SynthesisPeerJ2024
Performance of risk prediction models for diabetic foot ulcer: a meta-analysis.
Synthesis in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Research progress on risk prediction models for the diabetic foot.Acta diabetologica · 2025Pooled it
- Risk factors and predictive models for perioperative acute kidney injury in children: a narrative review.Translational pediatrics · 2026Review
- Machine Learning Analysis of Retrospective Data From 503 Hospitalized Older Patients With Type 2 Diabetes to Identify Factors Associated With Cognitive Impairment.Medical science monitor : international medical journal of experimental and clinical research · 2026Article
- Impact of Cilostazol versus Cilostazol and Selenium Combination on The Healing of Diabetic Foot Ulcer Patients: A Randomized Controlled Trial.Diabetology & metabolic syndrome · 2026Article
- Development and validation of a diagnostic nomogram for Wagner grade≥2 diabetic foot ulcers in hospitalized patients with type 2 diabetes.Frontiers in endocrinology · 2026Article
- Development and validation of a nomogram model for predicting diabetic foot in type 2 diabetes.PeerJ · 2026Article
- A Parsimonious Four-Variable Nomogram for Predicting Lower-Extremity Amputation in Patients with Type 2 Diabetes and Diabetic Foot Ulcers: Development and Internal Validation Using Dual-Method Stability-Based Variable Selection.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026Article
- Mortality predictors and survival nomogram for hospitalized diabetic foot patients: a decade-long cohort.Frontiers in endocrinology · 2026Article
- Understanding risk factors and prognosis in diabetic foot ulcers.Open life sciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Background: The number of prediction models for diabetic foot ulcer (DFU) risk is increasing, but their methodological quality and clinical applicability are uncertain. We conducted a systematic review to assess their performance. Methods: We searched PubMed, Cochrane Library, and Embase databases up to 10 February 2024 and extracted relevant information from selected prediction models. The Prediction model Risk Of Bias ASsessment Tool (PROBAST) checklist was used to assess bias risk and applicability. All statistical analyses were conducted in Stata 14.0. Results: Initially, 13,562 studies were retrieved, leading to the inclusion of five development and five validation models from eight studies. DFU incidence ranged from 6% to 16.8%, with age and hemoglobin A1C (HbA1c) commonly used as predictive factors. All included studies had a high risk of bias, mainly due to disparities in population characteristics and methodology. In the meta-analysis, we observed area under the curve (AUC) values of 0.78 (95% CI [0.69-0.89]) for development models and 0.84 (95% CI [0.79-0.90]) for validation models. Conclusion: DFU risk prediction models show good overall accuracy, but there is a risk of bias. Adherence to the PROBAST checklist is crucial for improving their clinical applicability.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.