Alcohol use disorder increases risk of major adverse limb events following lower-extremity revascularization for chronic limb-threatening ischsemia - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Official websites use .gov A .gov website belongs to an official government organization in the United States. Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites. Search Log in Dashboard Publications Account settings Log out Search… Search NCBI Primary site navigation Search Logged in as: Dashboard Publications Account settings Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide PERMALINK Copy As a library, NLM provides access to scientific literature. 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Published in final edited form as: J Vasc Surg. 2026 Feb 24;83(6):1649–1660.e2. doi: 10.1016/j.jvs.2026.02.008 Search in PMC Search in PubMed View in NLM Catalog Add to search Alcohol use disorder increases risk of major adverse limb events following lower-extremity revascularization for chronic limb-threatening ischsemia Samantha N Machinski Samantha N Machinski , BA a Division of Vascular Surgery, UPMC, Pittsburgh, PA Find articles by Samantha N Machinski a , Mikayla Lowenkamp Mikayla Lowenkamp , MD a Division of Vascular Surgery, UPMC, Pittsburgh, PA b Department of Surgery, University of Pittsburgh, Pittsburgh, PA Find articles by Mikayla Lowenkamp a, b , Lindsey Olivere Lindsey Olivere , MD a Division of Vascular Surgery, UPMC, Pittsburgh, PA b Department of Surgery, University of Pittsburgh, Pittsburgh, PA Find articles by Lindsey Olivere a, b , Hasan Nassereldine Hasan Nassereldine , MD b Department of Surgery, University of Pittsburgh, Pittsburgh, PA Find articles by Hasan Nassereldine b , Mary Ann Ostach Mary Ann Ostach , BS a Division of Vascular Surgery, UPMC, Pittsburgh, PA Find articles by Mary Ann Ostach a , Neha Shetty Neha Shetty , BS a Division of Vascular Surgery, UPMC, Pittsburgh, PA Find articles by Neha Shetty a , Stuthi Iyer Stuthi Iyer , MPH a Division of Vascular Surgery, UPMC, Pittsburgh, PA Find articles by Stuthi Iyer a , Sarah Cook Sarah Cook , PhD c Department of Health Services Research and Policy, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom Find articles by Sarah Cook c , Katherine M Reitz Katherine M Reitz , MD, MSc a Division of Vascular Surgery, UPMC, Pittsburgh, PA b Department of Surgery, University of Pittsburgh, Pittsburgh, PA d Veterans Affairs Pittsburgh Health System, Pittsburgh, PA Find articles by Katherine M Reitz a, b, d Author information Article notes Copyright and License information a Division of Vascular Surgery, UPMC, Pittsburgh, PA b Department of Surgery, University of Pittsburgh, Pittsburgh, PA c Department of Health Services Research and Policy, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom d Veterans Affairs Pittsburgh Health System, Pittsburgh, PA AUTHOR CONTRIBUTIONS Conception and design: SM, ML, LO, HN, NS, SI, SC, KR Analysis and interpretation: SM, KR Data collection: SM, MO, KR Writing the article: SM Critical revision of the article: SM, ML, LO, HN, MO, NS, SI, SC, KR Final approval of the article: SM, ML, LO, HN, MO, NS, SI, SC, KR Statistical analysis: SM, KR Obtained funding: Not applicable Overall responsibility: SM ✉ Correspondence: Katherine M. Reitz, MD, MSc, Division of Vascular Surgery, UPMC, 200 Lothrop St, Pittsburgh, PA 15213 ( [email protected] ). Issue date 2026 Jun. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ). PMC Copyright notice PMCID: PMC13092323 NIHMSID: NIHMS2161515 PMID: 41748039 The publisher's version of this article is available at J Vasc Surg Abstract Objective: One in four patients with chronic limb-threatening ischemia (CLTI) undergo major amputation. Despite an established pathophysiological link between excessive alcohol consumption and adverse cardiovascular outcomes, the prevalence and impact of alcohol use disorder (AUD) among adult patients with CLTI has not been investigated. To address this gap, we sought to evaluate the association between AUD and major adverse limb events (MALE) among adults undergoing lower extremity revascularization for CLTI. Methods: Data were abstracted via Structured Query Language server queries of inpatient and outpatient electronic health records of the UPMC multi-hospital, unified health care system. We included index revascularization (endovascular or open) among adults with CLTI (2016-2024). Validated International Classification of Diseases, 10th Revision-Clinical Modification (ICD-10-CM) codes defined AUD. One-year outcomes of MALE (primary), major amputation, and major revascularization were compared with Fine-Gray regression risk-adjusted for competing mortality. Cumulative hazard curves and Cox modeling assessed these outcomes alongside 1-year mortality in sensitivity analyses. Multivariable regression was clustered by hospital and generated subdistribution (sHR) or adjusted (aHR) hazard ratios with 