Structured Abstract
Objective:
To assess rates of surgical complications and postoperative readmission in diabetic patients with and without active perioperative prescriptions for GLP-1 RA medications.
Background:
With the rapid growth of glucagon-like peptide-1 receptor agonist (GLP-1 RA) use in the United States, it is important to understand the potential effect of these drugs on surgical outcomes broadly.
Methods:
In this retrospective, observational cohort analysis, patients with a diagnosis of type 1 or type 2 diabetes undergoing a surgical procedure at a multicenter quaternary-care healthcare system between February 2020 to July 2023 were included. Propensity score matching was performed between procedures in patients with and without an active GLP-1 RA prescription. The primary outcome was 30-day readmission, and secondary outcomes were documented dehiscence, infection, hematoma, and bleeding within 180 days after surgery.
Results:
Among 74,425 surgical procedures in 21,772 patients included in the analysis, 27.2% were performed in the setting of an active GLP-1 RA prescription. 35,020 procedures in 13,129 patients (48.0% men, 52.0% women; median [IQR] age, 67 [57, 75]) were propensity score matched. After matching, the active GLP-1 RA prescription group had a significantly reduced risk of 30-day readmission (RR, 0.883; 95% CI, 0.789-0.987; p=0.028; NNT, 219; 95% CI, 191-257), postoperative wound dehiscence (RR, 0.711; 95% CI, 0.577-0.877; p=0.001; NNT, 266; 95% CI, 202-391), and postoperative hematoma (RR, 0.440; 95% CI, 0.216-0.894; p=0.023; NNT, 1786; 95% CI, 652-2416). No significant differences were seen in rates of infection and bleeding.
Conclusions:
An active perioperative GLP-1 RA prescription in patients with diabetes was associated with significant reductions in risk-adjusted readmission, wound dehiscence, and hematoma, and no difference in infection and bleeding rates. Further study is warranted to elucidate any causal association.
Introduction
Diabetes and obesity significantly contribute to poor health outcomes in the United States and increasingly worldwide. More than 34 million people in the US—greater than 10% of the population—have diabetes1. Over 70% of adults in the US are overweight and further, approximately 40% of the population is obese2. GLP-1 receptor agonist (GLP-1 RA) drugs have shown significant efficacy in improving glycemic control and reducing cardiovascular mortality in patients with type 2 diabetes mellitus (T2DM)3–6. Clinically significant weight loss is also commonly seen with GLP-1 RA-based therapies7–10. In 2014, the U.S. Food and Drug Administration approved liraglutide as the first GLP-1 RA medication for the treatment of obesity in the absence of T2DM11. Since then, many other GLP-1 RA drugs have been approved for the treatment of obesity and diabetes, leading to a rapid increase in patients taking GLP-1 RA medications7,12–14. Between 2021 to 2023, the number of monthly prescription fills for semaglutide increased by 442%, reaching 2.6 million prescriptions filled at retail pharmacies by December 202315.
Despite their increasing prevalence, there are a paucity of studies examining the impact these medications have on surgical outcomes16. The limited existing studies exploring GLP-1 RA use by surgical patients have focused mainly on anesthesia considerations, with concern that decreased gastric motility seen in patients taking GLP-1 RA medications could increase the risk of aspiration events during general anesthesia17–20. Current perioperative guidelines by the American Society of Anesthesiologists recommend holding GLP-1 RA medications on the day of surgery (if taken daily) or the week before surgery (if taken weekly) to reduce aspiration risk during general anesthesia and deep sedation21–23.
However, no previous studies have examined the effect of GLP-1 RA medications on surgical outcomes including readmission, surgical-site infection, bleeding, and wound breakdown after surgery. The only surgical studies examining GLP-1 RA medications in the perioperative period have specifically investigated their impact on postoperative glycemic control and cardiac function after coronary artery bypass grafting. These studies found improved postoperative glycemic control and better preservation of myocardial function after cardiac surgery when a GLP-1 RA drug was given preoperatively24–25. Despite these promising early results from cardiac surgery patients, the effects of preoperative GLP-1 RA treatment on complications after all surgical procedures remains unknown.
