Bibliographic Details
Title: |
Prediction model for recommending coronary artery calcium score screening (CAC-prob) in cardiology outpatient units: A development study. |
Authors: |
Wongyikul, Pakpoom, Tantraworasin, Apichat, Suwannasom, Pannipa, Srisuwan, Tanop, Wannasopha, Yutthaphan, Phinyo, Phichayut |
Source: |
PLoS ONE; 9/30/2024, Vol. 19 Issue 9, p1-15, 15p |
Subject Terms: |
CORONARY artery calcification, ESSENTIAL hypertension, MEDICAL screening, DISEASE risk factors, CHEST pain |
Abstract: |
Despite the well-established significance of the CAC score as a cardiovascular risk marker, the timing of using CAC score in routine clinical practice remains unclear. We aim to develop a prediction model for patients visiting outpatient cardiology units, which can recommend whether CAC score screening is necessary. A prediction model using retrospective cross-sectional design was conducted. Patients who underwent CAC score screening were included. Eight candidate predictors were preselected, including age, gender, DM or primary hypertension, angina chest pain, LDL-C (≥130 mg/dl), presence of low HDL-C, triglyceride (≥150 mg/dl), and eGFR. The outcome of interest was the level of CAC score (CAC score 0, CAC score 1–99, CAC score ≥100). The model was developed using ordinal logistic regression, and model performance was evaluated in terms of discriminative ability and calibration. A total of 360 patients were recruited for analysis, comprising 136 with CAC score 0, 133 with CAC score 1–99, and 111 with CAC score ≥100. The final predictors identified were age, male gender, presence of hypertension or DM, and low HDL-C. The model demonstrated excellent discriminative ability (Ordinal C-statistics of 0.81) with visually good agreement on calibration plots. The implementation of this model (CAC-prob) has the potential to enhance precision in recommending CAC screening. However, external validation is necessary to assess its robustness in new patient cohorts. [ABSTRACT FROM AUTHOR] |
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Database: |
Complementary Index |
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