95% confidence intervals (CIs) for Fine-Gray or Cox modeling, respectively. Results: Among 3744 patients with CLTI undergoing revascularization (mean age, 69.8 ± 11.7 years; 61.0% male), 183 (4.9%) had an AUD diagnosis. Patients with an AUD diagnosis were more frequently male (84.2% vs 59.8%; P < .001) and concurrent tobacco users (56.3% vs 26.4%; P < .001). AUD correlated with an increased risk of 1-year MALE (35.6% vs 27.2%; P = .002). In Fine-Gray competing-mortality risk regression, AUD was independently associated with increased risk MALE (sHR, 1.29; 95% CI, 1.03-1.63; P = .029). Although major revascularization failed to reach significance (sHR, 1.14; 95% CI, 0.89-1.47; P = .295), AUD conferred higher 1-year risk of major amputation (sHR, 1.94; 95% CI, 1.65-2.36; P < .001) and mortality (aHR, 1.51; 95% CI, 1.09-2.09; P = .013). Conclusions: An AUD diagnosis independently conferred greater risk of MALE and mortality among adults undergoing index lower extremity revascularization for CLTI. These findings underscore the potential value of preoperative identification of AUD to refine risk stratification in this vulnerable, understudied population. Keywords: Alcohol use disorder, Chronic limb-threatening ischemia, Lower extremity revascularization, Major adverse limb events, Peripheral arterial disease Peripheral artery disease (PAD) is an atherosclerotic cardiovascular disease estimated to affect over 200 million people worldwide. 1 Chronic limb-threatening ischemia (CLTI), the most severe manifestation of PAD, is characterized by ischemic rest pain, non-healing ulcerations, and gangrene, culminating in a high risk of limb loss. 2 Revascularization techniques, including surgical bypass or endovascular therapies, can restore limb perfusion; however, without timely intervention, there is an ongoing 25% incidence of limb loss within 1 year of CLTI diagnosis 3 and 60% increased risk of mortality within 5 years of diagnosis. 4 Among elderly patients with CLTI undergoing major amputation, mortality risk rises to 85% within 5 years of amputation. 5 Comorbid psychiatric and medical conditions can further worsen CLTI outcomes 6 ; however, its association with alcohol use disorder (AUD) has not been investigated and is poorly understood. AUD is a global public health crisis affecting nearly 30 million individuals ages 12 and older in the United States. 7 Limited screening guidelines, inequitable access to care, and underreporting of alcohol use contribute to substantial underdiagnosis of AUD in clinical care settings. These interrelated factors prevent early detection of AUD and portend exacerbated morbidity and mortality for those with the diagnosis. 8 , 9 The chronic alcohol consumption defining AUD is directly associated with life-threatening pathophysiological changes across multiple organ systems. 10 , 11 Heavy drinking (≥3 drinks/day) is consistently linked to adverse cardiovascular outcomes, including coronary artery disease. 12 Furthermore, acute heavy alcohol intake enhances the progression of atherosclerosis, 13 alters the functionality of the coagulation cascade, and mirrors the inflammatory profile strongly associated with PAD development and progression. 14 Moreover, AUD and PAD disproportionately affect vulnerable populations and individuals of lower socioeconomic status (SES), groups who often face greater comorbidity burden, delayed medical treatment, and reduced access to care. 15 Despite these considerations, the long-term consequences of coexisting AUD and CLTI remains unknown. To address this gap, we sought to evaluate the association between AUD and major adverse limb events (MALE) among adults with CLTI undergoing lower extremity revascularization. MATERIALS AND METHODS Design and data sources. All data were retrospectively extracted via Structured Query Language server queries of inpatient and outpatient electronic health records (EHRs) of UPMC’s multi-hospital, unified health care system. The single health care provider and payer model provides robust data with minimal missingness and a comprehensive, longitudinal analysis of health care information. 16 – 18 The data for hypothesis testing have regulatory approval by the Institutional Review Board (STUDY24090124), and all data were presented in concordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. 19 Our data includes baseline demographic and patient data and outpatient and inpatient diagnosis codes, as well as long-term outcomes. Demographic data included age, sex, race, body mass index (BMI), Risk Analysis Index (RAI) as a validated measure of frailty, 20 Area of Deprivation Index (ADI) quantifying social determinates of health, 21 Rural-Urban Communicating Areas (RUCA) categorizing patients’ residence rurality status, 22 comorbid conditions, procedural characteristics, and hospital details. Outpatient evaluations of smoking status included self-reported tobacco use as current, never, passive, or quit, and a binary variable depicting active smokers (current) vs non-smokers (never, passive, or quit) defined smoking in our study. Validated diagnoses were defined by validated International Classification of Diseases, 10th Revision-Clinical Modification (ICD-10-CM) and procedures by Current Procedural Terminology (CPT) codes. 