Evidence map›Paper›PMID 40131908›Full record

ArticlePloS one2025

Analysis of the incidence and influencing factors of high-risk foot in elderly patients with type 2 diabetes in a community in Beijing.

Gaoqiang Li, Qian Lu, Bing Wen, Huijuan Li, Jin Liu, Yanming Ding

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Review
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.

Gaoqiang LiRespiratory and Critical Care Medicine Department, Second Medical Center of Chinese People's Liberation Army General Hospital, Beijing, China.
Qian LuDepartment of Surgical Nursing, School of Nursing, Peking University Health Science Center, Beijing, China.ORCID 0000-0003-2611-3284
Bing WenPlastic Surgery and Burn Department, Peking University First Hospital, Beijing, China.
Huijuan LiPlastic Surgery and Burn Department, Peking University First Hospital, Beijing, China.
Jin LiuPlastic Surgery and Burn Department, Peking University First Hospital, Beijing, China.
Yanming DingChinese Nursing Association, Beijing, China.ORCID 0009-0000-0918-2128

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiabetic foot is one of the important causes of disability and death in diabetic patients, and effective measures can reduce or prevent the occurrence of diabetic foot, among which, the screening of diabetic high-risk foot helps to identify the risk groups that may progress to diabetic foot, and targeted intervention for this group of people can effectively reduce the prevalence of diabetic foot and the incidence of adverse consequences.

objectiveTo investigate the occurrence of high-risk foot with type 2 diabetes in elderly people in a community in Beijing and analyze its influencing factors, so as to provide evidence for preventing the occurrence of diabetic foot.

methods269 elderly patients with type 2 diabetes in Xinjiekou community of Beijing were selected for foot examination by convenient sampling, and the high-risk foot was classified according to the international Diabetic Foot Working Group grading system.

resultsThe detection rate of high risk foot of type 2 diabetes was 51.7%. Binary Logistic regression analysis showed that age, glycosylated hemoglobin, hyperlipidemia, insulin therapy, and diabetic retinopathy were independent influencing factors for the occurrence of diabetic High-risk foot.

conclusionThe incidence of high-risk foot in elderly type 2 diabetes patients is high in this community. Community health care workers should pay attention to elderly diabetic patients with hyperlipidemia, insulin therapy, high glycated hemoglobin, and diabetic retinopathy to reduce the occurrence of foot ulcers.

Indexed as

Diabetes Mellitus, Type 2Diabetic FootAgedAged, 80 and overBeijingFemaleHumansIncidenceMaleMiddle AgedRisk Factors

Identifiers

PMID40131908
PMCPMC11936230

What Socratic holds

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LicenceCC BY
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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 Socratic graph.