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Abstract

Background:

Bariatric surgery has been shown to significantly reduce cardiovascular risk factors. However, whether surgery can reduce major adverse cardiovascular events (MACE), especially in patients with established cardiovascular disease, remains poorly understood. The present study aims to determine the association between bariatric surgery and MACE among patients with cardiovascular disease and severe obesity.

Methods:

This was a propensity score–matched cohort study using province-wide multiple-linked administrative databases in Ontario, Canada. Patients with previous ischemic heart disease or heart failure who received bariatric surgery were matched on age, sex, heart failure history, and a propensity score to similar controls from a primary care medical record database in a 1:1 ratio. The primary outcome was the incidence of extended MACE (first occurrence of all-cause mortality, myocardial infarction, coronary revascularization, cerebrovascular events, and heart failure hospitalization). Secondary outcome included 3-component MACE (myocardial infarction, ischemic stroke, and all-cause mortality). Outcomes were evaluated through a combination of matching via propensity score and subsequent multivariable adjustment.

Results:

A total of 2638 patients (n=1319 in each group) were included, with a median follow-up time of 4.6 years. The primary outcome occurred in 11.5% (151/1319) of the surgery group and 19.6% (259/1319) of the controls (adjusted hazard ratio [HR], 0.58 [95% CI, 0.48–0.71]; P<0.001). The association was notable for those with heart failure (HR, 0.44 [95% CI, 0.31–0.62]; P<0.001; absolute risk difference, 19.3% [95% CI, 12.0%–26.7%]) and in those with ischemic heart disease (HR, 0.60 [95% CI, 0.48–0.74]; P<0.001; absolute risk difference, 7.5% [95% CI, 4.7%–10.5%]). Surgery was also associated with a lower incidence of the secondary outcome (HR, 0.66 [95% CI, 0.52–0.84]; P=0.001) and cardiovascular mortality (HR, 0.35 [95% CI, 0.15–0.80]; P=0.001).

Conclusions:

Bariatric surgery was associated with a lower incidence of MACE in patients with cardiovascular disease and obesity. These findings require confirmation by a large-scale randomized trial.

Clincal Perspective

What Is New?

This is a propensity-matched retrospective cohort study investigating the association between bariatric surgery and major adverse cardiovascular events in patients with severe obesity and cardiovascular disease.
In this propensity score–matched study of 2638 patients with severe obesity and cardiovascular disease, bariatric surgery was associated with a significantly lower incidence of major adverse cardiovascular events, all-cause mortality, cardiovascular mortality, coronary events, and heart failure hospitalizations.
It adds to the current literature by including a large, matched cohort of patients with heart failure and examining effect modification across important patient strata.

What Are the Clinical Implications?

Bariatric surgery may be an effective intervention for patients with ischemic heart disease or heart failure.
These results necessitate confirmation with a large, randomized trial.

Introduction

Editorial, see p 1481
Obesity is associated with an increase incidence of heart failure (HF), myocardial infarction (MI), stroke, and death.1–3 Weight loss has become a standard recommendation for all patients with cardiovascular disease (CVD) and coexisting obesity; however, randomized evidence to support this recommendation is limited. The largest trial to date investigating whether intentional weight loss reduces cardiovascular morbidity and mortality in overweight individuals with type 2 diabetes did not show a significant reduction in cardiovascular events.4 However, the weight loss observed in this trial was modest, and it is not known whether greater levels of weight loss would lead to clear reductions in recurrent cardiovascular events and deaths. Several studies of overweight and obese patients with CVD suggest an “obesity paradox,” whereby elevated body mass index (BMI) may be associated with lower mortality and cardiovascular events.5,6 However, other studies have described a U-shaped relationship with respect to weight, with severe obesity being associated with increased risk of cardiovascular outcomes.3 Although the relationship between obesity and cardiovascular outcomes is not well delineated, bariatric surgery, in addition to being the most effective weight loss treatment, is also known to resolve other cardiovascular risk factors, including the burden of recurrent CVD in patients with obesity and previous heart disease.7
Randomized clinical trials (RCTs) have revealed that bariatric surgery leads to consistent improvements in diabetes outcomes and cardiovascular risk factors in patients with diabetes and severe obesity.8–10 However, such trials did not evaluate the effect of bariatric surgery on mortality and other major cardiovascular outcomes. Several observational studies have reported on the promising correlation between bariatric surgery and decreased cardiovascular outcomes.11–13 Early studies of patients with severe obesity and type 2 diabetes undergoing bariatric surgery showed lower risks of macrovascular events in the surgery group, but confounding bias may have contributed to these results, and patients in these studies received procedures that are no longer common.12 More recently, retrospective studies of patients with diabetes undergoing sleeve gastrectomy and Roux-en-Y gastric bypass have associated bariatric surgery with significantly lower incidence of incident major cardiovascular events after 8 years.11,13 Nonetheless, the observed effects of bariatric surgery in patients with severe obesity and a history of heart disease remain a major gap in the literature.
This study aimed to examine the outcomes of patients with both CVD and severe obesity undergoing either bariatric surgery or routine clinical care in Ontario, Canada.

Methods

Overview of Study Design

This is a population-based matched cohort study that used linked databases in Ontario. The present study aimed to determine the associations of bariatric surgery with major adverse cardiovascular events (MACE) using 2 similar cohorts of patients with obesity and previous CVD. This study was approved by the Hamilton Integrated Research Ethics Board (No. 4803). The data set from this study is held securely in coded form at ICES. Although data sharing agreements prohibit ICES from making the data set publicly available, access may be granted to those who meet prespecified criteria for confidential access, available at www.ices.on.ca/DAS. The full data set creation plan and underlying analytic code are available from the authors on request, understanding that the computer programs may rely on coding templates or macros that are unique to ICES and are therefore either inaccessible or may require modification. The methods and codes can be made available for reproduction.

