Prehospital Loss of R-to-R Interval Complexity is Associated With Mortality in Trauma Patients

Abstract

To improve our ability to identify physiologic deterioration caused by critical injury, we applied nonlinear analysis to the R-to-R interval (RRI) of the electrocardiogram of prehospital trauma patients. Methods: Ectopy-free, 800-beat sections of electrocardiogram from 31 patients were identified. Twenty patients survived (S) and 11 died (NonS) after hospital admission. Demographic data, heart rate, blood pressure, field Glasgow Coma Scale (GCS) score, and survival times were recorded. RRI complexity was assessed via nonlinear statistics, which quantify entropy or fractal properties. Results: Age and field heart rate and blood pressure were not different between groups. Mean survival time (NonS) was 129 hours 62 hours. NonS had a lower GCS score (8.6 + or - 1.7 vs. 13.2 + or - 0.8, p less than 0.05). RRI approximate entropy (ApEn; 0.87 + or - 0.06 vs. 1.09 + or - 0.07, p less than 0.01), sample entropy (SampEn; 0.80 + or - 0.08 vs. 1.10 + or - 0.05, p less than 0.01) and fractal dimension by dispersion analysis (1.08 0.02 vs. 1.13 0.01, p less than 0.05) were lower in NonS. Distribution of symbol 2 (Dis_2), a symbol-dynamics measure of RRI distribution, was higher in NonS (292.6 + or - 34.4 vs. 222 + or - 21.3, p less than 0.10). For RRI data, logistic regression analysis revealed ApEn and Dis_2 as independent predictors of mortality (area under the receiver-operating characteristic curve 0.96). When GCS MOTOR was considered, it replaced Dis_2 whereas ApEn was retained (area under curve 0.92). When Injury Severity Score was considered, it replaced GCS MOTOR ; ApEn was retained. Conclusions: Prehospital loss of RRI complexity, as evidenced by decreased entropy, was associated with mortality in trauma patients independent of GCS score or Injury Severity Score.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2007
Accession Number
ADA627864

Entities

People

  • Andriy I Batchinsky
  • Jing J. Wang
  • John B Holcomb
  • Josè Salinas
  • Leopoldo C. Cancio
  • Marla Boehme
  • Tom Kuusela
  • Victor A Convertino
  • William H. Cooke

Organizations

  • United States Army Institute of Surgical Research

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Cardiac Arrhythmias
  • Cardiovascular Physiological Phenomena
  • Cardiovascular System
  • Data Science
  • Data Sets
  • Databases
  • Electrocardiography
  • Frequency
  • Health Services
  • Heart Rate
  • Hospitals
  • Information Science
  • Intervals
  • Myocardial Ischemia
  • Patient Care
  • Predictive Modeling
  • Vital Signs

Fields of Study

  • Medicine

Readers

  • Trauma or Military Medicine
  • Wave Propagation and Nonlinear Chaotic Dynamics.