Lower Limb Amputations Among Individuals Living With Diabetes Mellitus in Low- and Middle-Income Countries: A Systematic Review and Meta-Analysis.
systematic_review · Level I
Where this comes from
- Record sourced from PubMed, PMID 42452908.
- Also identified by DOI 10.1002/wjs.70493.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
Diabetes-related lower-limb amputation (LLA) is a major global health problem; although rates have declined in some high-income settings, the burden in low- and middle-income countries (LMICs) has not been systematically quantified. This review aimed to estimate the prevalence and incidence of diabetes-related LLA in LMICs, based on available published evidence from community and facility-based populations. Following a PROSPERO-registered protocol (CRD42021238656), we searched Medline, CINAHL, AJOL, Scopus, Embase, and Google Scholar (January 1990-June 2025) for quantitative studies reporting diabetes-related LLA in LMICs from community and facility populations. Data were extracted using Joanna Briggs Institute tools, low-quality studies were excluded from quantitative synthesis, and meta-analyses used the Freeman-Tukey double-arcsine transformation; subgroup analyses (age, sex, WHO region, high-risk groups) explored heterogeneity, and certainty of evidence (CoE) was assessed with GRADE. Of 201 included studies from 32 LMICs, 121 moderate-to-high-quality studies were meta-analyzed; most were facility-based high-risk cohorts (especially diabetic foot or advanced-complication care). Pooled prevalence was 23 per 100 individuals (95% CI 0.21-0.24; n = 89; moderate CoE), incidence 29 per 100 (95% CI 0.25-0.32; n = 29; low CoE), re-amputation 31 per 100 (95% CI 0.14-0.48; n = 8; low CoE), and contralateral amputation 23 per 100 (95% CI 0.13-0.33; n = 2; very low CoE). Diabetes-related LLA remains a substantial burden in LMICs, while scarce population-based data highlights key surveillance gaps for prevention planning.