Prescriptions for all GLP-1 medications have increased 40-fold between 2018 to 2023; according to a study by Epic Research, about 1.7% of the American population was prescribed semaglutide in 202326. As we continue to see a rapid increase in the number of patients on GLP-1 RA medications presenting for surgery, it becomes imperative to understand the specific risks and/or benefits of these medications. Herein, we report on an analysis of diabetic patients undergoing surgery at a quaternary care hospital system in the nation’s largest city. Patients who had an active prescription for GLP-1 RA medications in addition to standard diabetic medical management were compared to patients who did not have an active GLP-1 RA medication prescription as part of their diabetic management at the time of surgery.
Methods
This study was approved by the Weill Cornell Medicine and the Columbia University Irving Medical Center Institutional Review Boards with waivers of patient consent for research of existing records. This retrospective cohort study included adult patients with diabetes who had a surgical procedure between February 2020 and July 2023 at Weill Cornell Medical Center or Columbia University Irving Medical Center with at least 180 days of follow up. All reporting followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines27.
Eligible procedures were defined by the American Medical Association (AMA) Current Procedural Terminology (CPT®) codes within the range for all surgical procedures (10004-69990) with subsequent filtering of relevant codes by researchers. As this study focused on outcomes after surgery, codes for fine needle biopsy aspirations (10004-10021), casting/strapping procedures (29000-29799), and venipuncture (36415) were not included. Additionally, procedures of the eyes and ears (65091-69979) were excluded from analysis, due to the immune privilege of the eyes and ears, specialized nature of procedures on these functional organs, and the relatively low complication rates associated with these surgical procedures.
Data Extraction
Inpatient and outpatient information were extracted from the electronic health record (EHR) of the health care system (Epic Systems Corporation, Madison, WI). Demographic information, co-morbid conditions, preoperative hemoglobin A1C, and active prescriptions at the time of surgery were obtained from patients’ charts. We included only surgeries with complete patient demographic and comorbidity information and follow-up longer than 180 days after hospital discharge. All other data had < 10% missing, so no imputation was done.
GLP-1 RA Exposure
Active GLP-1 RA use was defined as a prescription for a GLP-1 RA drug started or ordered before the date of the surgery, with an end date after the date of surgery. If there was no end date, the prescription was presumed to be active at the time of surgery. Patients with no previous prescription for a GLP-1 RA, a prescription which had been discontinued before the surgical encounter date, or a prescription which was only started after the surgery date were considered unexposed.
Study Outcomes
The primary outcome of interest was readmission to the hospital within 30 days of discharge from the hospital encounter during which the index surgery took place. Secondary outcomes were wound dehiscence, wound infection, hematoma, and bleeding within 180 days of the index surgery. All patients were followed for at least 180 days after hospital discharge. These postoperative outcomes were identified by ICD-10 diagnosis codes assigned within 180 days of the surgery (Table, Supplemental Digital Content 1).
Statistical Analysis
R statistical software version 4.0.5 (R Foundation for Statistical Computing, Vienna, Austria) was used for statistical analysis. One-to-one propensity score matching was performed on pairs of surgical encounters with active GLP-1 RA use and no active GLP-1 RA use by nearest-neighbor matching with a caliper width of 0.2 SD of the log odds of the estimated propensity score. Procedures were matched based on patient demographic information, comorbidities, concurrent diabetic pharmacotherapy at the time of surgery, open or closed surgical procedure, and organ system of the surgery. Covariate balance was evaluated using the standard mean difference before and after propensity score matching. Values less than 0.10 were considered adequately balanced28.
Generalized estimating equations (GEE) were used to analyze readmission and complication outcomes in the matched cohort. The GEE model accounted for within-cluster correlation (in this case, correlation within matched pairs derived from the propensity score matching process). An exchangeable correlation structure was used to model this within-cluster correlation assumption. Statistical significance was assessed using Wald tests.