Setting

The Ontario Bariatric Network was established in 2009 by the Ontario Ministry of Health and Long-Term Care.13 Through the Ontario Bariatric Network, all patients in Ontario have access to bariatric surgery and are referred mainly by their primary care providers based on the National Institutes of Health criteria14 through a centralized online referral system maintained by the Population Health Research Institute at McMaster University and Hamilton Health Sciences.13 All patients undergo preoperative work and treatment at Bariatric Centers of Excellence. These centers are the only centers sanctioned to perform bariatric surgery in Ontario and undergo an accreditation process. Each Bariatric Centers of Excellence must perform at least 125 procedure cases per year, with each bariatric surgeon performing at least 50 procedures annually. In Ontario, >80% of the bariatric procedures are Roux-en-Y gastric bypasses.14 Sleeve gastrectomy is recommended in specific clinical circumstances: (1) patients with BMI ≥60 kg/m2 as part of a 2-stage duodenal switch, and (2) when Roux-en-Y gastric bypass is contraindicated for medical (eg, inflammatory bowel disease or need for certain medications) or surgical (eg, small bowel disease/adhesions) reasons.14

Study Cohort

The surgery group consisted of all patients who underwent bariatric surgery from January 2010 to December 2016 in Ontario as identified in the Ontario Bariatric Registry. Nonsurgical controls were identified from the EMRALD (Ontario Electronic Medical Record Administrative Linked Database)15; this is a database that covers >500 entire family physician practices and >500 000 patients. This database represents a sample collected through purposeful recruitment of family physician practices with an aim for geographic and demographic representation in Ontario.15
From these records, all patients who were not eligible for bariatric surgery were excluded. The exclusion criteria for bariatric surgery were patients who were not residents of Ontario, age ≥70 years, cancer within 2 years, active substance use, BMI <35 kg/m2, history of accessing palliative care, pregnancy at the time of index date, previous solid organ (lung, liver, or heart) transplant, and severe liver disease with ascites within a year of the index date. Nonsurgical control patients were deemed eligible if they had at least 1 date where the criteria for bariatric surgery could be established (BMI >35 kg/m2 with a comorbidity or BMI ≥40 kg/m2). A history of ischemic heart disease (IHD) was defined as 1 hospital discharge with an IHD diagnostic or procedure code or at least 2 physician claims with an IHD diagnosis code within a 1-year period.16 A history of HF was defined as 1 hospitalization record alone with a HF diagnosis code or at least 2 physician claims with an HF diagnosis code within a 1-year period. The administrative data case definitions for IHD and HF have been validated previously with sensitivities of 77.0% for IHD and 84.8% for HF and specificities >97% for both, respectively.16,17 The specific case definition for IHD was 1 hospital discharge with an IHD diagnostic or procedure code or at least 2 physician claims with an IHD diagnosis code within a 1-year period. The accuracy of BMI data in EMRALD has not been assessed for adults but has been assessed in children, and data completeness at well-child visits and overall data accuracy were >95%.18 Multiple linked databases that combined inpatient and outpatient data common to all patients were then used to derive all outcomes and confounding variables (Table I in the Data Supplement).

Matching Process

Each bariatric patient with a nonsurgical comparator was matched using propensity score methods to reduce the risk of bias attributed to confounding.19,20 The propensity score was developed using all of the demographic, socioeconomic, and clinical variables listed in Table I in the Data Supplement. The variables were selected a priori for their potential to be strongly associated with receipt of bariatric surgery. The propensity score was then created using a generalized logistic model to predict the probability of receiving bariatric surgery. The logit of this score was taken with a caliper of 0.6 to create the propensity score on which we matched. A logit of 0.6 was used because it maximized the number of patients without comprising the match. Sensitivity analyses for this logit size were done using a logit of 0.2 and 0.4. In addition to matching on the propensity score, to ensure balance of potentially important confounders, patients were hard matched on age (±3 years), sex, history of HF, and index date (±3 months). Greedy nearest-neighbor matching was done in a 1:1 fashion sequentially without replacement.21 Of note, 1:3, 1:2, and other match possibilities were attempted, but anything beyond 1:1 decreased the number of patients substantially (>50% from initial). Overall, we elected to focus on a quality match as opposed to more power.

Outcomes

The primary outcome was extended MACE (composite of the first occurrence of all-cause mortality, MI, coronary artery bypass grafting, or percutaneous coronary intervention, stroke, or hospitalization for HF). The main secondary outcome was the composite of MI, stroke, and all-cause mortality. We also evaluated cause-specific mortality as coded from provincial death records. Cause-specific mortality was categorized as cardiovascular or other medical mortality. Last, 30-day surgical outcomes were assessed for safety.

Statistical Analysis

Balance on potential baseline confounders was evaluated using standardized differences with an importance threshold set a priori at 0.10. Standardized differences were used instead of P values because of their insensitivity to sample size.22 Variance ratios were used to assess the distribution of covariates.20 Unadjusted incidence of the primary and secondary outcomes, as well as the absolute risk difference (ARD) and incidence rate differences, were calculated for the entire duration of follow-up for clinically relevant strata. Analyses by strata were done to elucidate any effect modification. These were sought rather than interactions for simplicity to interpretation to minimize type I error and because none of the covariates were exposures that worked synergistically or antagonistically with bariatric surgery. The strata included history of ischemic disease, history of HF, sex, type of bariatric surgery (Roux-en-Y gastric bypass and sleeve gastrectomy), age, and BMI. After propensity score matching, a Cox proportional hazards regression was used to estimate hazard ratios (HRs) for the primary and secondary outcomes on the entire cohort and all subgroups. Patients were followed from the index date to the first occurrence of an outcome event, loss of health insurance coverage, death, or the end of the study period (December 31, 2019). Loss of health insurance coverage and death were used as competing risks for all models, including nonfatal events. Because models were used that accounted for competing risks, Gray’s K-sample test was used as opposed to the log-rank test to assess for differences between cohorts. The results are reported as HRs with the corresponding 95% CIs and associated P values. Three sensitivity analyses were also performed: (1) adjusted analysis using all variables with a standardized difference >0.10,23 (2) adjusted analysis using all variables, and (3) stratified analysis to account for the matched cohort design. Because of matching, each matched pair of patients has an underlying baseline hazard that is similar to each other but different than other matched pairs, and a stratified Cox analysis takes into account this within-pair correlation. All P values are reported to 3 decimal places, and statistical significance was set at α = 0.05. Proportionality of hazards was tested using standard methods. Statistical analysis was performed in SAS (SAS 9.4, SAS Institute Inc, Cary, NC).

