the day of surgery because this would typically result in a case cancellation). The high prevalence of ASA class 3 and ASA class 4 disease in this cohort among patients with and without heart failure is perhaps not surprising. Procedure costs and insurance coverage have caused a marked shift of surgery out of hospitals and into ambulatory surgical centers.37 This shift has also broadened the acceptability of patients with significant comorbidities as candidates for ambulatory procedures. For example, the Society of Ambulatory Anesthesia in 2012 published a consensus statement extending the indications for ambulatory patients with obstructive sleep apnea over the previously published 2006 ASA guideline.38 Currently, however, no overarching patient selection guideline for ambulatory surgery centers exist. Although some institution-specific regulations exist, the development of a consensus guideline has the potential to improve patient safety and patient outcomes, perhaps in particular among patients with heart failure.39 Additional research on the risks associated with ambulatory surgery is warranted to further improve patient safety.
Limitations
This study has several limitations. First, by the nature of the inclusion criteria, all patients in this study were deemed to be fit for surgery by a surgeon and anesthesiologist. Data on patients who were considered for surgery but did not ultimately undergo surgery and data on patients considered for ambulatory surgery but who ultimately received inpatient surgery were not available. This limitation may have resulted in selection bias regarding the generalizability of this study’s findings. Second, this analysis was not able to compare baseline mortality rates not attributable to surgery because all patients in this study underwent surgery.
Third, as with any observational study, unmeasured confounding factors may exist that, if accounted for, could negate the apparent contribution of heart failure as an independent risk factor for postoperative mortality. E values were calculated as a sensitivity analysis to determine the likelihood that an unmeasured confounder could exist that would negate the observed association between heart failure and postoperative mortality. This possibility seems unlikely given that the range of point estimates for the ORs for known risk factors available in the data extended from 0.97 to 1.88 (eTable 5 in the Supplement). The E values for the 95% CIs closest to the null for the aORs for the association among heart failure, symptoms, and ejection fraction ranged from 2.77 to 3.56 (eTable 4 in the Supplement). An unmeasured confounder would necessarily have an OR that exceeded these values, a possibility seemingly remote because the ORs for all measured known risk factors for postoperative mortality were smaller than the E values given in eTable 4 in the Supplement.
Fourth, the generalizability of this study may be limited given the source of the population that we examined. All participants were veterans, and most were men. However, although the number of women was relatively small, the absolute number of female patients with heart failure included in this study was comparable to that in another major study.40
Conclusions
In this study, among patients undergoing elective, ambulatory surgery, heart failure with or without symptoms was significantly associated with 90-day mortality and 30-day postoperative complications. These data may be helpful in preoperative discussions with patients with heart failure undergoing ambulatory surgery.
eTable 1. VA Surgical Complexity Matrix Examples by Surgical Specialty
eTable 2. Clinical Characteristics of Heart Failure Patients
eTable 3. Frequencies of Surgical Complexity Levels by Left Ventricular Ejection Fraction