Model coefficients from the GEE analysis were exponentiated to obtain the adjusted odds ratio, which was used to approximate the adjusted relative risk ratio, due to sufficiently rare outcomes of interest (<10% prevalence). Numbers needed to treat were calculated as the inverse of the absolute risk reduction.
Sensitivity Analyses
To assess the robustness of our findings, multiple sensitivity analyses were performed. Subgroup analyses were performed in open and closed surgical procedures. Propensity score matching was performed within each subgroup, with outcomes between GLP-1 RA exposed and unexposed analyzed with chi-squared tests and GEE models. Additional subgroup analyses were performed for body systems which had greater than 10,000 procedures represented in the overall cohort—in this cohort, this included procedures of the integumentary (CPT codes 10021-19499), cardiovascular (CPT codes 33000-37799), gastrointestinal (CPT codes 40000-49999), and urinary (CPT codes 50000-53899) body systems.
To determine the sensitivity of the results to the propensity score matching method, an additional sensitivity analysis was performed with inverse probability weighting of the final cohort. A weighted model was created by assigning weights to observations based on their propensity scores. Odds ratios were calculated for primary and secondary outcomes by generalized linear models.
Results
We initially identified 88,540 surgical procedures performed between February 2020 to July 2023 in 28,479 diabetic patients. The full and final cohort included 74,425 surgical procedures in 21,772 patients (50.1% men and 49.9% women; median [IQR] age, 67 [57, 75]) who met all inclusion criteria and no exclusion criteria, of which 20,253 procedures (27.2%) were performed in patients with an active GLP-1 RA prescription. The propensity score-matched cohort included 35,020 surgical procedures in 13,129 patients (48.0% men, 52.0% women; median [IQR] age, 65 [55, 72]). The flow diagram of patients in the propensity score-matched cohorts is shown in Figure 1. The propensity score-matched cohort had a median [IQR] BMI of 30.12 kg/m2 [26.31, 35.02] and hemoglobin A1C of 6.80 [6.10, 7.90].
Figure 1:
Flow diagram of patients in the propensity score-matched cohorts
a Exclusion criteria were not mutually exclusive
Patient demographics, comorbid conditions, preoperative A1C, and diabetic pharmacotherapy at the time of surgery before and after propensity score matching are shown in Table 1. Categorization of included procedures is shown in Table 2, and the most frequent procedural codes of each body system, by study group, are shown in Supplemental Digital Content 2. After propensity score matching, the GLP-1 RA group had lower representation of cardiovascular procedures, but there were no significant differences for all other types of procedures between the two comparison cohorts. Differences in age, BMI, Hgb A1C, and rates of hypertension, CKD, and HLD persisted before and after matching, but standard mean differences below 0.10 for every covariate confirmed good balance between the two groups (see Table, Supplemental Digital Content 3). A Love plot demonstrated covariate balance in the entire cohort (unadjusted) and the propensity-score matched cohort (adjusted) (see Figure, Supplemental Digital Content 4).
