Prognostic value of heart rate variability for risk of serious adverse events in continuously monitored hospital patients

• Published in: Journal of clinical monitoring and computing 2024-12, Vol.38 (6), p.1315-1329
• Main Authors: Aagaard, Nikolaj, Olsen, Markus Harboe, Rasmussen, Oliver Wiik, Grønbaek, Katja K., Mølgaard, Jesper, Haahr-Raunkjaer, Camilla, Elvekjaer, Mikkel, Aasvang, Eske K., Meyhoff, Christian S.
• Format: Article
• Language: English
• Subjects: Adult; Aged; Aged, 80 and over; Anesthesiology; Area Under Curve; Confidence intervals; Critical Care Medicine; Electrocardiography - methods; Female; Health Sciences; Heart Rate; Humans; Intensive; Male; Medicine; Medicine & Public Health; Middle Aged; Monitoring; Monitoring, Physiologic - methods; Mortality; Original Research; Predictive control; Predictive Value of Tests; Prognosis; Prospective Studies; ROC Curve; Statistics for Life Sciences; Subgroups; Telemedicine; Thresholds; Vital Signs
• ISSN: 1387-1307; 1573-2614; 1573-2614
• DOI: 10.1007/s10877-024-01193-8

Technological advances allow continuous vital sign monitoring at the general ward, but traditional vital signs alone may not predict serious adverse events (SAE). This study investigated continuous heart rate variability (HRV) monitoring’s predictive value for SAEs in acute medical and major surgical patients. Data was collected from four prospective observational studies and two randomized controlled trials using a single-lead ECG. The primary outcome was any SAE, secondary outcomes included all-cause mortality and specific non-fatal SAE groups, all within 30 days. Subgroup analyses of medical and surgical patients were performed. The primary analysis compared the last 24 h preceding an SAE with the last 24 h of measurements in patients without an SAE. The area under a receiver operating characteristics curve (AUROC) quantified predictive performance, interpretated as low prognostic ability (0.5–0.7), moderate prognostic ability (0.7–0.9), or high prognostic ability (> 0.9). Of 1402 assessed patients, 923 were analysed, with 297 (32%) experiencing at least one SAE. The best performing threshold had an AUROC of 0.67 (95% confidence interval (CI) 0.63–0.71) for predicting cardiovascular SAEs. In the surgical subgroup, the best performing threshold had an AUROC of 0.70 (95% CI 0.60–0.81) for neurologic SAE prediction. In the medical subgroup, thresholds for all-cause mortality, cardiovascular, infectious, and neurologic SAEs had moderate prognostic ability, and the best performing threshold had an AUROC of 0.85 (95% CI 0.76–0.95) for predicting neurologic SAEs. Predicting SAEs based on the accumulated time below thresholds for individual continuously measured HRV parameters demonstrated overall low prognostic ability in high-risk hospitalized patients. Certain HRV thresholds had moderate prognostic ability for prediction of specific SAEs in the medical subgroup.