Hypotension in ICU Patients Receiving Vasopressor Therapy

Bryce Yapps,Sadeq A Quraishi,Sungtae Shin,Jill Thorsen,Andrew T Reisner,Jin-Oh Hahn,Colleen Arsenault,Ramin Bighamian

doi:10.1038/s41598-017-08137-0

Bryce Yapps, Sadeq A Quraishi + Show 6 more

Open Access

https://doi.org/10.1038/s41598-017-08137-0

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Abstract

Vasopressor infusion (VPI) is used to treat hypotension in an ICU. We studied compliance with blood pressure (BP) goals during VPI and whether a statistical model might be efficacious for advance warning of impending hypotension, compared with a basic hypotension threshold alert. Retrospective data were obtained from a public database. Studying adult ICU patients receiving VPI at submaximal dosages, we analyzed characteristics of sustained hypotension episodes (>15 min) and then developed a logistic regression model to predict hypotension episodes using input features related to BP trends. The model was then validated with prospective data. In the retrospective dataset, 102-of-215 ICU stays experienced >1 hypotension episode (median of 2.5 episodes per day in this subgroup). When trained with 75% of retrospective dataset, testing with the remaining 25% of the dataset showed that the model and the threshold alert detected 99.6% and 100% of the episodes, respectively, with median advance forecast times (AFT) of 12 and 0 min. In a second, prospective dataset, the model detected 100% of 26 episodes with a median AFT of 22 min. In conclusion, episodes of hypotension were common during VPI in the ICU. A logistic regression model using BP temporal trend features predicted the episodes before their onset.

Highlights

Many patients treated for circulatory shock receive hours or days of vasopressor infusion to manage persistent hypotension
We studied ICU patients with vasopressor infusion doses documented in the nursing flowcharts with concurrent heart rate (HR) and mean arterial pressure (MAP) data from indwelling arterial catheters
Performance in Hospital 2 was similar to performance in Hospital 1, in the sense that the logistic regression model again provided sensitive advance warning to episodes of hypotension, without a greater number of false alarms than the simple threshold alert

Summary

Introduction

Many patients treated for circulatory shock receive hours or days of vasopressor infusion to manage persistent hypotension. The rationale for treating severe hypotension with vasopressors is based in large part on classical physiology studies showing that central nervous system (CNS) auto-regulation of CNS perfusion fails in healthy animals for MAP < 65 mmHg3, 4. This limit, CNS hypoperfusion and tissue ischemia occur. In a preliminary study[9], we reported that ICU patients frequently experience sustained episodes (>15 min) of hypotension while receiving vasopressor infusions. The second goal of this study was to investigate the efficacy of statistical methods for predicting when the patient’s vasopressor dosage requires a change, because computerized decision-support offers a potential means to enhance clinician practice. In an ICU as a tool for preventing hypotension by providing a reliable advance warning before hypotension develops

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