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July 10, 2026PeerJOpen Access

A 7-predictor nomogram accurately predicts multivessel disease risk in CAD with an AUC of 0.84.

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Why the study?

Can a nomogram integrating cardiac function parameters and clinical features accurately predict multivessel disease in patients with coronary artery disease?

Population

353 patients with angiographically confirmed coronary artery disease at Guangzhou Red Cross Hospital

Design

Cohort, Randomly assigned to training (70%) and validation (30%) sets

Key result

A 7-predictor nomogram accurately predicted multivessel disease risk in patients with coronary artery disease, achieving an AUC of 0.84 (95% CI 0.79-0.90) in the training set.

Authors

AHAibao HuangGYGuangdong YanMYMengying Yu

Discussion

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Overview

Nomogram may aid MVD risk stratification in CAD; leaves open prospective validation before clinical adoption.

Key Points

  • Develop and validate a nomogram that predicts the risk of multivessel disease in patients with coronary artery disease using cardiac function and clinical features.
  • Retrospective analysis of clinical data from 353 patients with coronary artery disease.
  • Patients divided into training (70%) and validation (30%) sets for model development and assessment.
  • LASSO regression and multivariate logistic regression were employed to identify risk factors and construct the nomogram.
  • Seven predictors integrated into the nomogram: age, gender, prior stent implantation, total cholesterol, left ventricular ejection fraction, high-density lipoprotein, and albumin.
  • AUC of 0.84 (95% CI [0.79–0.90]) in training set and 0.79 (95% CI [0.68–0.89]) in validation set, indicating good discrimination.
  • Nomogram effectively stratified patients into high-risk (≥191) and low-risk (<191) groups, with significant differences (P < 0.001) in score distributions between MVD and non-MVD groups.

Study Design

Type

Observational (n=353)

Multicenter

No

Structured PICO

Can a nomogram integrating cardiac function parameters and clinical features accurately predict multivessel disease in patients with coronary artery disease?

P
Population
353 patients with angiographically confirmed coronary artery disease retrospectively analyzed to develop and validate a nomogram for predicting multivessel disease.
E
Exposure
Nomogram model integrating age, gender, prior stent implantation, total cholesterol, left ventricular ejection fraction (LVEF), high-density lipoprotein, and albumin
O
Outcome
Prediction of multivessel disease (MVD)surrogate

Main Result

Effect estimate: AUC 0.84 (95% CI 0.79-0.90)

p-value: p=< 0.001

A nomogram integrating clinical and cardiac function parameters provides an accurate, non-invasive tool for predicting multivessel disease risk in CAD patients.

Cite This Study

Huang et al. (2026) conducted an observational in Coronary artery disease (n=353). Nomogram model (age, gender, prior stent, total cholesterol, LVEF, HDL, albumin) was evaluated on Prediction of multivessel disease (MVD) risk (AUC 0.84, 95% CI 0.79-0.90, p=< 0.001). A 7-predictor nomogram accurately predicted multivessel disease risk in patients with coronary artery disease, achieving an AUC of 0.84 (95% CI 0.79-0.90) in the training set.

synapsesocial.com/papers/6a508df96eeac72a437a1267https://doi.org/10.7717/peerj.21517
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