eTable 4. E-Values for Heart Failure and 90-Day Post-Operative Mortality with Selected Sub-Populations
eTable 5. Adjusted Odds Ratios for the Independent Association with 90-Day Post-Operative Mortality of Selected Additional Covariates Included in Table 2, Model 3
References
- 1.Lee TH, Marcantonio ER, Mangione CM, et al. Derivation and prospective validation of a simple index for prediction of cardiac risk of major noncardiac surgery. Circulation. 1999;100(10):1043-1049. doi: 10.1161/01.CIR.100.10.1043 [DOI] [PubMed] [Google Scholar]
- 2.Benjamin EJ, Blaha MJ, Chiuve SE, et al. ; American Heart Association Statistics Committee and Stroke Statistics Subcommittee . Heart disease and stroke statistics–2017 update: a report from the American Heart Association. Circulation. 2017;135(10):e146-e603. doi: 10.1161/CIR.0000000000000485 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Hammill BG, Curtis LH, Bennett-Guerrero E, et al. Impact of heart failure on patients undergoing major noncardiac surgery. Anesthesiology. 2008;108(4):559-567. doi: 10.1097/ALN.0b013e31816725ef [DOI] [PubMed] [Google Scholar]
- 4.Hanninen M, McAlister FA, Bakal JA, van Diepen S, Ezekowitz JA. Neither diabetes nor glucose-lowering drugs are associated with mortality after noncardiac surgery in patients with coronary artery disease or heart failure. Can J Cardiol. 2013;29(4):423-428. doi: 10.1016/j.cjca.2012.07.004 [DOI] [PubMed] [Google Scholar]
- 5.Hernandez AF, Whellan DJ, Stroud S, Sun JL, O’Connor CM, Jollis JG. Outcomes in heart failure patients after major noncardiac surgery. J Am Coll Cardiol. 2004;44(7):1446-1453. doi: 10.1016/j.jacc.2004.06.059 [DOI] [PubMed] [Google Scholar]
- 6.van Diepen S, Bakal JA, McAlister FA, Ezekowitz JA. Mortality and readmission of patients with heart failure, atrial fibrillation, or coronary artery disease undergoing noncardiac surgery: an analysis of 38 047 patients. Circulation. 2011;124(3):289-296. doi: 10.1161/CIRCULATIONAHA.110.011130 [DOI] [PubMed] [Google Scholar]
- 7.Bilimoria KY, Liu Y, Paruch JL, et al. Development and evaluation of the universal ACS NSQIP surgical risk calculator: a decision aid and informed consent tool for patients and surgeons. J Am Coll Surg. 2013;217(5):833-42.e1, 3. doi: 10.1016/j.jamcollsurg.2013.07.385 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Vigen R, Maddox TM, Allen LA. Aging of the United States population: impact on heart failure. Curr Heart Fail Rep. 2012;9(4):369-374. doi: 10.1007/s11897-012-0114-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Lerman BJ, Popat RA, Assimes TL, Heidenreich PA, Wren SM. Association of left ventricular ejection fraction and symptoms with mortality after elective noncardiac surgery among patients with heart failure. JAMA. 2019;321(6):572-579. doi: 10.1001/jama.2019.0156 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Khuri SF, Daley J, Henderson W, et al. ; National VA Surgical Quality Improvement Program . The Department of Veterans Affairs’ NSQIP: the first national, validated, outcome-based, risk-adjusted, and peer-controlled program for the measurement and enhancement of the quality of surgical care. Ann Surg. 1998;228(4):491-507. doi: 10.1097/00000658-199810000-00006 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Massarweh NN, Kaji AH, Itani KMF. Practical guide to surgical data sets: Veterans Affairs Surgical Quality Improvement Program (VASQIP). JAMA Surg. 2018;153(8):768-769. doi: 10.1001/jamasurg.2018.0504 [DOI] [PubMed] [Google Scholar]
- 12.Henderson WG, Daley J. Design and statistical methodology of the National Surgical Quality Improvement Program: why is it what it is? Am J Surg. 2009;198(5)(suppl):S19-S27. doi: 10.1016/j.amjsurg.2009.07.025 [DOI] [PubMed] [Google Scholar]
