Evidence map›Paper›PMID 40252103›Full record

SynthesisActa diabetologica2025

Research progress on risk prediction models for the diabetic foot.

Haixia Qi, Tao Zhang, Lijie Hou, Qi Li, Ruiping Huang, Lihua Ma

Abstract readSystematic Review
In one paragraph

Synthesis in Acta diabetologica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Haixia Qi *School of Nursing, Lanzhou University, Lanzhou, 730011, China.
Tao Zhang *The 940 Hospital of Chinese People's Liberation Army, Lanzhou, 730050, China.
Lijie HouDepartment of Endocrinology, The First Hospital of Lanzhou University, Lanzhou, 730000, China.
Qi LiDepartment of Neurology, The First Hospital of Lanzhou University, Lanzhou, 730000, China.
Ruiping HuangDepartment of Endocrinology, The First Hospital of Lanzhou University, Lanzhou, 730000, China.
Lihua MaSchool of Nursing, Lanzhou University, Lanzhou, 730011, China. mlhfmmu@163.com.ORCID http://orcid.org/0000-0002-4066-7278

Funding

Innovative Research Group Project of the National Natural Science Foundation of China 72264022Lanzhou Science and Technology Bureau 2023-ZD-95Scientific Research Plan of the Health Industry in Gansu Province GSWSHL2021-05The First Hospital of Lanzhou University ldyyyn2022-97
6 · The paper itself

Abstract

objectiveThis study aimed to comprehensively review the latest advancements in diabetic foot risk prediction models over the past four years to address the severe challenges posed by diabetic foot ulcers, which are among the leading causes of disability and mortality among diabetic patients. Diabetic foot ulcers are characterized by their complex aetiology, pose a grave threat to life and impose enormous social and economic burdens, thus becoming a critical issue in public health that urgently requires attention. By accurately predicting the risk of diabetic foot and implementing early intervention strategies, this study aimed to reduce its incidence and mortality rates.

methodsThis study employed a systematic review and comprehensive analysis framework, conducted extensive searches of electronic databases (including PubMed, EMBASE, the Cochrane Library, CNKI, etc.) and supplemented these searches with manual literature collection to ensure comprehensive information coverage. During the literature screening and evaluation phase, strict adherence to the predetermined inclusion and exclusion criteria was maintained to guarantee the high quality of the included studies. Further detailed quality assessments, data extraction, and analysis of the selected literature were conducted, with a focus on exploring the construction strategies of risk prediction models, the selection of key variables, the evaluation indicators of model performance, and the validation methods.

resultsBy comparing and analysing the differences among studies in terms of methodology, model effectiveness, and practical application potential, this study summarized the development trends of diabetic foot risk prediction models and anticipated future research directions. These findings indicate that with the assistance of advanced diabetic foot risk prediction models, potential risk factors can be identified and addressed early on, thereby effectively reducing the incidence of diabetic foot and significantly improving patients' quality of life.

conclusionThis study revealed that diabetic foot risk prediction models have significant effects on accurately identifying risk factors and guiding early interventions, serving as effective tools to reduce the incidence of diabetic foot. Through early identification and intervention, the prognosis and quality of life of patients can be significantly improved, providing important references and guidance for the field of public health.

Indexed as

Diabetic FootHumansRisk AssessmentRisk FactorsDiabetesDiabetic foot ulcerHigh-risk diabetic footPrediction model

Identifiers

PMID40252103
PMCPMC12727708

What OpenQuestion holds

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Registered trials

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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.