23 , 24 Endovascular and open revascularization procedure types were categorized by anatomical location of the most distal portion of the intervention as available. Lower extremity lysis CPT codes do not carry an anatomical level designation and were therefore categorized as unspecified. Missing data were quantified ( Supplementary Table I , online only). Cohort and exposure. We included index lower extremity revascularization procedure (endovascular or open) among adults (age ≥18 years) with CLTI (2016-2024). 3 Patients without a CLTI diagnosis, trauma admissions, and hospitals with <20 revascularizations performed annually were excluded from analyses. Our exposure of interest was a diagnosis of AUD. ICD-10-CM codes indicating an AUD diagnosis included those with: (1) a clinical diagnosis term indicating AUD; (2) evidence of alcohol withdrawal; or (3) chronic alcohol-related harm defined as any health-related outcome directly attributed to alcohol. 23 A complete list of ICD-10-CM codes utilized to identify AUD can be found in Supplementary Table II (online only). OUTCOMES We sought to identify the association between AUD and MALE among adults undergoing revascularization for CLTI and quantify the prevalence of AUD among patients with CLTI. Our primary outcome was 1-year MALE, including above-ankle amputation or major reintervention (surgical bypass or interposition grafting, thrombectomy, or thrombolysis). Secondary 1-year outcomes include individual items of the composite outcome MALE (major amputation, revascularization) and mortality. Death was defined by a combination of in-hospital death certificates and the Social Security Death Index, which is highly accurate but disallows for consistent characterization of cause of death. 16 Statistical analysis. Continuous data were presented as mean ± standard deviation (SD) (normally distributed variables) or median (interquartile range) (skewed distribution variables). Categorical data were presented as frequency (percentage). Baseline characteristics were compared between groups utilizing independent, two-sample t -test for normally, distributed continuous variables and Wilcoxon rank-sum test for non-normally distributed, continuous variables. χ 2 tests were employed for comparison of categorical variables. Cumulative hazard curves calculated the probabilities of 1-year observed primary and secondary outcomes over time, stratified by AUD diagnosis. Log-rank testing was employed to assess the equality of stratified hazard curves. For all non-mortality outcomes, multivariable Fine-Gray competing-risk regression models controlled for competing mortality risk with data clustered at the hospital level generating: (1) proportional subdistribution hazard ratios (sHRs) with 95% confidence intervals (CIs); and (2) adjusted cumulative hazards curves. For mortality, multivariable Cox proportional hazards models generated adjusted hazard ratios (aHRs) with 95% CIs. The assumption of proportional hazards was tested and met using weighted residual methods. 25 For all multivariable models, adjustments were made for age, sex, BMI, diabetes, congestive heart failure, coronary artery disease, hypertension, renal disease, ADI, current tobacco use, procedure type, and anatomical location of revascularization. Given the large proportion of missing BMI values, we introduced a sixth category to explicitly account for missing BMI in data modeling. Subgroup analysis to evaluate heterogeneity of treatment effect among a priori groups and procedural approach were evaluated for significance using interaction terms and HRs with 95% CIs were generated with linear combinations. 24 A P value < .05 was considered statistically significant. All statistical analyses were completed utilizing Stata version 18.5 (StataCorp). Sensitivity analysis. Result robustness was evaluated utilizing multiple sensitivity analyses. We explored the potential for unmeasured confounding between AUD diagnosis and 1-year MALE and mortality by calculating E-values. 