Development and validation of a prediction model for amputation risk in patients with diabetic foot ulcers based on systematic review and meta-analysis
Bibliographic record
Abstract
Objective To develop and validate a prediction model for risk of amputation in patients with diabetic foot ulcers (DFU) based on systematic review and meta-analysis. Methods The studies on the risk factors of amputation in DFU patients was retrieved by using subject words+free words. After screening, 37 cohort studies were finally included, and the Newcastle-Ottawa scale (NOS) was used for quality evaluation. Meta-analysis was performed on the risk factors of amputation in DFU. Then a prediction model for DFU amputation risk were constructed based on the statistically significant risk factors in the meta-analysis. The corresponding β value was calculated based on the combined odds ratio (OR) value of each risk factor, and each risk factor was scored to establish a scoring system model. The clinical data of 453 DFU patients hospitalized in our department from 2021 to 2023 were collected as a validation cohort. Receiver operating characteristic (ROC) curve analysis was used to evaluate the model performance. The area under the curve (AUC) was calculated, and the optimal cutoff score was determined by calculation of the maximum Youden index through sensitivity and specificity. Results Our meta-analysis showed a cumulative amputation rate of approximately 34.65% in 11 779 DFU patients. The final risk prediction models include gangrene [OR=11.92 (5.86~24.24)], ulcer depth [OR=4.93 (2.52~9.64)], osteomyelitis [OR=3.19 (2.36~4.29)], previous amputation history [OR=3.19 (2.00~5.09)] and lower extremity arterial disease [OR=3.10 (2.31~4.17)]. According to the weights of each risk factor, the total score of the model is 76, and the optimal cut-off score is 36.5. The prediction model performed well, with an AUC value of 0.864 (0.824, 0.903), a sensitivity of 0.743, a specificity of 0.859, and an accuracy rate of 83.00%. Conclusion A prediction model for DFU amputation risk is developed based on risk factor scoring, and has good discrimination and calibration, providing effective scientific basis for clinical research and clinical decision-making related to DFU amputation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".