title: Prehospital loss of R-to-R interval complexity is associated with mortality in trauma patients.
abstract: BACKGROUND
  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 +/- 1.7 vs. 13.2 +/- 0.8, p < 0.05). RRI approximate entropy (ApEn; 0.87 +/- 0.06 vs. 1.09 +/- 0.07, p < 0.01), sample entropy (SampEn; 0.80 +/- 0.08 vs. 1.10 +/- 0.05, p < 0.01) and fractal dimension by dispersion analysis (1.08 +/- 0.02 vs. 1.13 +/- 0.01, p < 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 +/- 34.4 vs. 222 +/- 21.3, p < 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 GCSMOTOR was considered, it replaced Dis_2 whereas ApEn was retained (area under curve = 0.92). When Injury Severity Score was considered, it replaced GCSMOTOR; 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.
authors: US Army Institute of Surgical Research, Fort Sam Houston, Texas 78234-6315, USA. andriy.batchinsky@amedd.army.mil
authors: Andriy I
authors: AI
authors: Batchinsky
authors: Leopoldo C
authors: LC
authors: Cancio
authors: Jose
authors: J
authors: Salinas
authors: Tom
authors: T
authors: Kuusela
authors: William H
authors: WH
authors: Cooke
authors: Jing Jing
authors: JJ
authors: Wang
authors: Marla
authors: M
authors: Boehme
authors: Victor A
authors: VA
authors: Convertino
authors: John B
authors: JB
authors: Holcomb
mesh_terms: D015998:Abbreviated Injury Scale; D000328:Adult; D017732:Air Ambulances; D001145:Arrhythmias, Cardiac / Q000175:diagnosis* / Q000209:etiology* / Q000503:physiopathology; D001342:Autonomic Nervous System Diseases / Q000175:diagnosis* / Q000209:etiology* / Q000503:physiopathology; D001794:Blood Pressure / Q000502:physiology; D004562:Electrocardiography; D005260:Female; D015600:Glasgow Coma Scale; D006339:Heart Rate / Q000502:physiology; D006801:Humans; D015601:Injury Severity Score; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009104:Multiple Trauma / Q000150:complications / Q000401:mortality* / Q000503:physiopathology; D011237:Predictive Value of Tests; D011379:Prognosis; D012307:Risk Factors; D015996:Survival Rate; D013781:Texas / Q000453:epidemiology; D014218:Triage / Q000379:methods