Evidence map›Paper›PMID 42157190›Full record

ArticleDiabetology & metabolic syndrome2026

Prediabetes and diabetes exacerbated cardiac systolic function in obese patients at the subclinical stage: insights from global longitudinal strain and myocardial work.

Kai Lu, Guang-An Li, Yan-Jiao Wang, Jun Huang

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Article in Diabetology & metabolic syndrome, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Kai Lu *Department of Radiology, The Affiliated Changzhou Second People's Hospital with Nanjing Medical University, Changzhou, 213003, China.
Guang-An Li *Department of Cardiovascular Ultrasound, The Affiliated Changzhou Second People's Hospital with Nanjing Medical University, Changzhou, 213003, China.
Yan-Jiao WangDepartment of Cardiovascular Ultrasound, The Affiliated Changzhou Second People's Hospital with Nanjing Medical University, Changzhou, 213003, China.
Jun HuangDepartment of Cardiovascular Ultrasound, The Affiliated Changzhou Second People's Hospital with Nanjing Medical University, Changzhou, 213003, China. 305669112@qq.com.

Funding

Municipal-level Top Talent in Health and Health Care 2025CZBJ002Science and Technology Project of Changzhou Health Commission ZD202342
6 · The paper itself

Abstract

aimsThis investigation aims to estimate the diagnostic value of global longitudinal strain (GLS) and myocardial work (MW) indices for the identification of subclinical left ventricular (LV) systolic impairment (SLVSI) in individuals with simple obesity, obesity and prediabetes, and obesity and type 2 diabetes mellitus (T2DM).

methodsThis investigation included 302 participants: 225 obese patients and 77 healthy individuals. LV GLS and MW-derived values, namely, the global constructive work (GCW), global work index (GWI), global wasted work (GWW), and global work efficiency (GWE), were analyzed. All individuals with obesity were classified into three groups: simple obesity, individuals with obesity and prediabetes, and individuals with obesity and T2DM. Comparisons of the LV GLS and MW were conducted among the four groups. The independent factors that affected the SLVSI in individuals with obesity were assessed using a logistic regression model. We conducted an ROC analysis to estimate the performance of MW in detecting SLVSI in individuals with obesity.

resultsSignificant differences were detected in the GWI, GCW, LV GLS, GWW, and GWE among normal controls, individuals with simple obesity, individuals with obesity and prediabetes, and individuals with obesity and T2DM (P < 0.05). The combination of the GCW, GWW, GWI, and GWE resulted in the best AUC (0.896) for the determination of SLVSI in individuals with obesity. After adjustment for confounders, prediabetes or T2DM was independently associated with an absolute LV GLS < 20% in obese individuals.

conclusionsIt is feasible to use LV GLS and MW-related parameters to determine SLVSI in individuals with obesity, individuals with obesity and prediabetes, and individuals with obesity and T2DM. Even in the preclinical stage prior to the onset of diabetes, prediabetes still has an incremental effect on SLVSI in obese patients.

Indexed as

GLSMWObesePrediabetesT2DM

Identifiers

PMID42157190
PMCPMC13317272

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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.