26 The E-value quantifies the minimum magnitude of an unmeasured confounder required to invalidate the observed association between the presence of AUD diagnosis and 1-year MALE and mortality. Sensitivity analyses evaluating our primary outcome of 1-year MALE in adjusted cohorts included: (1) utilizing an alternative definition of AUD indicated solely by the ICD-10-CM F10 (alcohol-related disorders) diagnosis code; (2) addressing BMI missingness by combining individuals with missing BMI and those with a healthy weight BMI into a single reference group; and (3) incorporating binary indicators for documented primary care, cardiology, and anesthesiology visits during the study period into multivariable modeling to assess the potential influence of patient compliance with follow-up care. 16 All multivariable regression modeling the association between AUD diagnosis and MALE in the adjusted cohorts utilized Fine-Gray subdistribution hazard models adjusting for competing mortality risk. Given the widespread utilization of Cox regression in quasi-experimental clinical research, primary and secondary outcomes in the original cohort were analyzed with multivariable Cox proportional hazards models. aHRs with 95% CIs were generated with data clustered at the hospital level to estimate the effect of AUD on time to MALE, major amputation, secondary revascularization, and mortality. RESULTS A total of 3744 patients met all inclusion and no exclusion criteria during the study period ( Fig 1 ). The mean age was 69.8 years (SD, 11.7 years). The presence of AUD was identified in 183 patients (4.9%). Patients with AUD were more frequently male (84.2% vs 59.8%; P < .001) with a mean age of 64.2 years (SD, 8.2 years) vs 70.0 years (SD, 11.8 years) among patients without AUD ( P < .001). Compared with patients with AUD, those without AUD were more frequently African American (6% vs 11.3%; P = .01). Patients with an AUD diagnosis were more frequently concurrent tobacco users (56.3% vs 26.4%; P < .001), within limits of the healthy weight BMI classification (42.6% vs 20.4%; P < .001), had a higher ADI score (73.7 vs 71.0; P = .03), and more frequently presented with ulceration or gangrene (55.0% vs 45.0%; P = .017) ( Table I ). Fig 1. Open in a new tab Inclusion criteria. Consolidated Standards of Reporting Trials (CONSORT) diagram of inclusion and exclusion criteria defining final cohort of all adult patients who underwent index lower-extremity revascularization for chronic limb-threatening ischemia ( CLTI ). AUD , Alcohol use disorder; LE , lower extremity; PAD , peripheral artery disease. Table I. Baseline characteristics of adult patients with chronic limb-threatening ischemia ( CLTI ) stratified by the presence of alcohol use disorder ( AUD ) diagnosis Parameter characteristics No AUD diagnosis (n = 3561) AUD diagnosis (n = 183) P value Age, years 70.04 (11.77) 64.15 (8.19) <.001 Sex <.001 Female 1431 (40.2) 29 (15.8) Male 2130 (59.8) 154 (84.2) Race .010 White 3078 (86.4) 163 (89.1) Black 404 (11.3) 11 (6.0) Asian 13 (0.4) 1 (0.5) American Indian 7 (0.2) 2 (1.1) Other 59 (1.7) 6 (3.3) BMI <.001 Underweight 106 (3.0) 15 (8.2) Healthy weight 726 (20.4) 78 (42.6) Overweight 705 (19.8) 29 (15.8) Obese 565 (15.9) 22 (12.0) Morbidly obese 1459 (41.0) 39 (21.3) RAI .022 Robust 1601 (45.0) 101 (55.2) Normal 1449 (40.7) 63 (34.4) Frail 511 (14.3) 19 (10.4) ADI 71.03 (16.13) 73.70 (15.33) .03 RUCA .18 Non-rural 2500 (70.2) 120 (65.6) Rural 1061 (29.8) 63 (34.4) Self-reported alcohol use <.001 Yes 1088 (38.3) 93 (66.4) No 1604 (56.4) 32 (22.9) Current tobacco use 939 (26.4) 103 (56.3) <.001 Hypertension 1994 (56.0) 89 (48.6) .13 Coronary artery disease 1896 (53.2) 62 (33.9) <.001 Congestive heart failure 1150 (32.3) 48 (26.2) .20 Diabetes 2803 (78.7) 139 (76.0) .59 Renal failure 991 (27.8) 59 (32.2) .39 Cirrhosis 68 (1.9) 36 (19.7) <.001 Fatty liver disease 83 (2.3) 10 (5.5) .027 Alcohol-related liver disease 0 (0.0) 23 (12.6) <.001 HbA1c 7.26 (1.92) 6.33 (1.75) <.001 Platelets 250.18 (101.36) 248.35 (109.17) .81 CLTI presentation .017 Rest pain 1458 (55) 70 (45) Ulceration/gangrene 1207 (45) 86 (55) Procedure type <.001 Open 1489 (41.8) 111 (60.7) Endovascular 2072 (58.2) 72 (39.3) Anatomical location of revascularization <.001 Aortoiliac 495 (13.9) 48 (26.2) Femoropopliteal 2014 (56.6) 106 (57.9) Tibial 940 (26.4) 25 (13.7) Documented medical visits Primary care 5 (2.7) 5 (2.7) .90 Cardiology 77 (2.2) 1 (0.5) .14 Anesthesiology 6 (0.2) 0 (0.0) .58 Open in a new tab ADI , Area Deprivation Index; BMI , body mass index; HbA1c , hemoglobin A1c; RAI , Risk Analysis Index; RUCA , Rural-Urban Commuting Area. Data are presented as number (%) or mean (standard deviation). Among the 3744 patients with CLTI undergoing lower extremity revascularization, 2144 patients (57.3%) underwent endovascular revascularization, whereas 1600 patients (42.7%) underwent open surgical revascularization. The majority of revascularization was femoropopliteal interventions (2120 patients; 56.6%). 