{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T15:35:21Z","timestamp":1790091321828,"version":"4.0.1"},"reference-count":70,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2025,6,3]],"date-time":"2025-06-03T00:00:00Z","timestamp":1748908800000},"content-version":"vor","delay-in-days":2,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["International Wound Journal"],"published-print":{"date-parts":[[2025,6]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:p>This study compares the performance of various wound classification systems to determine which system most effectively predicts amputation risk in diabetic foot ulcer (DFU) patients. Additionally, it identifies the key clinical and socioeconomic factors that influence this risk. A total of 616 DFUs from 400 outpatient participants in a prospective cohort study were followed over 6\u2009months. Ten machine learning (ML) algorithms were employed to evaluate the predictive accuracy of various wound classification systems. The SHapley Additive exPlanations (SHAP) method was used to interpret the predictions of the selected model. The DIAFORA (diabetic foot risk assessment) and WIFI (Wound, Ischaemia and foot Infection) classification systems demonstrated the highest predictive power for predicting amputation within 6\u2009months. SHAP analysis revealed that wound penetration to bone, presence of ischaemia and infection, renal failure, delayed first specialist visit, longer diabetes duration, high baseline HbA1c, low education levels and high body mass index were significant risk factors for amputation. Conversely, higher education levels served as a protective factor. Occupation showed variable effects, with private\u2010sector employment associated with increased risk, while being a housewife was linked to lower risk. Infection and ischaemia are significant factors affecting DFU outcomes. Addressing treatment adherence barriers and implementing tailored interventions that consider patients' occupational needs can reduce amputation rates.<\/jats:p>","DOI":"10.1111\/iwj.70515","type":"journal-article","created":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T01:18:32Z","timestamp":1748999912000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Machine Learning Insights Into Amputation Risk: Evaluating Wound Classification Systems in Diabetic Foot Ulcers"],"prefix":"10.1111","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1611-3806","authenticated-orcid":false,"given":"Farideh","family":"Mostafavi","sequence":"first","affiliation":[{"name":"Student Research Committee School of Public Health and Safety, Shahid Beheshti University of Medical Sciences  Tehran Iran"},{"name":"Department of Epidemiology School of Public Health and Safety, Shahid Beheshti University of Medical Sciences  Tehran Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5550-6792","authenticated-orcid":false,"given":"Mohammad Reza","family":"Amini","sequence":"additional","affiliation":[{"name":"Diabetes Research Center Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences  Tehran Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yadollah","family":"Mehrabi","sequence":"additional","affiliation":[{"name":"Department of Epidemiology School of Public Health and Safety, Shahid Beheshti University of Medical Sciences  Tehran Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ensieh","family":"Nasli Esfahani","sequence":"additional","affiliation":[{"name":"Diabetes Research Center Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences  Tehran Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seyed Saeed Hashemi","family":"Nazari","sequence":"additional","affiliation":[{"name":"Department of Epidemiology School of Public Health and Safety, Shahid Beheshti University of Medical Sciences  Tehran Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,6,3]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12889-020-08953-6"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41581-020-0278-5"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.2147\/CWCMR.S98762"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.31128\/AJGP-11-19-5161"},{"issue":"2","key":"e_1_2_10_6_1","first-page":"112","article-title":"Diagnosis and Treatment of Diabetic Foot Infections: Adopted IWGDF Guidline","volume":"79","author":"Amini M. 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