Admission-Time Prediction of In-Hospital Major Amputation in Diabetes-Related Foot Disease: Model Development and Temporal Validation Study

Background Major above-ankle amputation is a devastating outcome of diabetes-related foot disease. The Wagner classification is routinely available but places many inpatients in the same grade; few prediction models for major amputation have undergone temporal validation or reported calibration. Objective This study aimed to develop an admission-time model for in-hospital major amputation from routinely collected data and to validate it internally in a later period at the same center. Its intended role is to support prognostic communication and prioritization of early multidisciplinary and vascular assessment and not to inform the decision to amputate. Secondary objectives were to compare machine learning algorithms with penalized logistic regression and to assess the added value of segmental limb pressures. Methods In this retrospective cohort study at a tertiary center in Taiwan, adults with a single hospitalization for diabetes-related foot disease from 2015 through 2025 were divided by admission date into a development cohort (2015-2021) and a temporal test cohort (2022-2025). Twenty admission variables were modeled. Five algorithms were compared by nested cross-validation in the development cohort; the one with the lowest out-of-fold log loss became the primary model, with operating thresholds fixed before a single evaluation in the test cohort. Results The development cohort included 1400 patients with 126 (9.0%) major amputations and the test cohort 771 patients with 51 (6.6%). In the test cohort, the primary ridge logistic regression model had an area under the receiver operating characteristic curve (AUROC) of 0.882 (95% CI 0.841-0.917) vs 0.804 (95% CI 0.737-0.867) for Wagner grade alone. Absolute risk was overpredicted: mean predicted risk was 9.6% vs 6.6% observed, with calibration intercept –0.47, slope 1.33, and observed-to-expected ratio 0.69 (95% CI 0.53-0.86). At the prespecified screening threshold, 343 (44.5%) patients were flagged; sensitivity was 0.980 (95% CI 0.897-0.997), specificity 0.593 (95% CI 0.557-0.628), positive predictive value 14.6% (95% CI 11.2%-18.7%), and negative predictive value 0.998 (95% CI 0.987-1.000). Of 771 patients, no major amputation occurred among the 396 (51.4%) patients in the lowest risk band; of 54 patients, 22 (40.7%) patients in the highest band underwent major amputation. Random forest and gradient boosting reached higher AUROCs (0.915 and 0.912) in secondary comparisons. Segmental limb pressures did not clearly improve discrimination in complete cases (change in AUROC –0.004). Conclusions In an internal temporal validation at a single center, a transparent model based on routine admission data added discrimination for in-hospital major amputation beyond Wagner grade alone but overpredicted absolute risk. It estimates amputation under 1 institution’s care pathway and was not compared with multidimensional classifications such as Wound, Ischemia, and foot Infection; whether acting on it improves outcomes is untested. Independent external validation, recalibration where needed, and prospective evaluation are required before clinical use; the model must not be used to indicate amputation or withhold limb-salvage evaluation.