543 patients (14.5%) underwent aortoiliac revascularization, whereas 965 patients (25.8%) underwent revascularization at the tibial artery. Anatomical location of revascularization was unspecified for 116 patients (3.1%) within this cohort. During the follow-up period, 933 patients (24.9%) experienced MALE, and 642 patients (17.2%) died. Among individual items of MALE, 353 patients (9.4%) underwent major amputation, whereas 709 patients (18.9%) underwent secondary revascularization. Cumulative hazard curves demonstrated the probability of MALE and all-cause mortality over time and stratified by the presence of AUD diagnosis ( Fig 2 ). AUD correlated with an increased risk of 1-year MALE (35.6% vs 27.2%; P = .0015), major amputation (19.2% vs 10.1%; P < .001), and secondary revascularization (26.6% vs 21.0%; P = .027); however, mortality failed to reach significance in univariate evaluation (20.2% vs 18.3%; P = .336). Fig 2. Open in a new tab Observed cumulative hazard estimates for 1-year major adverse limb events ( MALE ) (A) , mortality (B) , major amputation (C) , and secondary revascularization (D) . Observed cumulative hazard estimates for 1-year MALE (A) , mortality (B) , major amputation (C) , and major revascularization (D) . AUD , Alcohol use disorder. In multivariable Fine-Gray competing-mortality risk regression, AUD was independently associated with 29% increased adjusted risk of MALE (sHR, 1.29; 95% CI, 1.03-1.63; P = .029). Among the individual components of MALE, AUD diagnosis conferred a nearly two-fold increased risk of major amputation (sHR, 1.94; 95% CI, 1.65-2.36; P < .001), but AUD was not significantly associated with an increased adjusted risk of major revascularization risk (sHR, 1.14; 95% CI, 0.89-1.47; P = .295) ( Table II ; Fig 3 ). In multivariable Cox regression, AUD was associated with an 51% increased risk of morality (HR, 1.51; 95% CI, 1.09-2.09; P = .013) ( Supplementary Table III , online only). Table II. Fine-Gray proportional subdistribution hazards model of 1-year major adverse limb events ( MALE ), major amputation, and major revascularization risk-adjusted for competing mortality Covariate 1-Year MALE 1-Year major amputation 1-Year major revascularization sHR 95% CI P value sHR 95% CI P value sHR 95% CI P value AUD diagnosis 1.29 1.03-1.63 .029 1.97 1.65-2.36 <.001 1.14 0.89-1.47 .295 Age 0.97 0.97-0.98 <.001 0.96 0.95-0.97 <.001 0.97 0.97-0.98 <.001 Female sex 0.85 0.74-0.98 .027 0.98 0.75-1.29 .907 0.88 0.74-1.04 .121 BMI Underweight Reference Reference Reference Healthy weight 0.87 0.60-1.26 .449 0.70 0.38-1.28 .242 0.92 0.57-1.50 .741 Overweight 0.97 0.67-1.41 .869 0.81 0.40-1.62 .548 1.01 0.62-1.64 .976 Obese 0.92 0.63-1.33 .642 0.53 0.29-1.00 .049 1.12 0.70-1.79 .638 Morbidly obese 0.74 0.45-1.23 .248 0.85 0.29-2.44 .758 0.65 0.31-1.36 .255 Missing 0.84 0.58-1.23 .368 0.67 0.36-1.25 .210 0.90 0.53-1.53 .696 Diabetes 0.92 0.83-1.03 .143 1.07 0.80-1.42 .658 0.84 0.76-0.93 .001 Congestive heart failure 1.03 0.88-1.19 .748 1.28 0.96-1.71 .095 0.90 0.75-1.07 .217 Coronary artery disease 1.19 0.94-1.50 .144 1.19 0.90-1.58 .216 1.20 0.91-1.59 .194 Hypertension 0.99 0.83-1.17 .869 0.82 0.66-1.01 .064 0.98 0.80-1.21 .867 Renal disease 0.96 0.80-1.16 .674 1.39 1.14-1.68 .001 0.83 0.68-1.03 .094 ADI 1.00 1.00-1.01 .573 1.01 1.00-1.02 .158 1.00 0.99-1.01 .758 Current tobacco user 0.90 0.81-1.02 .092 0.73 0.58-0.94 .013 0.96 0.83-1.12 .623 Procedure type Open Reference Reference Reference Endovascular 1.18 0.98-1.41 .083 0.96 0.75-1.21 .708 1.19 0.96-1.49 .117 Anatomical location of revascularization Aortoiliac Reference Reference Reference Femoropopliteal 1.10 0.89-1.37 .382 2.42 1.45-4.04 .001 0.93 0.73-1.17 .538 Tibial 1.06 0.85-1.32 .596 3.88 2.09-7.22 <.001 0.75 0.59-0.94 .013 No location specified 1.79 1.32-2.41 <.001 2.79 1.55-5.01 .001 1.57 1.08-2.28 .018 Open in a new tab ADI , Area Deprivation Index; BMI , body mass index; CI , confidence interval; sHR , subdistribution hazard ratio. P -value < .05 was considered statistically significant. Fig 3. Open in a new tab Adjusted cumulative hazard estimates for 1-year major adverse limb events (MALE) (A) , major amputation (B) , and major revascularization (C) . AUD , Alcohol use disorder; CI , confidence interval; sHR , subdistribution hazard ratio. In subgroup analyses, the association between AUD and MALE was ubiquitously observed ( Fig 4 ). However, it was moderated by revascularization type ( P interaction = .012). Among individuals with AUD, a greater magnitude of 1-year MALE was observed among those undergoing endovascular (sHR, 1.69; 95% CI 1.26-2.27) when compared with open (sHR, 1.05; 95% CI, 0.79-1.39) revascularization. Fig 4. Open in a new tab Association between alcohol use disorder ( AUD ) and major adverse limb events ( MALE ) among subgroups. Forest plot of Fine-Gray proportional hazard models demonstrating subdistribution hazard ratios ( sHRs ) and associated 95% confidence intervals ( CIs ) for 1-year MALE risk among prespecified subgroups. Sensitivity analysis. The robustness of our results was apparent in multiple sensitivity analyses. The E-values calculated for the observed association between AUD diagnosis and MALE and mortality were 1.78 and 1.99, respectively, implying that considerable unmeasured confounding would be required to invalidate our primary findings. The association between AUD and MALE remained robust when: (1) utilizing an AUD definition solely defined by