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RESEARCH Open Access© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit h t t p : / / c r e a t i v e c o m m o n s . o r g / l i c e n s e s / b y / 4 . 0 /.Khan et al. BMC Medical Informatics and Decision Making (2025) 25:287 https://doi.org/10.1186/s12911-025-03112-6BMC Medical Informatics and Decision Making*Correspondence:Sabiha Khansabiha.khan@fnu.ac.f j1 School of Information Technology, Engineering, Mathematics & Physics, The University of the South Pacif i c, Suva, Fiji2 College of Medicine, Nursing and Health Science, Fiji National University, Suva, Fiji3 Diabetic Hub, Colonial War Memorial Hospital, Suva, FijiAbstractBackground or introduction Multiple Lower extremity amputation (MLEA) is an unfortunate outcome following a lower extremity amputation (LEA) in individuals with diabetes. The challenges faced by individual with MLEA are signif i cantly higher than those who have undergone a single amputation. Therefore, developing a reliable and accurate method for determining risk factors associated with MLEA is essential for reducing the incidence of this outcome among diabetic patients.Objectives This study aimed to explore the demographic and clinical characteristics of diabetic inpatients with foot ulcers. The goal was to develop a statistical model to determine the risk factors of MLEA among patients type 2 diabetic mellitus (T2DM).Methods Data for statistical model development were collected from patients’ folders involving 1,972 patients with T2DM who were hospitalized for acute diabetic foot ulcers (DFU) at three tertiary care hospitals in Fiji from 2016 to 2019. This cross-sectional study was conducted in accordance with the STROBE guidelines focusing on patients who experienced MLEA at the hospitals. Patients were categorized into three ordinal outcomes: no-amputation, primary amputation, and multiple amputations. A partial proportional odds model was developed to fi t the ordinal outcome and determine the risk factors associated with MLEA. The proposed model was validated by comparing it to a proportional odds model and a multinomial logistics regression model.Results The proposed partial proportional odds model (PPOM) identif i ed several risk factors for MLEA, including age, gender, ethnicity, hypertension, anemia, leukocytosis, and thrombocytosis.Conclusions The analytical fi ndings reveal that the PPOM is appropriate for determining the risk factors associated with MLEA in T2DM patients in Fiji.Keywords Lower extremity amputation, Multiple-amputation, Risk factors, Statistical model, Ordinal logistics regression, Partial proportional odds model, Multinomial logistic regressionPartial proportional odds model for predicting multiple lower extremity amputation among T2DM patientsSabiha Khan 1,2* , Karuna Reddy 1 , Momtaz Ahmed 3 , Donald Wilson 2 and Bibhya Sharma 1