Results

Table 1 presents patient demographics, comorbidity status, and health care use characteristics. There were 1700 surgical patients and 3749 eligible nonsurgical patients from January 2010 to December 2016. From these, 1319 surgical patients were matched to nonsurgical controls in a 1:1 ratio (Figure 1). Among these individuals, 548 (21%; 274 in each group) had a history of HF (with or without a history of IHD), and the remainder had a history of IHD. The overall mean age was 56.0 years at baseline (61% female). The mean BMI on the index date was 47.4 kg/m2 (±11.3 kg/m2). Roux-en-Y gastric bypass accounted for 80% of procedures. The nonsurgical group was older and included a greater number of smokers, history of MI, substance abuse, hospitalizations for cardiac reasons, and emergency department visits within 1 year. In contrast, surgical patients were more likely to have been previously hospitalized for any reason, come from urban areas, and reside in higher-income neighborhoods. Regarding the sensitivity analysis based on logit size, using a logit of 0.2 or 0.4 did not substantially change the match results but decreased the number of patients by 10%. The rates of revascularization were not different between groups overall, with 25.7% in the controls and 24.3% in the cases, or within the IHD subgroup, because rates of revascularization within this subgroup were 28.0% of controls and 26.5% of cases, respectively.
Table 1. Baseline Characteristics of Surgical and Matched Nonsurgical Patients
VariableNo surgery (N= 1319)Surgery (N= 1319)Total (N=2638)St-diffVariance ratio
Age at index date±SD, y56.55±7.8555.41±7.4355.98±7.670.150.9
Body mass index at index date±SD, kg/m246.74±13.7948.04±8.0447.39±11.310.120.34
Female, n (%)804 (61.0)804 (61.0)1608 (61.0)01
Income quintile, n (%)
 1353 (26.8)294 (22.3)647 (24.5)0.11.13
 2332 (25.2)296 (22.4)628 (23.8)0.061.08
 3267 (20.2)259 (19.6)526 (19.9)0.021.02
 4213 (16.1)258 (19.6)471 (17.9)0.090.86
 5154 (11.7)212 (16.1)366 (13.9)0.130.76
Neighborhood marginalization index, n (%)
 1 (least marginalized)65 (4.9)79 (6.0)144 (5.5)0.050.83
 2394 (29.9)472 (35.8)866 (32.8)0.130.91
 3603 (45.7)557 (42.2)1160 (44.0)0.071.02
 4 (most marginalized)257 (19.5)211 (16.0)468 (17.7)0.091.17
Rural status, n (%)361 (27.4)235 (17.8)596 (22.6)0.231.36
Immigrant status, n (%)77 (5.8)60 (4.5)137 (5.2)0.061.27
Recent smoking history, n (%)219 (16.6)134 (10.2)353 (13.4)0.191.52
Gastric bypass, n (%) 1049 (79.5)   
Sleeve gastrectomy, n (%) 270 (20.5)   
Diabetes history, n (%)
 Overall diabetes745 (56.5)775 (58.8)1520 (57.6)0.051.01
 Complicated diabetes257 (19.5)296 (22.4)553 (21.0)0.070.9
Cardiac history, n (%)
 Atrial fibrillation80 (6.1)105 (8.0)185 (7.0)0.070.78
 Ischemic heart disease1201 (91.1)1202 (91.1)2403 (91.1)01.01
 Stent/coronary artery bypass graft339 (25.7)321 (24.3)660 (25.0)0.031.04
 Hypertension1061 (80.4)1098 (83.2)2159 (81.8)0.071.13
 Heart failure274 (20.8)274 (20.8)548 (20.8)01
 Valvular disease12 (0.9)13 (1.0)25 (0.9)0.010.92
 Myocardial infarction156 (11.8)108 (8.2)264 (10.0)0.121.39
Other medical history
 Stroke≤20≤20≤200.070.42
 Chronic obstructive pulmonary disease, n (%)165 (12.5)137 (10.4)302 (11.4)0.071.18
 Sleep apnea, n (%)110 (8.3)111 (8.4)221 (8.4)00.99
 Renal disease, n (%)86 (6.5)105 (8.0)191 (7.2)0.060.83
  Dialysis, n (%)10 (0.8)9 (0.7)19 (0.7)0.011.11
 Liver disease, n (%)15 (1.1)8 (0.6)23 (0.9)0.061.86
 Inflammatory bowel disease, n (%)18 (1.4)17 (1.3)35 (1.3)0.011.06
 Previous malignancy, n (%)*12 (0.9)13 (1.0)25 (0.9)0.010.92
 Substance abuse82 (6.2)50 (3.8)132 (5.0)0.111.6
  Alcohol, n (%)40 (3.0)27 (2.0)67 (2.5)0.061.47
  Opioids≤20≤20≤200.062.49
  Cocaine≤20≤20≤200.06-
 Eating disorder≤20≤20≤200.022
 Mood disorder, n (%)54 (4.1)31 (2.4)85 (3.2)0.11.71
  Severe depression≤20≤20≤200.18.95
  Schizophrenia≤20≤20≤200.15-
 Suicide or self-harm≤20≤20≤200.062.66
  Medication≤20≤20≤200.062.66
  Alcohol≤20≤20≤200.04-
  Chemical≤20≤20≤200.040
  Physical trauma≤20≤20≤200.04-
Health care use
 Hospitalization cause, n (%)809 (61.3)887 (67.2)1696 (64.3)0.121.08
  Hematologic, n (%)62 (4.7)67 (5.1)129 (4.9)0.020.93
  Cardiac, n (%)182 (13.8)109 (8.3)294 (11.1)0.181.57