F10 ICD-10-CM codes (sHR, 1.34; 95% CI, 1.08-1.67, P = .008); (2) grouping missing BMI and healthy BMI into a single reference category (sHR, 1.30; 95% CI, 1.02-1.65; P = .033); and (3) including binary patient compliance markers (primary care physician [PCP], cardiology, and anesthesiology visits) in modeling (sHR, 1.28; 95% CI, 1.03-1.62; P = .028). In multivariable Cox modeling, the adjusted risk of MALE (aHR, 1.36; 95% CI, 1.10-1.68; P = .005) was higher among patients with AUD compared with those without ( Supplementary Table III , online only). Again, AUD was not significantly associated with an increased risk of major revascularization (aHR, 1.19; 95% CI, 0.94-1.52; P = .154); however, higher adjusted risk of major amputation with AUD diagnosis persisted (aHR, 2.14; 95% CI, 1.39-3.29; P = .001). DISCUSSION In this large, multi-hospital analysis of 3744 adults with CLTI undergoing lower extremity revascularization within a unified health system, the prevalence of an AUD diagnosis was 5%. AUD was associated with a 29% higher risk of 1-year MALE and 51% higher risk of 1-year mortality compared with patients without AUD. Our findings were robust in subgroup and sensitivity analyses. An AUD diagnosis among 5% of adult patients with CLTI is comparable to current estimates in similarly aged populations in the United States. 7 However, given that less than 20% of adults consuming alcohol report disclosing it to their physician, 27 this figure likely under-estimates the true burden of AUD among adults with CLTI due to substantial underdiagnosis and underreporting of the disorder. 8 , 9 In the absence of immediate clinical relevance or active therapeutic intervention, alcohol consumption may be omitted from EHRs. This discrepancy has been attributed to the lack of universal screening, stigmatization of substance use, and limited physician training on substance use disorders. 28 Validated tools for standardized screening of AUD are efficient to administer and have demonstrated high sensitivity. Specifically, the Alcohol Use Disorders Identification Test – Consumption (AUDIT-C) or CAGE questionnaire are simple and efficient, but infrequently utilized in clinical practice, contributing to diagnostic omission of AUD. 29 A recent evaluation of alcohol screening demonstrated that, although alcohol use was documented for roughly 75% of patients in a primary care setting, validated screening instruments were utilized in only 2.1% of encounters, disallowing for the capture of unhealthy alcohol consumption. 30 Importantly, a previous study utilizing the Veteran’s Affairs Quality Improvement Program demonstrated that AUDIT-C scores ≥5 reported within 1 year of non-cardiac surgery were associated with heightened postoperative complication risks, 31 highlighting that underrecognition of AUD may be especially consequential in high-risk surgical populations. This diagnostic limitation therefore carries important clinical implications and may negatively influence surgical outcomes in this high-risk population, underscoring the need to systematically integrate validated screening instruments into routine clinical workflows. Given the observed increased risk of MALE following revascularization, screening and documentation of AUD in vascular surgery clinics alongside in-hospital consultations will add valuable risk stratification and improve identification of unhealthy alcohol use in at-risk patients. Beyond risk stratification, identification of AUD can allow for risk-reducing treatments. Traditional community-based, step-wise group programs (ie, Alcoholics Anonymous) consistently demonstrate a high rate of effectiveness, above that of other cogitative behavioral therapies. 32 Moreover, numerous oral therapies are available and are more immediately efficacious for reducing alcohol intake both alone and in combination with step programs. 33 Initiation of preoperative alcohol cessation or reduction programs for elective interventions has shown promising results reducing postoperative complications. 34 Delaying care for CLTI to reach alcohol cessation is often not feasible and may ultimately worsen limb outcomes. Furthermore, prospective trials randomizing patients to intensive cessation programs vs standard of care prior to oncologic resections, which similarly cannot be delayed, yielded high rates of successful cessation but failed to demonstrate corresponding outcome improvement. 35 Our data identify the association between AUD and adverse outcomes following CLTI revascularization; however, additional work is required to identify ideal next steps. In the advent of broad preoperative risk stratification strategies paired alongside enhanced recovery programs, focused AUD identification and validated programs targeting alcohol use reduction may serve as a critical opportunity for detection and evidence-based strategy for treatment approach in the context of CLTI revascularization. 