Concealed cannabis use and adverse outcomes after lower-limb arthroplasty in a narcotic drugs and psychotropic substances -constrained setting: A case series

Background: Preoperative cannabis use disorder is an established independent risk factor for adverse outcomes after total hip and knee arthroplasty in legalized settings, where disclosure is reliable. In India, enforcement under the Narcotic Drugs and Psychotropic Substances (NDPS) Act promotes stigma and under-reporting, leaving the perioperative impact of cannabis use in arthroplasty poorly characterized. Methodology: A retrospective case series was performed at a tertiary care center in Bengaluru, including seven consecutive male patients who underwent primary lower-limb arthroplasty between January 2023 and June 2024. Procedures comprised total hip arthroplasty (THA) ( n = 3), total knee arthroplasty ( n = 2), and bipolar hemiarthroplasty ( n = 2). Inclusion criteria were documented preoperative denial of cannabis use, post-complication disclosure of persistent consumption, and complete 18-month follow-up. Demographics, comorbidities, postoperative cannabis use patterns, and complications were descriptively analyzed. Results: The median age was 57 years (range 40–63). All patients denied cannabis use preoperatively, while persistent postoperative consumption was later confirmed in all cases (median 4 joints/week). Comorbidities included tobacco use (71%) and alcohol use (29%). Major complications occurred in two of seven patients (29%): deep periprosthetic joint infection (Patient 1, THA) and aseptic loosening (Patient 4, TKA). No additional implant-related failures were observed during follow-up. Conclusion: Concealed and persistent cannabis use in an NDPS-restricted Indian setting was associated with a relatively high complication burden after lower-limb arthroplasty. These findings underscore the limitations of reliance on self-reported substance use and support consideration of ethically governed objective screening and multidisciplinary perioperative optimization in similar contexts.