   Digestive, n (%)145 (11.0)168 (12.7)313 (11.9)0.050.88
  Endocrine, n (%)15 (1.1)24 (1.8)39 (1.5)0.060.63
  Infectious≤20≤20≤200.051.99
  Other, n (%)393 (29.8)513 (38.9)906 (34.3)0.190.88
 Hospitalization incidence, n (%)
  0510 (38.7)432 (32.8)942 (35.7)0.121.08
  1–2620 (47.0)658 (49.9)1278 (48.4)0.061
  3+189 (14.3)229 (17.4)418 (15.8)0.080.86
 Emergency department visit, n (%)853 (64.7)765 (58.0)1618 (61.3)0.140.94
 Cardiology specialist assessment, n (%)397 (30.1)432 (32.8)829 (31.4)0.060.96
 Diabetic specialist assessment, n (%)598 (45.3)643 (48.7)827 (31.3)0.070.99
Preventative care/cancer screening, n (%)*
 Colon845 (64.1)821 (62.2)1666 (63.2)0.040.98
 Cervical432 (32.8)397 (30.1)829 (31.4)0.061.05
 Breast472 (35.8)468 (35.5)940 (35.6)0.011
 Flu vaccine583 (44.2)646 (49.0)1229 (46.6)0.100.99
Inpatient or hospital psychiatric assessment, n (%)13 (1.0)9 (0.7)22 (0.8)0.031.44
 Form 1 assessment§≤20≤20≤200.062.19
 Form 3 assessment≤20≤20≤200.06-
 Consultation for involuntary psychiatric treatment≤20≤20≤20--
Data are n (%), mean (SD), or median (interquartile range).
*
Within 5 years.
Within 1 year.
Difference between sample means divided by pooled SD. Values >0.1 are generally considered meaningful.
§
Application by Physician for Psychiatric Assessment. Form 1 allows a doctor to involuntarily hold patients in a psychiatric facility for up to 72 hours to undergo a psychiatric assessment.
Application by Physician for Psychiatric Assessment. Form 3 allows a doctor to involuntarily hold patients in a psychiatric facility for up to 2 weeks to undergo a psychiatric assessment.
Figure 1. CONSORT diagram of cohort creation and identification of eligible patents for inclusion. CONSORT indicates Consolidated Standards of Reporting Trials.
Table 2 and Figure 2 present the association between bariatric surgery and the primary outcome, as well as within subgroups with previous HF or previous IHD. Overall, 410 individuals experienced a primary outcome at a median of 4.5 years of follow-up. Of these, there were 151 events (11.5%) in the surgery group and 259 (19.6%) in the control group. The unadjusted ARD associated with surgery was 8.2% (95% CI, 5.4%–11.0%), and the adjusted HR was 0.58 (95% CI, 0.48–0.71) in favor of the surgery group. In the subgroup of patients with IHD (n=2403), surgery was associated with a 40% lower hazard of primary events. The subgroup of patients with previous HF experienced a 56% lower observed hazard of the primary outcome, with an associated ARD of 19.3%. In terms of the main secondary outcome, 280 patients experienced the secondary outcome, with 107 patients (8.1%) in the surgery group and 173 (13.1%) in the control group. At a median of 4.7 years of follow-up, bariatric surgery was associated with 34% lower hazard of experiencing the secondary outcome (95% CI, 0.52–0.84). In subgroups of patients with ischemic disease and patients with HF, surgery was associated with a 33% (HR, 0.67 [95% CI, 0.52–0.87]) and 60% (HR, 0.40 [95% CI, 0.25–0.63]) lower hazard of the secondary outcome, respectively. The proportionality assumption was met for all outcomes. Censoring for loss of insurance occurred 21 times in our cohort (0.8%), and there was no difference between the groups.
Table 2. Association Between Bariatric Surgery and the Primary/Secondary Outcomes According to Previous Cardiac Disease Status
VariableTotal cohortIschemic heart diseaseHeart failure
Surgery (n=1319)Control (n=1319)Surgery (n=1202)Control (n=1201)Surgery (n=274)Control (n=274)
Primary outcome
 Follow-up, median (interquartile range), y4.65 (3.09–6.28)4.38 (2.83–6.09)4.71 (3.12–6.30)4.42 (2.89–6.15)4.19 (2.75–5.82)3.40 (2.31–5.49)
 Person-years followed6284.005935.175775.865470.711184.481039.83
 Total outcomes, n (%)151 (11.5)259 (19.6)134 (11.2)225 (18.7)47 (17.2%)100 (36.5)
 Outcome per 1000 person-years (95% CI)24.0 (23.9–24.1)43.6 (43.4–43.8)23.2 (23.0–23.3)41.1 (41.0–41.2)39.8 (39.3–40.0)96.2 (95.6–96.7)
 Absolute risk reduction (95% CI)8.2% (5.4%–11.0%)7.5% (4.7%–10.5%)19.3% (12.0%–26.7%)
 Incidence rate difference (95% CI)19.6 (13.1–26.0)17.9 (11.6–24.2)46.4 (37.8–55.0)
 Adjusted hazard ratio (95% CI)*0.58 (0.48–0.71)P<0.0010.60 (0.48–0.74)P<0.0010.44 (0.31–0.62)P<0.001
