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Table. 3.

Table. 3.

Logistic regression analysis for predicting AVS according to the VAF

Model VAF≥0.5% VAF≥1% VAF≥2%
OR (95% CI) P§ OR (95% CI) P OR (95% CI) P
Model 1* 1.19 (0.65–2.19) 0.570 2.43 (1.20–4.94) 0.014 3.62 (1.20–10.93) 0.022
Model 2 1.03 (0.52–2.04) 0.927 2.44 (1.11–5.36) 0.027 3.86 (1.19–12.56) 0.025
IPTW cohort 1.00 (0.64–1.57) 0.987 2.45 (1.47–4.08) <0.001 5.13 (2.28–11.58) <0.001

*Model 1 was adjusted for age and sex.

Model 2 was adjusted for model 1 plus hypertension, diabetes mellitus, dyslipidemia, previous stroke, glomerular filtration rate, high-density lipoprotein, C-reactive protein, NT-proBNP, septal e′, septal E/e′, and the left-atrial volume index.

The IPTW model was adjusted for hypertension, diabetes mellitus, dyslipidemia, previous stroke, body mass index, hemoglobin, glomerular filtration rate, high-density lipoprotein, and C-reactive protein.

§P<0.05.

Abbreviations: AVS, aortic valve sclerosis; VAF, variant allele frequency; OR, odds ratio; IPTW, inverse-probability treatment weighting; NT-proBNP, N-terminal prohormone of brain natriuretic peptide; E/e′, comparative rate of peak velocity of early trans-mitral inflow against the early diastolic velocity at the mitral annulus.

Ann Lab Med 2024;44:279~288 https://doi.org/10.3343/alm.2023.0268

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