Evidence mapPaperPMID 40084147Full record

ArticleFrontiers in endocrinology2025

Development and validation of a risk prediction model for 30-day readmission in elderly type 2 diabetes patients complicated with heart failure: a multicenter, retrospective study.

Yuxin He, Yuan Yuan, Qingzhu Tan, Xiao Zhang, Yunyu Liu, Minglun Xiao

Abstract readMulticenter StudyValidation Study
In one paragraph

Article in Frontiers in endocrinology, 2025. 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
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

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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

2 citing papers in PubMed.

  1. Article
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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.

Yuxin HeDepartment of Medical Administration, Affiliated Banan Hospital of Chongqing Medical University, Chongqing, China.
Yuan YuanMedical Recorods Department, Women and Children's Hospital of Chongqing Medical University, Chongqing Health Center for Women and Children, Chongqing, China.
Qingzhu TanMedical Records and Statistics Room, Affiliated Banan Hospital of Chongqing Medical University, Chongqing, China.
Xiao ZhangMedical Records and Statistics Room, Affiliated Banan Hospital of Chongqing Medical University, Chongqing, China.
Yunyu LiuMedical Insurance Department, Affiliated Banan Hospital of Chongqing Medical University, Chongqing, China.
Minglun XiaoDepartment of Gerontology, Affiliated Banan Hospital of Chongqing Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Elderly type 2 diabetes mellitus (T2DM) patients complicated with heart failure (HF) exhibit a high rate of 30-day readmission. Predictive models have been suggested as tools for identifying high-risk patients. Thus, we aimed to develop and validate a predictive model using multicenter electronic medical records (EMRs) data to estimate the risk of 30-day readmission in elderly T2DM patients complicated with HF. Methods: EMRs data of elderly T2DM patients complicated with HF from five tertiary hospitals, spanning 2012 to 2023, were utilized to develop and validate the 30-day readmission model. The model were evaluated using holdout data with the area under the receiver operating characteristic curve (AUROC), calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). Results: A total of 1899 patients were included, with 955, 409, and 535 in the derivation, internal validation, and external validation cohorts, respectively. Pulmonary infections (odds ratio [OR]: 3.816, 95% confidence interval [CI]: 2.377-6.128, Conclusion: A 30-day readmission risk prediction model was developed and externally validated. This model facilitates the targeting of interventions for elderly T2DM patients complicated with HF who are at high risk of an early readmission.

Indexed as

Diabetes Mellitus, Type 2Heart FailurePatient ReadmissionAgedAged, 80 and overElectronic Health RecordsFemaleHumansMalePrognosisRetrospective StudiesRisk AssessmentRisk Factors30-day readmissionelectronic medical recordsheart failureprediction modeltype 2 diabetes mellitus

Identifiers

PMID40084147
PMCPMC11903290

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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.