Secondary outcome
 Follow-up, median (interquartile range), y4.74 (3.18–6.38)4.65 (3.09–6.26)4.83 (3.24–6.41)4.69 (3.12–6.33)4.54 (2.91–6.12)3.99 (2.72–5.75)
 Person-years followed6427.016245.565899.305732.541271.151164.57
 Total outcomes, n (%)107 (8.1)173 (13.1)95 (7.9)153 (12.7)26 (9.5)65 (23.7)
 Outcome per 1000 person-years (95% CI)16.6 (16.5–16.7)27.7 (27.6–27.8)16.1 (16.0–16.2)26.7 (26.6–26.8)20.5 (20.2–2.07)55.8 (55.4–56.2)
 Absolute risk reduction (95% CI)5.0% (2.6%–7.4%)4.8% (2.4%–7.3%)14.2% (8.0%–20.5%)
 Incidence rate difference (95% CI)11.1 (5.86–16.3)10.6 (5.45–15.7)35.4 (28.6–42.2)
 Adjusted hazard ratio (95% CI)*0.66 (0.52–0.84)P=0.0010.67 (0.52–0.87)P=0.0020.40 (0.25–0.63)P<0.001
*
Adjusted for age, body mass index, sex, immigrant status, income, rurality, diabetes status, overall cardiac history, stroke, chronic obstructive pulmonary disease, hypertension, sleep apnea, renal disease, smoking status, previous malignancy, substance abuse, self-harm, mood disorder, cancer screening (colon, breast, cervical) and health care use in previous year (family physician, hospital inpatient, emergency room visit, specialist visit).
Figure 2. Kaplan–Meier curve comparing bariatric surgery group versus nonsurgical control group. A, Overall cohort for the primary outcome. B, Ischemic heart disease patients for the primary outcome. C, Heart failure patients for the primary outcome. D, Overall cohort for the secondary outcome.
Table 3 illustrates the association between bariatric surgery and the primary outcome according to sex and procedure type. The ARD for the primary outcome was larger in male patients at 10.9% (95% CI, 6.0%–15.8%) after surgery. After adjustment, the HR for the primary outcome was not different in male (HR, 0.55 [95% CI, 0.41–0.73]) and female patients (HR, 0.60 [95% CI, 0.45–0.80]). In terms of procedures, a significant lower hazard of reaching the primary outcome was observed in patients who received a Roux-en-Y gastric bypass (HR, 0.61 [95% CI, 0.49–0.77]) and sleeve gastrectomy (HR, 0.47 [95% CI, 0.30–0.71]). There was no significant interaction in the sex or procedure strata.
Table 3. Association Between Bariatric Surgery and the Primary Outcome According to Sex, Procedure Type, Age, and BMI
 ArmNFollow-up, median (IQR), yPerson years followedTotal outcome, No. (%)Outcome/1000 person yearsARD (95% CI)IRD (95% CI)Adjusted HR (95% CI, P value)*Interaction P value
Sex
 MalesSurgery5154.64 (3.13–6.19)2440.0574 (14.3%)30.3 (30.13–0.5)10.9 (6.0–15.8)28.3 (21.1–35.6)0.55 (0.41–0.73)<0.0010.75
Control5154.11 (2.68–5.88)2219.36130 (25.2%)58.6 (58.2–58.9)   
 FemalesSurgery8044.66 (3.09–6.32)3843.9577 (9.6%)20.0 (19.8–20.1)6.4 (3.1–9.8)14.7 (8.90–20.5)0.60 (0.45–0.80)<0.001Ref
Control8044.51 (2.96–6.19)3715.82129 (16.0%)34.7 (34.5–34.9)   
Procedure Type
 Gastric BypassSurgery10494.89 (3.18–6.57)5157.15117 (11.2%)22.7 (22.6–22.8)7.8 (4.7–10.9)18.0 (11.8–24.2)0.61 (0.49–0.77)<0.0010.19
Control10494.70 (2.93–6.30)4888.15199 (19.0%)40.7 (40.5–40.9)   
 Sleeve GastrectomySurgery2703.95 (2.84–5.31)1126.8534 (12.6%)30.2 (29.9–30.5)9.6 (3.2–16.1)27.1 (19.8–34.4)0.47 (0.30–0.71)<0.001Ref
Control2703.72 (2.58–5.16)1047.0360 (22.2%)57.3 (56.9–57.8)   
Age
 ≤49 ySurgery2694.77 (3.41–6.30)1314.9020 (7.43%)15.2 (15.0–15.4)5.2 (0.04–10.3)11.3 (6.22–16.4)0.58 (0.33–1.00)0.050.06
Control2694.72 (3.18–6.22)1280.8034 (12.6%)26.5 (26.2–26.8)   
 50–59 ySurgery6154.84 (3.12–6.56)3015.0465 (10.6%)21.6 (21.4–21.7)7.2 (3.2–11.1)16.9 (10.8–23.0)0.55 (0.41–0.75)<0.0010.61
Control6154.50 (2.83–6.29)2833.26109 (17.7%)38.5 (38.2–38.7)   
 ≥60 ySurgery4354.33 (2.94–5.93)1954.0666 (15.2%)33.8 (33.5–34.0)11.5 (6.0–17.0)29.9 (22.2–37.6)0.59 (0.44–0.80)<0.001Ref
Control4354.04 (2.66–5.71)1821.11116 (26.7%)63.7 (63.3–64.0)   
BMI
 ≤40 kg/m2Surgery1854.29 (2.97–6.28)856.3526 (14.1%)30.4 (30.2–30.7)5.9 (-1.8–13.7)14.9 (8.12–21.7)0.77 (0.46–1.29)0.32Ref
Control1854.17 (2.83–5.99)816.0537 (20.0%)45.3 (45.0–45.5)   
 40–50 kg/m2Surgery6764.66 (3.09–6.19)3200.7676 (11.2%)23.7 (23.5–23.8)8.8 (4.8–12.6)21.3 (14.8–27.8)0.56 (0.42–0.74)<0.0010.13
Control6764.38 (2.79–6.05)2998.67135 (20.0%)45.0 (44.8–45.1)   
 ≥50 kg/m2Surgery4584.76 (3.21–6.48)2226.8949 (10.7%)22.0 (21.8–22.3)8.3 (3.6–12.9)19.0 (12.8–25.2)0.56 (0.39–0.79)0.0010.19
