Predicting Major Adverse Cardiovascular Events After Cardiac Surgery Using Combined Clinical, Laboratory, and Echocardiographic Parameters: A Machine Learning Approach.

Medicina (Kaunas) · 2025 · PMC12387864 · PMID 40870369

Europe PMC DOI

hedged sentences

0.0493

closest p · 1.0× alpha

0.0500

boldest claim

The sentences

borderline significancep = 0.0493actually significant

HDL cholesterol showed borderline significance (OR = 1.69, 95% CI: 1.00–2.87, p = 0.0493), suggesting a potentially complex relationship between lipid metabolism and postoperative cardiovascular outcomes.

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did not reach statistical significancep > 0.05actually significant

Other clinical, biochemical, and hemodynamic parameters—including BMI, creatinine, erythrocyte count, fibrinogen, troponin I, ejection fraction, and comorbidities (DM, HTA, COPD, previous myocardial infarction)—did not reach statistical significance in the univariate analysis (all p > 0.05).

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