- 13.Patterson OV, Freiberg MS, Skanderson M, J Fodeh S, Brandt CA, DuVall SL. Unlocking echocardiogram measurements for heart disease research through natural language processing. BMC Cardiovasc Disord. 2017;17(1):151. doi: 10.1186/s12872-017-0580-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Garvin JH, DuVall SL, South BR, et al. Automated extraction of ejection fraction for quality measurement using regular expressions in Unstructured Information Management Architecture (UIMA) for heart failure. J Am Med Inform Assoc. 2012;19(5):859-866. doi: 10.1136/amiajnl-2011-000535 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Floyd JS, Blondon M, Moore KP, Boyko EJ, Smith NL. Validation of methods for assessing cardiovascular disease using electronic health data in a cohort of veterans with diabetes. Pharmacoepidemiol Drug Saf. 2016;25(4):467-471. doi: 10.1002/pds.3921 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Borzecki AM, Wong AT, Hickey EC, Ash AS, Berlowitz DR. Identifying hypertension-related comorbidities from administrative data: what’s the optimal approach? Am J Med Qual. 2004;19(5):201-206. doi: 10.1177/106286060401900504 [DOI] [PubMed] [Google Scholar]
- 17.McCormick N, Lacaille D, Bhole V, Avina-Zubieta JA. Validity of heart failure diagnoses in administrative databases: a systematic review and meta-analysis. PLoS One. 2014;9(8):e104519. doi: 10.1371/journal.pone.0104519 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Szeto HC, Coleman RK, Gholami P, Hoffman BB, Goldstein MK. Accuracy of computerized outpatient diagnoses in a Veterans Affairs general medicine clinic. Am J Manag Care. 2002;8(1):37-43. [PubMed] [Google Scholar]
- 19.Centers for Medicare & Medicaid Services Chronic Conditions Data Warehouse: condition categories. Published 2018. https://www.ccwdata.org/web/guest/condition-categories. Accessed April 22, 2018.
- 20.American College of Cardiology. Left ventricular ejection fraction assessment in the outpatient setting. Published 2018. https://www.acc.org/tools-and-practice-support/clinical-toolkits/heart-failure-practice-solutions/left-ventricular-ejection-fraction-lvef-assessment-outpatient-setting. Accessed April 30, 2018.
- 21.Turrentine FE, Sohn MW, Jones RS. Congestive heart failure and noncardiac operations: risk of serious morbidity, readmission, reoperation, and mortality. J Am Coll Surg. 2016;222(6):1220-1229. doi: 10.1016/j.jamcollsurg.2016.02.025 [DOI] [PubMed] [Google Scholar]
- 22.Petzel RA. Surgical Complexity Initiative: Institute of Medicine commentaries. Published 2012. https://nam.edu/wp-content/uploads/2015/06/VSRT-Surgical-Complexity-Initiative.pdf. Accessed April 28, 2018.
- 23.Department of Veterans Affairs Office of Inspector General A review of facility capabilities where veterans received complex surgical care. Published 2011. https://www.va.gov/oig/54/reports/VAOIG-10-02302-225.pdf. Accessed April 28, 2018.
- 24.Maile MD, Engoren MC, Tremper KK, Jewell E, Kheterpal S. Worsening preoperative heart failure is associated with mortality and noncardiac complications, but not myocardial infarction after noncardiac surgery: a retrospective cohort study. Anesth Analg. 2014;119(3):522-532. doi: 10.1213/ANE.0000000000000116 [DOI] [PubMed] [Google Scholar]
- 25.Koo CY, Hyder JA, Wanderer JP, Eikermann M, Ramachandran SK. A meta-analysis of the predictive accuracy of postoperative mortality using the American Society of Anesthesiologists’ physical status classification system. World J Surg. 2015;39(1):88-103. doi: 10.1007/s00268-014-2783-9 [DOI] [PubMed] [Google Scholar]
- 26.Durstenfeld MS, Ogedegbe O, Katz SD, Park H, Blecker S, Mhs SB. Racial and ethnic differences in heart failure readmissions and mortality in a large municipal healthcare system. JACC Heart Fail. 2016;4(11):885-893. doi: 10.1016/j.jchf.2016.05.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.VanderWeele TJ, Ding P. Sensitivity analysis in observational research: introducing the E-value. Ann Intern Med. 2017;167(4):268-274. doi: 10.7326/M16-2607 [DOI] [PubMed] [Google Scholar]