Control4584.65 (2.95–6.22)2120.4587 (19.0%)41.0 (40.8–41.2)   
ARR indicates absolute risk reduction; BMI, body mass index; CI, confidence interval; HR, hazard ratio; IQR, interquartile range; and IRD, incidence rate difference.
*
Adjusted for age, BMI, sex, immigrant status, income, rurality, diabetes status, overall cardiac history, stroke, chronic obstructive pulmonary disease, hypertension, sleep apnea, renal disease, smoking status, previous malignancy, substance abuse, self-harm, mood disorder, cancer screening (colon, breast, cervical), and healthcare utilization in previous year (family physician, hospital inpatient, emergency room visit, specialist visit).
Table 3 also demonstrates the association between bariatric surgery and the primary outcome stratified by age and BMI ranges. The lower ARD of surgery was strongest in the group ≥60 years of age with an ARD of 11.5% (95% CI, 6.0%–17.0%). Specifically, patients who were ≥60 years of age experienced a 41% lower hazard of the primary outcome after surgery. In terms of BMI, the association of bariatric surgery with MACE was not different among those with BMI 40 to 50 kg/m2 versus BMI >50 kg/m2 with ARD of 8.8% (95% CI, 4.8%–12.6%) and 8.3% (95% CI, 3.6%–12.9%), respectively. Surgery was not associated with a significantly lower incidence of experiencing the primary outcome in those with BMI <40 kg/m2. However, the direction of the observed incidence was not different from the BMI ≥40 kg/m2, and the number of patients in this group was small (n=185 per group). There was no significant interaction within the age or BMI strata.
Table 4 presents the association between bariatric surgery and cause-specific mortality, as well as specific cardiovascular events at a median of 4.5 years in the entire cohort and the IHD and HF subgroups. Bariatric surgery was associated with 65% lower hazards of cardiovascular mortality (HR, 0.35 [95% CI, 0.15–0.80]) and 44% lower hazard for other mortality (HR, 0.56 [95% CI, 0.36–0.88]). These observed lower mortality was seen in both strata of cardiac disease. In the overall cohort, surgery was associated with lower hazards of MI, coronary artery bypass grafting or percutaneous coronary intervention, and HF hospitalization. In the subgroup of HF patients, lower hazards of MI and HF were seen after surgery.
Table 4. Association Between Bariatric Surgery and Cause-Specific Mortality
VariableTotal cohortIschemic heart diseaseHeart failure
Adjusted hazard ratio* (95% CI)P valueAdjusted hazard ratio* (95% CI)P valueAdjusted hazard ratio* (95% CI)P value
All-cause mortality0.50 (0.34–0.74)<0.0010.44 (0.28–0.68)<0.0010.43 (0.24–0.78)0.006
Cardiovascular mortality0.35 (0.15–0.80)0.010.30 (0.11–0.79)0.020.31 (0.10–0.94)0.04
Other mortality0.56 (0.36–0.88)0.010.50 (0.30–0.81)0.010.50 (0.25–1.02)0.06
Coronary artery events0.67 (0.49–0.92)0.010.64 (0.46–0.89)0.0080.66 (0.34–1.28)0.22
Myocardial infarction0.63 (0.42–0.96)0.030.63 (0.41–0.96)0.030.39 (0.15–1.02)0.05
Stent/coronary artery bypass grafting0.70 (0.51–0.96)0.030.66 (0.47–0.91)0.010.69 (0.35–1.34)0.27
Cerebrovascular events0.98 (0.58–1.66)0.930.96 (0.55–1.69)0.890.48 (0.16–1.46)0.20
Heart failure hospitalization0.37 (0.25–0.54)<0.0010.38 (0.25–0.58)<0.0010.33 (0.20–0.53)<0.001
*
Adjusted for age, body mass index, sex, immigrant status, income, rurality, diabetes status, overall cardiac history, stroke, chronic obstructive pulmonary disease, hypertension, sleep apnea, renal disease, smoking status, previous malignancy, substance abuse, self-harm, mood disorder, cancer screening (colon, breast, cervical), and health care use in the previous year (family physician, hospital inpatient, emergency room visit, specialist visit).
Surgical safety was assessed in this cohort. The overall 30-day complication rate was 7.7% (95% CI, 6.3%–9.3%), and the overall 30-day mortality rate was 0.15% (95% CI, 0.02%–0.50%). The median length of stay after surgery was 3 days (interquartile range, 2–7 days), and 3.5% (95% CI, 2.5%–4.6%) of patients required an intensive care unit stay. There were 6 MIs (0.45% [95% CI, 0.16%–0.98%]) and 5 reoperations (0.38% [95% CI, 0.12%–0.88%]).

