Evidence map›Paper›PMID 33019409›Full record

ArticleMedicine2020

Establishment of a diagnostic model of coronary heart disease for patients with diabetic foot.

Ying Chen, Liwei Meng, Liangchen Wang, Li Xiao, Caizhe Yang

Open access · goldAbstract read
In one paragraph

Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 39% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 1 institution in 1 country.

Ying ChenDepartment of Endocrinology of the Air Force Medical Center, PLA.
Liwei MengDepartment of Endocrinology of the Xiangyang District People's Hospital of Xiangyang City, China.
Liangchen WangDepartment of Endocrinology of the Air Force Medical Center, PLA.
Li XiaoDepartment of Endocrinology of the Air Force Medical Center, PLA.
Caizhe YangDepartment of Endocrinology of the Air Force Medical Center, PLA.ORCID 0000-0002-1508-5890
Xiangyang Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to establish a diagnostic model of coronary heart disease (CHD) for diabetic foot (DF) patients.The clinical data of 489 hospitalized patients with DF were retrospectively analyzed in this case-control study. The patients were divided into the CHD group (DF with CHD, n = 212) and the control group (DF without CHD, n = 277). Univariate analysis was performed to screen for CHD-related risk factors, and multivariate logistic regression analysis was conducted to determine significant CHD risk factors. Scores were assigned according to the ratio of risk factors (OR) to establish a diagnostic model of CHD for patients with DF. The area under the ROC curve was used to test the application value of the diagnostic model.The logistic regression analysis showed that the risk factors for CHD in DF patients were age, duration of diabetes, toe-brachial index, hyperuricemia, and chronic renal insufficiency. The area under the ROC curve of the diagnostic model was 0.798 (0.759-0.837), the diagnostic point of CHD was 6 points, the diagnostic sensitivity was 69.3%, and the specificity was 76.5%.The established model has good diagnostic value and provides the basis for preliminary screening for CHD in patients with DF.

Indexed as

AdultAgedAged, 80 and overAge FactorsAnkle Brachial IndexCase-Control StudiesCoronary DiseaseDiabetic FootFemaleHumansHyperuricemiaLogistic ModelsMaleMiddle AgedRenal Insufficiency, ChronicRetrospective Studies

Identifiers

PMID33019409
PMCPMC7535636
OpenAlexW3091073227

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.