36 After multivariable adjustment for potential confounders, AUD conferred greater risk of MALE and mortality within 1 year of index lower extremity revascularization. Our findings support the establishment of AUD as an independent predictor for poorer postoperative outcomes among adults undergoing revascularization for CLTI. Although existing literature is limited, similar trends have been observed across other surgical subspecialties. A meta-analysis conducted by Harris et al demonstrated that alcohol use or misuse, including AUD, was consistently associated with elevated risk of postoperative complications and mortality across a range of abdominal, urologic, and orthopedic operations. 37 Although the definition for alcohol use/misuse varied across individual studies, these findings collectively underscore the broader impact of AUD and related patterns of alcohol misuse on postoperative outcomes across diverse surgical populations. Taken alongside our findings, these data emphasize the need for further research evaluating the independent impact of AUD on surgical outcomes to refine risk stratification in this vulnerable population. The elevated surgical risk associated with AUD is un-likely to act in isolation. AUD is commonly comorbid with additional social and behavioral stressors (ie, smoking, adverse social determinants of health [SDOH]) compound postoperative morbidity and mortality. 38 Previous literature has associated social risk factors, particularly tobacco use, with an increased risk of adverse limb events among patients undergoing revascularization for CLTI. 24 , 39 Within our cohort, those with an AUD diagnosis were more commonly observed to be active smokers with a significantly higher ADI. The latter observation reflects greater neighborhood-level socioeconomic disadvantage among individuals with AUD, linked to poorer access to health care and lower rates of long-term follow-up. 40 Furthermore, the association between AUD and adverse SDOH, including unstable housing, unemployment, and limited access to care, have been well-described. 41 These factors have been independently linked to poorer postoperative outcomes and recovery in broader surgical populations. 42 When considered alongside the high smoking prevalence among patients with AUD, these findings underscore the convergence of behavioral and social vulnerability that may potentially confound risk, undermine postsurgical outcomes, and impede recovery following major vascular interventions in this high-risk patient population. Holistic preoperative risk assessments and multidisciplinary, community-engaged approaches to care are warranted to optimize long-term outcomes in surgical candidates with coexisting AUD and CLTI. In subgroup analyses, endovascular revascularization conferred a higher risk of MALE among patients with AUD; however, this association did not persist among patients undergoing open revascularization. Therefore, consistent with evidence from recent trials, open revascularization provided superior results for patients with AUD. 3 Our findings are likely multifactorial and highlight important directions for future investigations aimed at furthering our understanding of the pathophysiologic mechanisms linking AUD and PAD, but also may be secondary to: (1) their younger age and robust status 43 , 44 ; (2) underlying liver disease-related coagulopathy altering endovascular revascularization patency rates 45 ; or (3) alterations in antithrombotic therapy compliance, a determinant especially important for endovascular revascularization durability. 46 Notably, subgroup analyses demonstrated that the association between AUD and MALE was not moderated by a diagnosis of cirrhosis, implying that the adverse impact of AUD on limb outcomes in CLTI is likely driven by multifactorial biological, behavioral, and social (eg, SDOH) mechanisms. Overall, these data further underscore the critical role of intervention-specific risk modeling into patient counseling discussions to facilitate informed decision-making in the preoperative care setting. Future prospective investigations should aim to incorporate temporal measures (time from AUD diagnosis to index procedure), disease severity, and treatment compliance into study designs to better delineate causal relationships and refine approaches to revascularization strategy. To better contextualize our findings, the pathophysiological consequences of excessive alcohol consumption warrant consideration. Hepatic metabolism of alcohol results in the generation of reactive oxygen species and disruption of various molecular signaling path-ways, contributing to systemic oxidative stress and inflammation alongside focal hepatic injury. 