Discussion

In this population-based matched cohort study of 2638 patients with CVD and severe obesity, bariatric surgery was associated with a significantly lower ARD in the primary outcome of all-cause mortality, coronary artery events, coronary revascularization, cerebrovascular events, or HF. In addition, this observed lower incidence was seen in subgroups of patients with ischemic disease and HF, with the latter group showing a larger associated lowered incidence of MACE. Bariatric surgery was also associated with lower incidences of the individual components of the primary outcome, except for cerebrovascular events. This analysis addresses a major gap in the literature by examining the association between bariatric and major adverse CVD outcomes.
The results of the present study are mostly consistent with previous studies reporting the associations of bariatric surgery with major adverse cardiovascular outcomes. Aminian et al13 conducted a cohort study of 2287 patients with diabetes undergoing bariatric surgery matched to 11 435 controls. In this study, bariatric surgery was associated with a 38% lower incidence of 3-component MACE.13 This is in agreement with the present study, because similarly lower observed incidences of MACE, coronary events, coronary artery bypass grafting, and HF hospitalization are reported. The present study is also similar to the results of the Swedish nationwide cohort study by Näslund et al,24 which matched 509 severely obese patients with history of previous MI undergoing bariatric surgery to 509 control patients with MI. Their results align with the present study, because the hazard of MACE, mortality, and new-onset HF was significantly lower in the bariatric surgery group at 8 years of follow-up. Similar to Näslund et al,24 the present study did not show a protective effect against stroke, although the incidence for stroke was low (2.1%) because of the 5-year follow-up, the largely female study cohort, and younger age. Further follow-up time is needed to evaluate whether an association between bariatric surgery and stroke risk is present. Other cohort studies including the Swedish Obese Subjects study have also suggested that the weight loss caused by bariatric surgery is associated with a lower risk of HF.25–27 The present study agrees with the previously elucidated associations and demonstrates a pronounced associated lower ARD for those with heart disease, which had not been shown previously.8,11–13 Conversely, in a study by Pirlet et al,28 there was significantly lower incidence of MACE in the surgery group in CVD patients at median follow-up of 8.9 years, albeit with no significant difference in all-cause death or cardiovascular death. However, the difference in all-cause mortality was only of borderline statistical significance (HR, 0.58 [95% CI, 0.33–1.01]; P=0.056) and may have been underpowered (n=232) to detect a significant difference. The present study also has an early divergence of the cumulative incidence curves between the groups for the primary outcome. However, shapes of survival curves are difficult to interpret given the modest number of events at any time point in any study. In the present study, the mortality curves appeared to diverge early, whereas in the study by Näslund et al24 of 1018 people and 279 events, the curves diverged after 4 to 5 months. The shapes of the curves are likely less reliable than the overall results, and emphasis should be not be placed in either study.
Our patient population was at high risk of recurrent CVD events and had a risk profile that is not different from what would be expected in nonseverely obese cohorts. At a median follow-up of 4.6 years, incidences of the primary and secondary outcomes in the control group were 19.6% and 13.1%, respectively. Similarly, in the REACH registry (Reduction of Atherothrombosis for Continued Health Registry; N=45 227; 28.4% of whom were obese), an observational cohort of patients with previous cardiovascular ischemic events or CVD risk factors, the rate of cardiovascular death, MI, and stroke among patients with previous CVD was 12.2% (95% CI, 11.4%–12.9%), whereas that of the composite of cardiovascular death, MI, stroke, and cardiovascular hospitalization was 31.1% (95% CI, 29.8%–32.4%) at 4 years.29
The associations demonstrated in this and previous studies may act through multiple mechanisms. Well-controlled cardiovascular risk factors, such as hypertension and diabetes, are certainly potential mechanisms, but weight loss in and of itself may also contribute greatly. Individuals with obesity experience a chronic inflammatory state that results in endothelial dysfunction and may increase the risk of atherosclerosis.2,30,31 Bariatric surgery has been associated with reductions in C-reactive protein concentrations, a marker of atherothrombotic risk, alongside increases in the anti-inflammatory mediator adiponectin.32–34 Furthermore, obesity can increase the preload, afterload, and stroke volume for the left ventricle, increasing left ventricular wall stress.35 This factor, alongside increases in hormones including adipokines, such as leptin, which drive ventricular hypertrophy and increase circulating volume within the heart, result in ventricular dilation and compensatory left ventricular hypertrophy.35,36 There is also a beneficial effect of surgery on cardiac structure and function including both regression of left ventricular hypertrophy and improved diastolic function.7,37,38 Bariatric surgery reduces the left ventricular stroke workload, decreases systolic blood pressure, and reverses metabolic dysfunction, which may result in cardiac reverse remodeling, including improvements in cardiac structure and function.38–40 Overall, although the obesity paradox exists and is not solved by this study, weight loss may only be part of the mechanism through which bariatric surgery may affect CVD.
The present study provides strong evidence regarding the association between bariatric surgery and lower MACE among patients with heart disease and obesity. While not an RCT, it suggests a potential benefit from surgery in this high-risk population, although the potential benefit reported in this study is likely overestimated because of the observational design of this study. To this point, the use of surgery has been limited in patients with CVD out of concern for perioperative risk, but previous studies have shown excellent safety, even in those awaiting heart transplant.41 The cohort of the present study also compared favorably to previously published data for Ontario.42 Accordingly, consideration should be given to surgery as a treatment option in patients with CVD and obesity, especially when no further treatment options exist. In addition, in certain groups with very high event rates despite optimal care (eg, those with HF, older populations, and males), the potential for benefit is high, although this benefit requires confirmation with an RCT. It is important to note that even for groups with no significant difference in outcomes in this study, these effects should be properly contextualized. Although the association within BMI <40 kg/m2 was not statistically significant, this may be because of the small sample size and lower event rate. Compared with the other BMI subgroups, the apparent effect size in this subgroup was not statistically heterogeneous relative to the overall results, and so care should be taken in interpreting underpowered subgroups on their own without reference to the overall results. Some caution should be noted as safety outcomes in this study are in the context of a high-volume Bariatric Centers of Excellence surgical care system, and these complex CVD patients should be referred to experienced centers for best results. Although this study does show tremendous promise for bariatric surgery as an important adjunct treatment, future research should be aimed at a large RCT to confirm the results of this study and establish the benefits and risks of surgery in this important patient population.
The present study should be interpreted with the understanding of several important limitations. There was no access to patient medication records, diabetes laboratory test results, or assessments of their left ventricular function, which would have been helpful to include in the adjustments, although all relevant hard clinical outcomes for adjustment are included. We also had no reliable follow-up data on weight loss to establish a dose-response relationship. Because EMRALD is EMR-based, weights are recorded unsystematically during the course of routine primary care, making such analyses difficult. Similarly, for the bariatric patients, many do not return to clinic but rather complete follow-up with their family physician. Thus, subsequent weight data are limited in the bariatric registry. There are multiple randomized studies that show weight differences over time in similar clinical cohorts with expected weight loss of 20% to 30% total body weight in the surgery group and 4% to 5% in the nonsurgical group. We would expect to have similar outcomes in this cohort. Secondly, although every effort was made to extensively match and adjust for potential confounders, there were some differences in the baseline patient characteristics between the surgical and nonsurgical patients, and unmeasured confounding bias could not be ruled out entirely. Furthermore, patients who received surgery may be more likely to comply with challenging postoperative lifestyle changes, and this could lead to a potential healthy user bias.43 To account for potential confounding on the basis of healthy user bias, multiple preventative health behaviors (eg, cancer screening and flu shot) were included, and these were relatively balanced between the groups. In addition, nonreferral for surgery is multifactorial, and only a small fraction of patients who are eligible actually are referred. These may be not related to patients healthy-user bias but rather a lack of knowledge and negative perception by either the patient or their primary care physician.44,45 Ultimately, the present study does not provide data on whether patients were counseled for bariatric surgery, although all patients within the present study had access to surgery and sought other preventative health measures at rates that are not different. Immortal time bias is another consideration for comparative observational studies. However, by design, no follow-up time was misattributed as treatment time and there was no immortal time. Last, whereas all surgery patients in this study would be clinically eligible to be placed in the primary care database used to determine the control population, this database is not population-based but rather was selected to represent a reasonable extent of practices in the province of Ontario. To help further maximize the comparability of the surgical and nonsurgical cohorts, individual and neighborhood demographic characteristics, such as immigration status, income quintile, and marginalization index, and prior health service use were used in the matching process. Despite this, some residual confounding by geography or service access could remain.

Conclusions

This study demonstrated that bariatric surgery was associated with a significant lower incidence of MACE in patients with CVD and severe obesity. These observed results apply to both patients with IHD and HF. This study provides novel information and requires confirmation by a large-scale RCT, because effects of observational studies can be overestimated.