Table 1:
Descriptive Statistics for Preoperative Demographics, Comorbidities, and Diabetic Pharmacotherapy Before and After Propensity Score Matching
| Variable | Entire cohort | Propensity Score-Matched Cohort | ||||
|---|---|---|---|---|---|---|
| No Active GLP-1 RA Use | Active GLP-1 RA Use | p-value | No Active GLP-1 RA Use | Active GLP-1 RA Use | p-value | |
| Total procedures (n) | 54172 | 20253 | 17510 | 17510 | ||
| Demographics | ||||||
| Age at surgery (median [IQR]) | 68.00 [58.00, 76.00] | 64.00 [55.00, 71.00] | <0.001 | 65.00 [56.00, 73.00] | 64.00 [55.00, 72.00] | <0.001 |
| Male sex (%) | 27730 (51.2) | 9569 (47.2) | <0.001 | 8446 (48.2) | 8372 (47.8) | 0.435 |
| BMI at surgery (kg/m2) (median [IQR]) | 28.00 [24.48, 32.38] | 31.10 [27.00, 36.25] | <0.001 | 29.70 [25.85, 34.33] | 30.67 [26.65, 35.70] | <0.001 |
| Weight at surgery (kg) (median [IQR]) | 99.10 [75.75, 161.00] | 108.86 [86.18, 159.39] | <0.001 | 107.20 [82.50, 168.00] | 109.32 [85.70, 160.94] | 0.015 |
| Medical History | ||||||
| Type 1 Diabetes (%) | 5643 (10.4) | 1496 (7.4) | <0.001 | 1160 (6.6) | 1236 (7.1) | 0.112 |
| Type 2 Diabetes (%) | 50563 (93.3) | 19756 (97.5) | <0.001 | 17040 (97.3) | 17025 (97.2) | 0.646 |
| Preoperative Hgb A1C (median [IQR]) | 6.40 [5.80, 7.30] | 7.00 [6.10, 8.10] | <0.001 | 6.80 [6.10, 7.80] | 6.90 [6.10, 8.00] | <0.001 |
| Anemia (%) | 22215 (41.0) | 7837 (38.7) | <0.001 | 6692 (38.2) | 6706 (38.3) | 0.886 |
| Arteriosclerosis (%) | 20700 (38.2) | 8005 (39.5) | 0.001 | 6991 (39.9) | 6805 (38.9) | 0.043 |
| Heart failure (%) | 8685 (16.0) | 3216 (15.9) | 0.615 | 2770 (15.8) | 2726 (15.6) | 0.528 |
| Hypertension (%) | 6929 (12.8) | 2019 (10.0) | <0.001 | 1976 (11.3) | 1823 (10.4) | 0.009 |
| Cirrhosis (%) | 3231 (6.0) | 1437 (7.1) | <0.001 | 1134 (6.5) | 1110 (6.3) | 0.616 |
| Hepatitis (%) | 2987 (5.5) | 916 (4.5) | <0.001 | 835 (4.8) | 832 (4.8) | 0.960 |
| Pancreatitis (%) | 1624 (3.0) | 367 (1.8) | <0.001 | 354 (2.0) | 357 (2.0) | 0.940 |
| Obesity (%) | 16201 (29.9) | 12119 (59.8) | <0.001 | 9294 (53.1) | 9513 (54.3) | 0.019 |
| Chronic kidney disease (%) | 16502 (30.5) | 5609 (27.7) | <0.001 | 5166 (29.5) | 4909 (28.0) | 0.003 |
| Chronic obstructive pulmonary disease (%) | 3211 (5.9) | 1118 (5.5) | 0.036 | 989 (5.6) | 974 (5.6) | 0.745 |
| Hypercholesterolemia/hyperlipidemia (%) | 35700 (65.9) | 14951 (73.8) | <0.001 | 12507 (71.4) | 12651 (72.3) | 0.089 |
| Diabetic Medications | ||||||
| Alpha-glucosidase inhibitors (%) | 279 (0.5) | 311 (1.5) | <0.001 | 179 (1.0) | 223 (1.3) | 0.031 |
| Biguanides (%) | 30682 (56.6) | 16703 (82.5) | <0.001 | 13954 (79.7) | 14052 (80.3) | 0.195 |
| DPP-4 inhibitors (%) | 33855 (62.5) | 17649 (87.1) | <0.001 | 14924 (85.2) | 14935 (85.3) | 0.880 |
| SGLT2 inhibitors (%) | 9422 (17.4) | 9995 (49.3) | <0.001 | 6831 (39.0) | 7393 (42.2) | <0.001 |
| Meglitinides (%) | 2554 (4.7) | 1943 9.6) | <0.001 | 1337 (7.6) | 1425 (8.1) | 0.085 |
| Sulfonylureas (%) | 9868 (18.2) | 6047 (29.9) | <0.001 | 4727 (27.0) | 4823 (27.5) | 0.254 |
| Thiazolidinediones (%) | 2414 (4.5) | 2468 (12.2) | <0.001 | 15.02 (8.6) | 1635 (9.3) | 0.014 |
| Insulin (%) | 32886 (60.7) | 14174 (70.0) | <0.001 | 11619 (66.4) | 11527 (65.8) | 0.304 |
Table 2:
Type of Surgery Before and After Propensity Score Matching
| Entire cohort | Propensity Score-Matched Cohort | |||||
|---|---|---|---|---|---|---|
| No Active GLP-1 RA Use | Active GLP-1 RA Use | p-value | No Active GLP-1 RA Use | Active GLP-1 RA Use | p-value | |
| Total procedures (n) | 54172 | 20253 | 17510 | 17510 | ||
| Type of surgery | ||||||
| Open | 37114 (68.5) | 13325 (65.8) | <0.001 | 11619 (66.4) | 11527 (65.8) | 0.304 |
| Closed | 170563 (31.5) | 6930 (34.2) | <0.001 | 5891 (33.6) | 5983 (34.2) | 0.304 |
| Organ system | ||||||
| Integumentary | 8807 (16.3) | 3396 (16.8) | 0.098 | 2872 (16.3) | 2914 (16.6) | 0.555 |
| Musculoskeletal | 5459 (10.1) | 2343 (11.6) | <0.001 | 1977 (11.3) | 2010 (11.5) | 0.590 |
| Respiratory | 4441 (8.2) | 1553 (7.7) | 0.019 | 1321 (7.5) | 1341 (7.7) | 0.702 |
| Cardiovascular | 8032 (14.8) | 2301 (11.4) | <0.001 | 2236 (12.8) | 2088 (11.9) | 0.017 |
| Gastrointestinal | 15419 (28.5) | 5976 (29.5) | 0.005 | 5202 (29.7) | 5205 (29.7) | 0.981 |
| Urinary | 9092 (16.8) | 3167 (15.6) | <0.001 | 2814 (16.1) | 2758 (15.8) | 0.422 |
| Genital | 2030 (3.7) | 1079 (5.3) | <0.001 | 872 (5.0) | 874 (5.0) | 0.980 |
| Maternity | 1625 (3.0) | 175 (0.9) | <0.001 | 137 (0.8) | 175 (1.0) | 0.035 |
| Nervous | 1897 (3.5) | 916 (4.5) | <0.001 | 726 (4.1) | 740 (4.2) | 0.729 |
| Other | 1120 (2.1) | 326 (1.6) | <0.001 | 331 (1.9) | 298 (1.7) | 0.198 |
Analysis of GLP-1 RA Use and Outcomes
The rates of GLP-1 RA medication use and concurrent diabetes medication use in the entire cohort and the propensity score-matched cohort are presented in Table 1. In the entire cohort, 27.2% of the surgical procedures were performed in the setting of an active GLP-1 RA prescription. Patients with an active GLP-1 RA prescription had significantly higher rates of concurrent prescriptions for all other diabetes medications compared to patients without a GLP-1 RA prescription. After propensity-score matching, significant differences in SGLT2 inhibitors and thiazolidinedione use persisted, but rates of all other diabetic medications were comparable.
Primary and secondary outcomes of the matched and unmatched cohorts are presented in Table 3. In the matched cohort analysis, patients with an active GLP-1 RA prescription at the time of surgery had lower rates of 30-day readmission compared to patients not actively being prescribed these medications (3.4% vs. 3.9%, p=0.031). They also had lower rates of dehiscence (0.8% vs. 1.2%, p=0.002) and hematoma (0.06% vs. 0.14%, p=0.030) within 180 days. The results from the GEE analysis of the primary and secondary outcomes of the matched cohort are shown in Supplemental Digital Content 5. Active GLP-1 RA prescription was associated with a reduced risk of 30-day readmissions (RR, 0.883; 95% CI, 0.789-0.987; p=0.028). A significant risk reduction was also noted for wound dehiscence within 180 days (RR, 0.711; 95% CI, 0.577-0.877; p=0.001) and hematoma (RR, 0.440; 95% CI, 0.216-0.894; p=0.023). The number needed to treat (NNT) to reduce one 30-day readmission was 219 (95% CI, 191-257), the NNT to reduce the incidence of 180-day wound dehiscence by one was 266 (95% CI, 202-391), and the NNT to reduce the incidence of 180-day hematoma by one was 1786 (95% CI, 652-2416) (Table 4).
