ArticleActa diabetologica2025
Development and validation of prediction model for stage I patients with lower extremity atherosclerotic disease in type 2 diabetes mellitus in China.
Article in Acta diabetologica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
- Erratum issued
Authors and funding
8 authors.
Funding
Abstract
aimsLower extremity atherosclerotic disease (LEAD) is the primary cause of ulcers, gangrene, and amputations in patients with type 2 diabetes mellitus (T2DM), stage I is the crucial time for prevention and intervention to improve the prognosis of T2DM-LEAD. The purpose of this study was to develop and validate a personalized predictive model to determine the risk of outcomes in stage I patients with T2DM-LEAD.
methodsThere were 1603 stage I patients with T2DM-LEAD at baseline in this retrospective study. Least absolute shrinkage and selection operator regression was applied to filter predictive variables. Cox regression was used to construct a nomogram prediction model. The model's 3-year and 5-year predictive performance was evaluated in terms of its discrimination, calibration, and clinical utility using the area under the receiver operating characteristic curve, calibration curve, decision curve analysis, respectively.
resultsPatients were randomly divided into a development cohort (n = 1122) and a validation cohort (n = 481). Age, cerebrovascular diseases, diabetic kidney disease, diabetic retinopathy, low-density lipoprotein cholesterol, fibrinogen, D-dimer and anti-platelet drugs were selected as predictive factors. The model presented moderate discrimination in development and validation sets with AUCs of 70.3 (95% CI: 65.2-75.3) and 70.1 (95% CI: 64.5-75.7) for the 3-year prediction. Andthe AUC values for the 5-year prediction in development and validation sets were 72.8 (95% CI: 67.6-78.1) and 75.9 (95% CI: 69.0-82.8), respectively. The calibration curve for the 3-year and 5-year predictions demonstrated good agreement between the predicted and actual probabilities, and decision curve analysis showed a wide range of beneficial clinical utility.
conclusionThe prediction model can identify the risk of stage I patients with T2DM-LEAD who are likely to develop outcomes events within 3 years and 5 years. It is valuable for clinical decisions and helps healthcare providers and policy makers to develop more personalized clinical treatment strategies, which has significant public health implications.
Indexed as
Identifiers
40293474What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.