ArticleESC heart failure2021
A predictive model for dilated cardiomyopathy with pulmonary hypertension.
Article in ESC heart failure, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- An optimized plasmalogen modulating dietary supplement provides greater protection in a male than female mouse model of dilated cardiomyopathy.Journal of molecular and cellular cardiology plus · 2025Article
- A predictive model for depression risk in individuals with hypertension: evidence from NHANES 2007-2020.BMC public health · 2025Article
- Association between comorbid COPD or chronic bronchitis and the prognosis of patients with Dilated cardiomyopathy.Annals of medicine · 2024Article
- Identification of Zip8-correlated hub genes in pulmonary hypertension by informatic analysis.PeerJ · 2023Article
- Stress Reactivity, Susceptibility to Hypertension, and Differential Expression of Genes in Hypertensive Compared to Normotensive Patients.International journal of molecular sciences · 2022Article
- A predictive model for dilated cardiomyopathy with pulmonary hypertension.ESC heart failure · 2021Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsDilated cardiomyopathy (DCM) is defined as a serious cardiac disorder caused by the presence of left ventricular dilatation and contractile dysfunction in the absence of severe coronary artery disease and abnormal loading conditions. The incidence of cardiac death is markedly higher in patients with DCM with pulmonary hypertension (PH) than in DCM patients without PH. No previous studies have constructed a predictive model to predict PH in patients with DCM.
methodsData from 218 DCM patients (68.3% man; mean age 57.33) were collected. Patients were divided into low, intermediate and high PH-risk groups based on the echocardiographic assessment at the tricuspid regurgitation peak velocity (TRV) in conjunction with the presence of echocardiographic signs from at least two different categories. Basic information, vital signs, comorbidities and biochemical data of each patient were determined. The impact of each parameter on PH probability was analysed by univariable and multivariable analyses, the data from which were employed to establish a predictive model. Finally, the discriminability, calibration ability and clinical efficacy of the model were verified for both the modelling group and the external validation group.
resultsWe successfully applied a history of chronic obstructive pulmonary disease (COPD) or chronic bronchitis, systolic murmur (SM) at the tricuspid area, SM at the apex and brain natriuretic peptide (BNP) level to establish a model for predicting PH probability in DCM. The model was proven to have high accuracy and good discriminability (area under the receiver operating characteristic curve 0.889), calibration ability and clinical application value.
conclusionsA model for predicting PH probability in patients with DCM was successfully established. The new model is reliable for predicting PH probability in DCM and has good clinical applicability.
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