Table 3:
Postoperative Complications and Readmission Rates in Matched and Unmatched Cohorts
| No Active GLP-1 RA Use | Active GLP-1 RA Use | p-value | |
|---|---|---|---|
| Total procedures – matched (n) | 17510 | 17510 | |
| Postoperative outcomes | |||
| Dehiscence within 6 months (%) | 213 (1.2) | 152 (0.9) | <0.001 |
| Infection within 6 months (%) | 149 (0.9) | 144 (0.8) | 0.814 |
| Hematoma within 6 months (%) | 25 (0.1) | 11 (0.1) | 0.030 |
| Bleeding within 6 months (%) | 107 (0.6) | 98 (0.6) | 0.575 |
| Readmission within 30 days (%) | 679 (3.9) | 602 (3.4) | 0.031 |
| Average # of readmissions within 30 days, if any (mean (SD)) | 1.13 (0.39) | 1.16 (0.41) | 0.227 |
| Total procedures - unmatched (n) | 54172 | 20253 | |
| Postoperative outcomes | |||
| Dehiscence within 6 months (%) | 809 (1.5) | 177 (0.9) | < 0.001 |
| Infection within 6 months (%) | 422 (0.8) | 168 (0.8) | 0.519 |
| Hematoma within 6 months (%) | 126 (0.2) | 11 (0.1) | < 0.001 |
| Bleeding within 6 months (%) | 365 (0.7) | 113 (0.6) | 0.087 |
| Readmission within 30 days (%) | 2668 (4.9) | 669 (3.3) | < 0.001 |
| Average # of readmissions within 30 days, if any (mean (SD)) | 1.16 (0.49) | 1.17 (0.42) | 0.707 |
Table 4:
Analysis of Adjusted Relative Risk of Primary and Secondary Outcomes in Propensity Score Matched Cohort
| OUTCOME | Adjusted Relative Risk Ratio (95% CI) | Baseline Risk | p-value | Number Needed to Treat (95% CI) |
|---|---|---|---|---|
| Dehiscence within 6 months | 0.711 (0.577, 0.877) | 0.013 | 0.0014 | 266 (203, 391) |
| Infection within 6 months | 0.966 (0.768, 1.22) | 0.008 | 0.769 | |
| Hematoma within 6 months | 0.440 (0.216, 0.894) | 0.001 | 0.0232 | 1786 (652, 2416) |
| Bleeding within 6 months | 0.915 (0.695, 1.20) | 0.005 | 0.529 | |
| Readmission within 30 days | 0.883 (0.789, 0.987) | 0.039 | 0.0285 | 219 (191, 257) |
Sensitivity Analyses
In open procedures, an active GLP-1 RA prescription was associated with lower rates of dehiscence in a propensity score-matched cohort (1.1% vs. 1.6%, p<0.001). A GEE analysis confirmed that patients with an active GLP-1 RA prescription had a 33.9% lower risk of postoperative dehiscence compared to those without (RR, 0.661; 95% CI, 0.526-0.831; p<0.001). In closed procedures, rates of readmission were lower in the GLP-1 RA group (1.7% vs. 2.3%, p=0.019). On GEE analysis, GLP-1 exposure was associated with a 27.3% reduced risk of 30-day readmission in closed procedures (RR, 0.727; 95% CI, 0.561-0.942; p=0.016) (see Tables, Supplemental Digital Content 6, 7).