Acknowledgments

This study was supported by the Ontario Bariatric Registry and ICES, which is funded by an annual grant from the MOHLTC (Ontario Ministry of Health and Long-Term Care). Parts of this material are based on data and information compiled and provided by the Ontario MOHLTC; Cancer Care Ontario; Immigration, Refugees and Citizenship Canada; the Ontario Registrar General (the original source of which is Service Ontario), and the Canadian Institute for Health Information. The analyses, conclusions, opinions and statements expressed herein are solely those of the authors and do not reflect those of the funding or data sources; no endorsement is intended or should be inferred.

Supplemental Material

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Circulation
Pages: 1468 - 1480
PubMed: 33813836

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History

Received: 24 October 2020
Accepted: 26 January 2021
Published online: 5 April 2021
Published in print: 13 April 2021

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Keywords

  1. bariatric surgery
  2. metabolic surgery
  3. population health

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Affiliations

Aristithes G. Doumouras, MD, MPH https://orcid.org/0000-0002-0543-3177
Division of General Surgery (A.G.D., Y.L., D.H., M.A.), McMaster University, Hamilton, Ontario, Canada.
ICES, Toronto, Ontario, Canada (A.G.D., J.M.P., B.S., D.H., M.A.).
Department of Medicine (J.A.W., S.Y.), McMaster University, Hamilton, Ontario, Canada.
Population Health Research Institute, Hamilton Health Sciences and McMaster University, Ontario, Canada (J.A.W., L.T., S.Y.).
J. Michael Paterson, MSc
Department of Family Medicine (J.M.P.), McMaster University, Hamilton, Ontario, Canada.
ICES, Toronto, Ontario, Canada (A.G.D., J.M.P., B.S., D.H., M.A.).
Institute of Health Policy, Management, and Evaluation, University of Toronto, Ontario, Canada. (J.M.P.).
Yung Lee, MD
Division of General Surgery (A.G.D., Y.L., D.H., M.A.), McMaster University, Hamilton, Ontario, Canada.
Branavan Sivapathasundaram, MPH
ICES, Toronto, Ontario, Canada (A.G.D., J.M.P., B.S., D.H., M.A.).
Jean-Eric Tarride, PhD
Department of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences (J.-E.T., L.T.), McMaster University, Hamilton, Ontario, Canada.
Center for Health Economics and Policy Analysis (J.-E.T.), McMaster University, Hamilton, Ontario, Canada.
Programs for Assessment of Technology in Health, The Research Institute of St Joe’s Hamilton, St Joseph’s Healthcare Hamilton, Ontario, Canada (J.-E.T.).
Lehana Thabane, PhD
Department of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences (J.-E.T., L.T.), McMaster University, Hamilton, Ontario, Canada.
Population Health Research Institute, Hamilton Health Sciences and McMaster University, Ontario, Canada (J.A.W., L.T., S.Y.).
Division of General Surgery (A.G.D., Y.L., D.H., M.A.), McMaster University, Hamilton, Ontario, Canada.
ICES, Toronto, Ontario, Canada (A.G.D., J.M.P., B.S., D.H., M.A.).
Salim Yusuf, DPhil
Department of Medicine (J.A.W., S.Y.), McMaster University, Hamilton, Ontario, Canada.
Population Health Research Institute, Hamilton Health Sciences and McMaster University, Ontario, Canada (J.A.W., L.T., S.Y.).
Mehran Anvari, MD, PhD [email protected]
Division of General Surgery (A.G.D., Y.L., D.H., M.A.), McMaster University, Hamilton, Ontario, Canada.
ICES, Toronto, Ontario, Canada (A.G.D., J.M.P., B.S., D.H., M.A.).

Notes

Sources of Funding, see page 1478
The Data Supplement, podcast, and transcript are available with this article at Supplemental Material.
Mehran Anvari, MD, PhD, Division of General Surgery, St Joseph’s Healthcare, 50 Charlton Avenue East, Hamilton, Ontario, Canada L8N 4A6. Email [email protected]

Disclosures

Disclosures All authors have completed the International Committee of Medical Journal Editors uniform disclosure form and declare: no support from any organisation for the submitted work, no financial relationships with any organisations that might have an interest in the submitted work in the previous 3 years, and no other relationships or activities that could appear to have influenced the submitted work.

Sources of Funding

This study was funded by the Ontario Bariatric Network (public) research grant. There was no private/industry funding involved in this research. The funding source was not involved in the study design, collection, analysis, interpretation of data, nor writing of the report. All authors were independent from funders and had full access to all of the data (including statistical reports and tables) and can take responsibility for the integrity of the data and the accuracy of the data analysis.

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  1. Relationship between Body Adiposity Indices and Reversal of Metabolically Unhealthy Obesity 6 Months after Roux-en-Y Gastric Bypass, Metabolites, 14, 9, (502), (2024).https://doi.org/10.3390/metabo14090502
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  2. Bariatric Surgery in Patients with Previous Cardiac Revascularization: Review of Literature, Journal of Clinical Medicine, 13, 16, (4779), (2024).https://doi.org/10.3390/jcm13164779
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  3. Clinical outcomes and adverse events of bariatric surgery in adults with severe obesity in Scotland: the SCOTS observational cohort study, Health Technology Assessment, (1-115), (2024).https://doi.org/10.3310/UNAW6331
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  5. Trends and Outcomes Associated With Bariatric Surgery and Pharmacotherapies With Weight Loss Effects Among Patients With Heart Failure and Obesity, Circulation: Heart Failure, 17, 2, (e010453), (2024)./doi/10.1161/CIRCHEARTFAILURE.122.010453
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  6. Impact of metabolic bariatric surgery on outcomes and the 10-year risk of major adverse cardiovascular events during a 7-year period: a retrospective cohort study, International Journal of Surgery, 110, 9, (5563-5573), (2024).https://doi.org/10.1097/JS9.0000000000001631
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  8. Association between overweight and obesity with coronary artery bypass graft failure: an individual patient data analysis of clinical trials, European Journal of Cardio-Thoracic Surgery, 65, 6, (2024).https://doi.org/10.1093/ejcts/ezae221
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  9. Primary prevention of cardiovascular disease in women, Climacteric, 27, 1, (104-112), (2024).https://doi.org/10.1080/13697137.2023.2282685
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  10. Contemporary pharmacological treatment and management of heart failure, Nature Reviews Cardiology, 21, 8, (545-555), (2024).https://doi.org/10.1038/s41569-024-00997-0
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