Risk stratification of patients who present with chest pain and have normal troponins using a machine learning model

doi:10.4330/wjc.v14.i11.565

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Nov 26, 2022 (publication date) through Jul 28, 2024

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World Journal of Cardiology

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1949-8462

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Retrospective Cohort Study

World J Cardiol. Nov 26, 2022; 14(11): 565-575
Published online Nov 26, 2022. doi: 10.4330/wjc.v14.i11.565

Table 1 Demographics

Characteristics	Abnormal cardiac stress test requiring cardiac catheterization and/or CABG		Degree of association (95%CI)	P value
Characteristics	Yes, n = 245	No, n = 2083	Degree of association (95%CI)	P value
Age, mean ± SD	63.02 ± 11.67	61.99 ± 12.46	Mean different: 1.03 (-0.53, 2.59)	0.200
Sex male	153 (62.4%)	965 (46.3%)	RR: 1.8 (1.41, 2.30)	< 0.001
Race
Caucasian	163 (66.5%)	1182 (56.7%)	RR: 1.8 (1.08, 3.00)	0.020 (combined)
African American	65 (26.5%)	650 (31.2%)	RR: 1.35 (0.79, 2.32)
Asian	2 (0.8%)	43 (2.1%)	RR: 0.66 (0.16, 2.79)
Other	15 (6.1%)	208 (10.0%)	Reference

CABG: Coronary artery bypass graft; CI: Confidence interval; RR: Risk ratio; SD: Standard deviation.

Citation: Shafiq M, Mazzotti DR, Gibson C. Risk stratification of patients who present with chest pain and have normal troponins using a machine learning model. World J Cardiol 2022; 14(11): 565-575
URL: https://www.wjgnet.com/1949-8462/full/v14/i11/565.htm
DOI: https://dx.doi.org/10.4330/wjc.v14.i11.565