Chi-squared tests were performed on outcomes between GLP-1 RA exposed and unexposed in propensity score-matched procedures of the integumentary, cardiovascular, gastrointestinal, and urinary systems. An active GLP-1 RA prescription was associated with lower rates of dehiscence in integumentary procedures (1.4% vs. 2.7%, p=0.001) and dehiscence (0.4% vs. 0.8%, p=0.008), hematoma (0.1% vs. 0.4%, p=0.008), and readmission (2.8% vs. 3.9%, p=0.004) in gastrointestinal procedures. However, in cardiovascular and urinary procedures, GLP-1 RA was associated with higher rates of infection (1.8% vs. 0.9%, p=0.025) and bleeding (0.7% vs. 0.3%, p=0.045), respectively (Table, Supplemental Digital Content 8).
Using an inverse probability weighted model of the full cohort, GLP-1 RA use was associated with statistically significant protective effects for 180-day dehiscence and hematoma. While this analysis did not show a significant reduction in readmission, an odds ratio below 1 supports the likelihood of a modest protective effect or no effect of GLP-1 RA medication on readmission rates after surgery (see Table, Supplemental Digital Content 9).
Discussion
In this retrospective, propensity score-matched cohort study, active GLP-1 RA prescriptions in diabetic patients were associated with a lower risk-adjusted 30-day readmission rate after a surgical procedure, compared to no active GLP-1 RA prescription. Additionally, active GLP-1 RA use indicated by an active GLP-1 RA prescription was associated with a reduction in postoperative wound dehiscence and hematoma. Previous studies of perioperative GLP-1 RA use in cardiac surgery have found improved postoperative glucose control and decreased perioperative insulin and inotropic agent requirement in patients given preoperative GLP-1 RA medicine16,29–31. Recommendations regarding preoperative GLP-1 RA discontinuation for potential anesthesia related complications have been inconsistent and based on limited evidence17–22. The American Gastroenterological Association (AGA) had stated that there is insufficient evidence for a formal guideline regarding GLP-1 RA management before endoscopic procedures32. However, a recent retrospective study found that patients taking GLP-1 RA medication for longer than six months prior to an endoscopic procedure have an increased risk of aspiration pneumonia in the periprocedural setting33. The present analysis, the first of its kind specifically investigating the effect of GLP-1 RA medication use on healing, bleeding, readmission, and other complications following surgical procedures widely, indicates that these medications do not increase perioperative morbidity and may be protective for diabetic patients undergoing both open and closed surgical procedures. The extent of the association between GLP-1 RA medications and postoperative complications and readmission varies depending on the organ system of procedure. These are important data for surgical and medical practitioners because they suggest that if providers can safely continue GLP-1 RA medications in the perioperative setting, patients with diabetes may benefit from reduced reoperations, wound complications, and readmission rates.
There are several hypotheses regarding the effects of GLP-1 RAs on wound healing. Patients with diabetes experience impaired wound healing secondary to a combination of vascular insufficiency, chronic inflammation, excess glycosylation, attenuated angiogenesis, and chronic hyperglycemia; therefore, improved glycemic control in the setting of GLP-1 RA use may counteract some of the deleterious effects of diabetes and lead to improved healing processes34–38. However, experimental studies of wound healing in diabetes suggest that the effects of GLP-1 go beyond tighter glucose control, mirroring the findings in our study, which hold true despite higher average hemoglobin A1C levels in the GLP-1 RA user group39. Several animal studies demonstrate that GLP-1 analogues, as well as GLP-1 breakdown inhibitors, accelerate excisional re-epithelialization and wound healing in vivo40–43. Additionally, other work has suggested that GLP-1 activation restores systemic anti-inflammatory and proangiogenic responses that are downregulated in diabetic states44, and that GLP-1 activation reduces vascular endothelial damage by lowering oxidative stress, promoting neo-angiogenesis, and indirectly inhibiting platelet activation, thereby reducing microvascular thrombosis45–48.
These experimental results, in addition to the clinical findings presented herein, suggest potential surgical wound healing benefits of perioperative GLP-1 RA use in diabetic patients. These possible gains must be carefully balanced with the anesthesia and aspiration risks these medications may pose. As GLP-1 RA prescriptions and indications continue to expand, our findings will become increasingly pertinent for surgeons, anesthesiologists, and patients alike.