- 28.Mathur MB, Ding P, Riddell CA, VanderWeele TJ. Website and R Package for Computing E-values. Epidemiology. 2018;29(5):e45-e47. doi: 10.1097/EDE.0000000000000864 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Xu-Cai YO, Brotman DJ, Phillips CO, et al. Outcomes of patients with stable heart failure undergoing elective noncardiac surgery. Mayo Clin Proc. 2008;83(3):280-288. doi: 10.4065/83.3.280 [DOI] [PubMed] [Google Scholar]
- 30.Hall MJ, Schwartzman A, Zhang J, Liu X. Ambulatory surgery data from hospitals and ambulatory surgery centers: United States, 2010. Natl Health Stat Report. 2017;(102):1-15. [PubMed] [Google Scholar]
- 31.Owings MF, Kozak LJ. Ambulatory and inpatient procedures in the United States, 1996. Vital Health Stat 13. 1998;(139):1-119. [PubMed] [Google Scholar]
- 32.Bhattacharyya N. Ambulatory sinus and nasal surgery in the United States: demographics and perioperative outcomes. Laryngoscope. 2010;120(3):635-638. doi: 10.1002/lary.20777 [DOI] [PubMed] [Google Scholar]
- 33.Putnam LR, Levy SM, Johnson E, et al. Impact of a 24-hour discharge pathway on outcomes of pediatric appendectomy. Surgery. 2014;156(2):455-461. doi: 10.1016/j.surg.2014.03.030 [DOI] [PubMed] [Google Scholar]
- 34.Fleisher LA, Pasternak LR, Herbert R, Anderson GF. Inpatient hospital admission and death after outpatient surgery in elderly patients: importance of patient and system characteristics and location of care. Arch Surg. 2004;139(1):67-72. doi: 10.1001/archsurg.139.1.67 [DOI] [PubMed] [Google Scholar]
- 35.Vila H Jr, Soto R, Cantor AB, Mackey D. Comparative outcomes analysis of procedures performed in physician offices and ambulatory surgery centers. Arch Surg. 2003;138(9):991-995. doi: 10.1001/archsurg.138.9.991 [DOI] [PubMed] [Google Scholar]
- 36.Khuri SF, Henderson WG, DePalma RG, Mosca C, Healey NA, Kumbhani DJ; Participants in the VA National Surgical Quality Improvement Program . Determinants of long-term survival after major surgery and the adverse effect of postoperative complications. Ann Surg. 2005;242(3):326-341. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Hollenbeck BK, Dunn RL, Suskind AM, Zhang Y, Hollingsworth JM, Birkmeyer JD. Ambulatory surgery centers and outpatient procedure use among Medicare beneficiaries. Med Care. 2014;52(10):926-931. doi: 10.1097/MLR.0000000000000213 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Joshi GP, Ankichetty SP, Gan TJ, Chung F. Society for Ambulatory Anesthesia consensus statement on preoperative selection of adult patients with obstructive sleep apnea scheduled for ambulatory surgery. Anesth Analg. 2012;115(5):1060-1068. doi: 10.1213/ANE.0b013e318269cfd7 [DOI] [PubMed] [Google Scholar]
- 39.Kaiser Permanente KPCO guidelines for determining appropriate ambulatory surgery venue. Published 2012. http://info.kaiserpermanente.org/info_assets/cpp_cod/cod_ambSurg_determination.pdf. Accessed January 16, 2019.
- 40.Aimo A, Vergaro G, Barison A, et al. Sex-related differences in chronic heart failure. Int J Cardiol. 2018;255:145-151. doi: 10.1016/j.ijcard.2017.10.068 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
eTable 1. VA Surgical Complexity Matrix Examples by Surgical Specialty
eTable 2. Clinical Characteristics of Heart Failure Patients
eTable 3. Frequencies of Surgical Complexity Levels by Left Ventricular Ejection Fraction
eTable 4. E-Values for Heart Failure and 90-Day Post-Operative Mortality with Selected Sub-Populations
eTable 5. Adjusted Odds Ratios for the Independent Association with 90-Day Post-Operative Mortality of Selected Additional Covariates Included in Table 2, Model 3