Predictors of cardiac arrest in severe accidental hypothermia

Paweł Podsiadło1, Tomáš Brožek2, Martin Balik2

  • 1Department of Emergency Medicine, Jan Kochanowski University, Kielce, Poland.

Insights

Predictors of hypothermic cardiac arrest (HCA) in severe accidental hypothermia include lower heart rate, hypoxemia, and ventricular arrhythmia. These factors aid in early identification of high-risk patients needing advanced rewarming.

Area of Science:

  • Emergency Medicine
  • Critical Care Medicine
  • Cardiology

Background:

  • Severe accidental hypothermia poses significant risks, including cardiac arrest (CA).
  • Early identification of patients at high risk for CA is crucial for timely intervention.
  • Predicting CA in hypothermic patients presenting with preserved spontaneous circulation requires further investigation.

Purpose of the Study:

  • To identify predictors of witnessed hypothermic cardiac arrest (HCA) in patients with severe accidental hypothermia.
  • To develop models for predicting HCA in prehospital and hospital settings.
  • To aid in the early selection and management of high-risk hypothermic patients.

Main Methods:

  • Retrospective analysis of 182 patients with severe accidental hypothermia (core body temperature ≤28°C) and preserved spontaneous circulation.
  • Patients were divided into groups based on the occurrence of HCA before normothermia.
  • Hemodynamic and biochemical parameters were analyzed to identify predictors of HCA.

Main Results:

  • Twenty-nine percent of patients experienced HCA. Significant predictors included lower heart rate, systolic blood pressure, ventricular arrhythmia, and arterial oxygen partial pressure (PaO2).
  • A multivariable model incorporating heart rate, PaO2, and Base Excess (BE) predicted HCA with an AUROC of 0.78.
  • In prehospital settings, a model with heart rate and ventricular arrhythmia achieved an AUROC of 0.74.

Conclusions:

  • Lower heart rate, hypoxemia, ventricular arrhythmia, lower BE, and lower blood pressure are associated with HCA in severe accidental hypothermia.
  • These parameters can guide early selection of high-risk patients for extracorporeal rewarming.
  • Predictive models can improve patient outcomes by facilitating timely transfer to specialized care facilities.
Abstract

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