Evidence map›Paper›PMID 39030503›Full record

ArticleBMC cardiovascular disorders2024

A nomogram for predicting CRT response based on multi-parameter features.

Yuxuan Lou, Yang Hua, Jiaming Yang, Jing Shi, Lei Jiang, Yang Yang

Abstract read
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Article in BMC cardiovascular disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yuxuan Lou *Southeast University, Nanjing, 210009, Jiangsu, China.
Yang Hua *Department of Cardiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
Jiaming Yang *Department of Cardiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
Jing ShiDepartment of Cardiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
Lei JiangDepartment of Cardiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
Yang YangDepartment of Cardiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China. yangyang@jsph.org.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo construct a nomogram for predicting the responsiveness of cardiac resynchronization therapy (CRT) in patients with chronic heart failure and verify its predictive efficacy.

methodA retrospective study was conducted including 109 patients with chronic heart failure who successfully received CRT from January 2018 to December 2022. According to patients after six months of the CRT preoperative improving acuity in the left ventricular ejection fraction is 5% or at least improve grade 1 NYHA heart function classification, divided into responsive group and non-responsive group. Clinical data of patients were collected, and LASSO regression analysis and multivariate logistic regression analysis were used to explore relative factors. A nomogram was constructed, and the predictive performance of the nomogram was evaluated using the calibration curve and decision curve analysis (DCA).

resultsAmong the 109 patients, 61 were assigned to the CRT-responsive group, while 48 were assigned to the non-responsive group. LASSO regression analysis showed that left ventricular end-systolic volume, diffuse fibrosis, and left bundle branch block (LBBB) were independent factors for CRT responsiveness in patients with heart failure (P < 0.05). Based on the above three predictive factors, a nomogram was constructed. The ROC curve analysis showed that the area under the curve (AUC) was 0.865 (95% CI 0.794-0.935). The calibration curve analysis showed that the predicted probability of the nomogram is consistent with the actual occurrence rate. DCA showed that the line graph model has an excellent clinical net benefit rate.

conclusionThe nomogram constructed based on clinical features, laboratory, and imaging examinations in this study has high discrimination and calibration in predicting CRT responsiveness in patients with chronic heart failure.

Indexed as

Cardiac Resynchronization TherapyHeart FailureNomogramsPredictive Value of TestsStroke VolumeVentricular Function, LeftAgedChronic DiseaseClinical Decision-MakingDecision Support TechniquesFemaleHumansMaleMiddle AgedRecovery of FunctionRetrospective StudiesCardiac resynchronization therapy (CRT)Heart failureMultiparameter featuresNomogram

Identifiers

PMID39030503
PMCPMC11264749

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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.