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Establishment and verification of a nomogram that predicts the risk for coronary slow flow

Coronary slow flow (CSF) has gained significance as a chronic coronary artery disease, but few studies have integrated both biological and anatomical factors for CSF assessment. This study aimed to develop and validate a simple-to-use nomogram for predicting CSF risk by combining biological and anat...

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Published in:Frontiers in endocrinology (Lausanne) 2024-03, Vol.15, p.1337284-1337284
Main Authors: Yu, Jiang, Ran, Yangshan, Yi, Dan, Yang, Chengyu, Zhou, Xiang, Wang, Sibin, Li, Hao, Yu, Wensi, Sun, Zhijun, Zhang, Zhengbo, Yan, Muyang
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container_title Frontiers in endocrinology (Lausanne)
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creator Yu, Jiang
Ran, Yangshan
Yi, Dan
Yang, Chengyu
Zhou, Xiang
Wang, Sibin
Li, Hao
Yu, Wensi
Sun, Zhijun
Zhang, Zhengbo
Yan, Muyang
description Coronary slow flow (CSF) has gained significance as a chronic coronary artery disease, but few studies have integrated both biological and anatomical factors for CSF assessment. This study aimed to develop and validate a simple-to-use nomogram for predicting CSF risk by combining biological and anatomical factors. In this retrospective case-control study, 1042 patients (614 CSF cases and 428 controls) were randomly assigned to the development and validation cohorts at a 7:3 ratio. Potential predictive factors were identified using least absolute shrinkage and selection operator regression and subsequently utilized in multivariate logistic regression to construct the nomogram. Validation of the nomogram was assessed by discrimination and calibration. N-terminal pro brain natriuretic peptide, high density lipoprotein cholesterol, hemoglobin, left anterior descending artery diameter, left circumflex artery diameter, and right coronary artery diameter were independent predictors of CSF. The model displayed high discrimination in the development and validation cohorts (C-index 0.771, 95% CI: 0.737-0.805 and 0.805, 95% CI: 0.757-0.853, respectively). The calibration curves for both cohorts showed close alignment between predicted and actual risk estimates, demonstrating improved model calibration. Decision curve analysis suggested high clinical utility for the predictive nomogram. The constructed nomogram accurately and individually predicts the risk of CSF for patients with suspected CSF and may be considered for use in clinical care.
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subjects Calibration
Cardiovascular Physiological Phenomena
Case-Control Studies
coronary angiography
coronary slow flow
diagnosis
Endocrinology
Humans
nomogram
Nomograms
prediction
Retrospective Studies
title Establishment and verification of a nomogram that predicts the risk for coronary slow flow
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