Evidence map›Paper›PMID 40184122›Full record

Observational studyMedicine2025

Construction of a predictive model for type 2 diabetes mellitus with coexisting hypertension: A cross-sectional study.

Huiling Zhang, Shuang Yu, Zheyuan Xia, Yahui Meng, Dezheng Zhu, Xiang Wang, Hui Shi

Abstract readObservational Study
In one paragraph

Observational study in Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Huiling ZhangSchool of Nursing, Anhui University of Traditional Chinese Medicine, Hefei, China.ORCID 0009-0008-0470-4183
Shuang YuSchool of Nursing, Anhui University of Traditional Chinese Medicine, Hefei, China.
Zheyuan XiaSchool of Nursing, Anhui University of Traditional Chinese Medicine, Hefei, China.
Yahui MengSchool of Nursing, Anhui University of Traditional Chinese Medicine, Hefei, China.
Dezheng ZhuSchool of Nursing, Anhui University of Traditional Chinese Medicine, Hefei, China.
Xiang WangSchool of Nursing, Anhui University of Traditional Chinese Medicine, Hefei, China.
Hui ShiSchool of Nursing, Anhui University of Traditional Chinese Medicine, Hefei, China.

Funding

Anhui Provincial Higher Education Quality Engineering Project: 2023jyxm0354 2023jyxm0354
6 · The paper itself

Abstract

Type 2 diabetes mellitus (T2DM) and hypertension often coexist, raising the risk of cardiovascular events, renal disease, and mortality. Early identification of high-risk patients with T2DM and concurrent HTN is vital for personalized care. This study aims to construct and validate a predictive model for hypertension in T2DM patients to aid early intervention and tailored treatment. A quantitative observational study using multivariable logistic regression analysis was conducted, with results presented in a nomogram. Data from 423 T2DM patients (206 with hypertension and 217 without) hospitalized at a tertiary hospital in Anhui Province between February 2023 and February 2024 were analyzed. Univariate and multivariate logistic regression identified significant predictors, and model performance was evaluated via ROC curves, AUC values, and the Hosmer-Lemeshow test. Age, alcohol use, diabetic nephropathy, coronary heart disease, cerebral infarction, and body mass index were significant predictors. The model showed good performance with an AUC of 0.72, and the Hosmer-Lemeshow test (P = .074) confirmed its fit. The predictive model effectively identifies high-risk T2DM patients for hypertension, aiding early intervention and personalized treatment.

Indexed as

Diabetes Mellitus, Type 2HypertensionAgedChinaCross-Sectional StudiesFemaleHumansLogistic ModelsMaleMiddle AgedNomogramsRisk AssessmentRisk FactorsROC Curve

Identifiers

PMID40184122
PMCPMC11709166

What Socratic holds

Textmetadata
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 Socratic graph.