Short-term outcomes after major lower limb amputation: meta-analysis

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Introduction Mortality after major lower limb amputation is a key factor in the decision to perform surgery. This review synthesizes the evidence on in-hospital and 30-day postoperative mortality after major amputation. Methods Electronic databases Medline, Embase, Scopus and African Journals Online were searched using keywords and thesaurus terms in October 2024 and updated in November 2025. Studies published globally and reporting in-hospital or 30-day mortality after major lower limb amputation (defined as at- or above-ankle amputation, or transtibial amputation (TTA) and/or transfemoral amputation (TFA)) and published between 2008 and 2025 were included. Only population level studies were included. Meta-analysis was performed and prediction intervals used to report findings primarily. The Newcastle–Ottawa tool was used to assess the methodological quality of studies. Results Fifty-two studies were included (1 067 616 patients). Only three studies were from low- and middle-income countries (two from Brazil, one from Togo). Most studies were either from North America (42%) or Europe and Central Asia (36%). Twenty-six studies reported in-hospital mortality and 26 reported 30-day mortality. Prediction intervals were 3.6–24.5% (point estimate 10.0%, 95% confidence interval 8.2% to 12.1%; 664 608), and 4.0–20.4% (point estimate 9.4%, 8.0% to 11.0%; 390 030) for in-hospital and 30-day mortality, respectively. In-hospital mortality prediction intervals were 2.9–12.7% (point estimate 6.2%, 5.1% to 7.7%; 77 204) for TTAs and 5.6–23.3% (point estimate: 11.8%, 9.6% to 14.4%; 78 632) for TFAs. Prediction intervals for 30-day mortality were 2.5–11.6% (point estimate 5.5%, 4.5% to 6.7%; 87 971) for TTAs and 4–26.6% (point estimate 10.9%, 8.3% to 14.2%; 42 145) for TFAs. Heterogeneity was high (> 75%) across all analyses. Conclusion Most studies reporting short-term outcomes after major lower limb amputation are from high-income countries. Reported mortality is highly variable, but prediction intervals can be used to estimate mortality in future studies and inform shared decision-making.