The strengths of this paper include its large sample size. Thirty-seven covariates were included in the propensity-score matching, with minimal imbalance, as represented by standard mean differences <0.10 for all covariates. This cohort size and matching methodology is comparable to other clinically significant large cohort studies examining postoperative outcomes and metformin or statin use49–50. Additional sensitivity analyses support the results and matching methodology of this paper.
Limitations
In diabetes management, GLP-1 RA medications are not a first-line therapy. The decision to prescribe a GLP-1 RA is multifactorial, considering factors such as inadequate glycemic control with other medications like metformin, an individual’s potential cardiovascular benefit, and BMI. In focusing on the diabetic cohort, patients taking GLP-1 medications in this study were likely to have more advanced disease and failed more conventional therapies, which is reflected by the higher A1C and greater proportion of concurrent diabetes pharmacotherapy prescriptions in the GLP-1 RA group before propensity score-matching. Despite rigorous propensity score-matching and good balance between groups, the potential for residual bias or confounders remains. A1C was selected as a more global measure of glycemic control and overall health. However, we recognize that this does not measure acute glycemic control in the immediate perioperative period. Furthermore, socioeconomic determinants, such as patients’ race, ethnicity, and insurance, were outside of the scope of this project and propensity score-matching formula, although they may confound which patients are prescribed GLP-1 RAs.
Additionally, diabetes duration and the type, formulation, dosing, and preoperative duration of GLP-1 RA was not recorded in this study. This incomplete information, along with the retrospective nature of the analysis, limits our ability to establish causality. GLP-1 RA use was defined as an active prescription at the time of surgery, but whether patients were actually taking the medication is only circumstantial. Furthermore, guidelines on perioperative GLP-1 RA management have been in flux during the study period and may also vary amongst specialties and procedure types. These differences were not accounted for in this study. However, the GLP-1 RA medications in this study have a half-life of about one week. Therefore, even if patients were told to hold their medication dose one week before their surgery date, ~50% of the active medication dose would still be circulating at the time of surgery. Also, we are unable to account for non-documented or off-label GLP-1 RA prescriptions. Furthermore, this study was limited to patients with diabetes, and thus the results may not be generalizable to non-diabetic individuals taking GLP-1 RA medications for weight loss, for which the medication dosing is typically lower and more variable than for patients prescribed GLP-1 RAs for glycemic control.
All variables and complications were extracted retrospectively from the EHRs of two large metropolitan academic medical centers; as with all such studies, there are risks of misclassification, underreported events, and missed out-of-system information. Readmission rates have high accuracy, unless patients are readmitted to a different hospital which uses a different EHR, but postoperative complications were defined in this study by ICD-10 diagnosis codes assigned within 180 days of surgery. This methodology likely underestimates the outcomes, as it relies on providers electronically assigning a diagnosis in the EHR. There is no reason to believe that the rate of underestimation would be different between groups.
This study, which focused on operative complications, did not include information about complications such as aspiration and airway problems. These complications related to gastric emptying dysfunction are a primary concern of perioperative GLP-1 RA use. While these outcomes were outside the scope of the present study, future studies will examine these additional complications to provide a complete picture of perioperative GLP-1 RA use.
Conclusion
Perioperative exposure to GLP-1 RA was associated with a significant reduction in 30-day readmission rates and 180-day wound dehiscence and hematoma. With the rapidly increasing prevalence of GLP-1 RA use in patients with and without a diagnosis of diabetes, an understanding of its effect on postoperative complications is critical. Ongoing studies are examining the effect of GLP-1 RA medications on postoperative complications in the non-diabetic patient population, while also exploring the dose-response relationship. Additionally, we plan to expand the study to analyze additional postoperative outcomes—such as aspiration pneumonia, venous thromboembolism, stroke, acute kidney injury, and more—and specific subgroups of surgeries.
Supplementary Material
Conflicts of Interest and Source of Funding:
No authors report a conflict of interest. This project was funded using Dr. Spector’s lab resources.
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