Anesthesia and analgesia · 2025
Diastolic Versus Systolic or Mean Intraoperative Hypotension as Predictive of Perioperative Myocardial Injury in a White-Box Machine-Learning Model.
СтатьяНаблюдательное исследованиеСравнительное исследованиеНазвание и аннотация: Перевод в очереди
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Valadkhani Arman, Gupta Anil, Cauli Giordano, Nordström Johan L, Rohi Ayda, Tufexis Panos, Hällsjö Sander Caroline, Jacobsson Martin, Bell Max
Аннотация
BACKGROUND: Intraoperative hypotension (IOH) and tachycardia are associated with perioperative myocardial injury (PMI), and thereby increased postoperative mortality. Patients undergoing vascular surgery are specifically at risk of developing cardiac complications. This study aimed to explore the association between different thresholds for IOH and tachycardia, and PMI. It also aimed to explore which threshold for IOH and tachycardia best predicts PMI.
METHODS: In this single-center prospective observational study, high-sensitivity cardiac troponin T was measured preoperatively and at 4, 24, and 48 hours after vascular surgery. Absolute and relative thresholds were used to define intraoperative systolic, mean, and diastolic arterial hypotension, measured every 15 seconds by invasive arterial pressure monitoring and heart rate using the Philips IntelliVue X3 monitor. Decision tree machine-learning (ML) models were used to explore which thresholds for IOH and tachycardia best predict PMI. Clinical utility and transparency were prioritized over maximizing the performance of the ML model and therefore a white-box model was used.
RESULTS: In all, 498 patients were included in the study. Ninety-nine patients (20%) had PMI. Significant associations were found between IOH and PMI using both absolute and relative thresholds for systolic, mean, and diastolic arterial pressure. Absolute thresholds based on diastolic arterial pressure had the strongest correlation with PMI and yielded greater statistical significance. The threshold that was most predictive of PMI was an absolute diastolic arterial pressure <44 mm Hg. The prediction model with the absolute threshold of diastolic arterial pressure <44 mm Hg had a macro average F1 score of 0.67 and a weighted average F1 score of 0.76. No association was found between tachycardia and PMI.
CONCLUSIONS: We found that an absolute, not relative, IOH threshold based on diastolic arterial pressure, and not systolic or mean arterial pressure, or tachycardia, was most predictive of PMI.
METHODS: In this single-center prospective observational study, high-sensitivity cardiac troponin T was measured preoperatively and at 4, 24, and 48 hours after vascular surgery. Absolute and relative thresholds were used to define intraoperative systolic, mean, and diastolic arterial hypotension, measured every 15 seconds by invasive arterial pressure monitoring and heart rate using the Philips IntelliVue X3 monitor. Decision tree machine-learning (ML) models were used to explore which thresholds for IOH and tachycardia best predict PMI. Clinical utility and transparency were prioritized over maximizing the performance of the ML model and therefore a white-box model was used.
RESULTS: In all, 498 patients were included in the study. Ninety-nine patients (20%) had PMI. Significant associations were found between IOH and PMI using both absolute and relative thresholds for systolic, mean, and diastolic arterial pressure. Absolute thresholds based on diastolic arterial pressure had the strongest correlation with PMI and yielded greater statistical significance. The threshold that was most predictive of PMI was an absolute diastolic arterial pressure <44 mm Hg. The prediction model with the absolute threshold of diastolic arterial pressure <44 mm Hg had a macro average F1 score of 0.67 and a weighted average F1 score of 0.76. No association was found between tachycardia and PMI.
CONCLUSIONS: We found that an absolute, not relative, IOH threshold based on diastolic arterial pressure, and not systolic or mean arterial pressure, or tachycardia, was most predictive of PMI.