Predicting Hypertensive Events with Time-Series Analysis of Mean Arterial Pressure.

We investigated whether a statistical model used previously to predict hypotension from mean arterial pressure (MAP) time series analysis could predict hypertension. We performed a retrospective analysis of minute-by-minute MAP records from two cohorts of intensive care unit (ICU) patients. The first cohort was comprised of surgical and medical ICUs while the second cohort was comprised of acute spinal cord injury (ASCI) patients in a neurological ICU. At each time point with physiological MAP, time series analysis was used to predict the median MAP for the subsequent 20 min. This method was used to predict hypertensive episodes, i.e., intervals of 20 or more minutes where at least half of the MAP measurements were > 105 mmHg. Advance prediction of hypertensive episodes was similar in the two cohorts (69.15% vs. 82.61%, respectively), as was positive predictive value of the hypertension predictions (67.42% vs. 71.57%). The results suggest that the methodology may be useable for predicting hypertension from time-series analysis of MAP. Patients requiring continuous vasopressor infusion are at risk of hypertension and excessive vasoconstriction. We found evidence that time-series analysis previously validated for predicting hypotension may also be usable for predicting hypertension.