10 , 47 , 48 Alcohol-related hepatic dysfunction is also associated with malnutrition, immune dysregulation, and impaired wound healing—factors that may underlie poorer postoperative outcomes among patients with AUD undergoing surgical intervention for CLTI. 49 , 50 A diagnosis of CLTI is often complicated by non-healing ulceration and gangrene; therefore, it is plausible that ulcerative manifestations of CLTI in patients with coexisting AUD—who may present with compromised immune function—contribute to poorer postoperative outcomes. However, subgroup analyses assessing the clinical presentation of CLTI among patients with AUD (rest pain vs ulceration or gangrene), which must be interpreted with caution secondary to the subgroup sample size, demonstrated that variation in presentation did not significantly modify the risk of 1-year MALE or mortality. These results indicate that systemic injury may be a more relevant driver of adverse outcomes comparatively. This hypothesis is consistent with prior literature establishing the association between AUD and malnutrition, immune dysregulation, and abnormal cytokine profiles. 47 , 48 These findings underscore the need for future prospective trials to elucidate the relative contributions of localized wound biology vs hepatic dysfunction as drivers of poor outcomes among patients with AUD and CLTI. Our study has limitations warranting consideration. First, the database utilized in this study was generated from a unified, multihospital hospital system with participating hospitals sharing centralized administration practices, catchment areas, and EHRs. Our final cohort identified as predominantly White race with smaller sample sizes representing minority racial and ethnic groups, introducing limitations to external validity. Second, the retrospective, non-randomized design of this study constrains our ability to establish a temporal relationship between AUD and CLTI and therefore limits causal inference. Data were obtained from past medical records and administrative data; therefore, analyses are both limited by what is available for characterization and susceptible to missing data or misclassification, and unmeasured confounding may persist. Additionally, subgroup analyses are limited by power and must be interpreted with caution. Notably, a diagnosis of AUD relied on ICD-10-CM code identification, which lacks detailed information on disease severity, timing, duration, and progression, thereby introducing heterogeneity in exposure classification. This approach: (1) increases risk for patient misclassification and underdiagnosis; (2) limits the granularity of AUD identification and status at time of index intervention; (3) precludes temporal analyses between AUD onset and procedural intervention; and (4) restricts the ability to quantify the dose-response relationships between AUD severity on revascularization outcomes. CONCLUSIONS An AUD diagnosis was associated with markedly worse limb-related and survival outcomes following index revascularization for CLTI. Our findings underscore the potential prognostic importance of preoperative AUD identification and support implementation of universal screening guidelines to improve perioperative risk stratification in this vulnerable and understudied patient population. Supplementary Material sup1 NIHMS2161515-supplement-sup1.pdf (65.5KB, pdf) sup3 NIHMS2161515-supplement-sup3.pdf (94.7KB, pdf) sup2 NIHMS2161515-supplement-sup2.pdf (37.1KB, pdf) ARTICLE HIGHLIGHTS. Type of Research: Multi-hospital, single-center, retrospective cohort study Key Findings: Alcohol use disorder (AUD) is 4.9% prevalent among 3744 patients undergoing lower extremity revascularization for chronic limb-threatening ischemia. AUD diagnosis was independently associated with a greater risk of major adverse limb events (subdistribution hazard ratio, 1.29; 95% confidence interval, 1.03-1.63; P = .029) and mortality (adjusted hazard ratio, 1.51; 95% confidence interval, 1.09-2.09; P = .013). Take Home Message: Preoperative identification of AUD and its inclusion in risk stratification models may improve postoperative outcomes among adult patients with chronic limb-threatening ischemia and AUD. FUNDING Funding for the project was obtained from the Society of Vascular Surgeons (SVS) Student Research Fellowship and the Summer Research in Vascular Surgery Project Grant (T35HL155018). Footnotes Presented at the Thirty-ninth Annual Meeting of the Eastern Vascular Society, Nashville, Tennessee, September 4-7, 2025. Additional material for this article may be found online at www.jvascsurg.org . The editors and reviewers of this article have no relevant financial relationships to disclose per the JVS policy that requires reviewers to decline review of any manuscript for which they may have a conflict of interest. DISCLOSURES None. The views expressed in this article are those of the authors and do not necessarily reflect the position of the Department of Veterans Affairs or the United States Government. REFERENCES 1. Shu J, Santulli G. Update on peripheral artery disease: epidemiology and evidence-based facts. 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