4.7 Article

Prediction of Critical Illness During Out-of-Hospital Emergency Care

Journal

JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
Volume 304, Issue 7, Pages 747-754

Publisher

AMER MEDICAL ASSOC
DOI: 10.1001/jama.2010.1140

Keywords

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Funding

  1. National Institutes of Health (NIH) [T32 NIH/HL07287, K23 HL082650, K23 GM086729-01, 5UL1RR0205014, R01 HL088576-01A1, R01 HL074098-01A1]
  2. National Center for Research Resources, NIH [KL2 RR025015]
  3. Robert Wood Johnson Foundation

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Context Early identification of nontrauma patients in need of critical care services in the emergency setting may improve triage decisions and facilitate regionalization of critical care. Objectives To determine the out-of-hospital clinical predictors of critical illness and to characterize the performance of a simple score for out-of-hospital prediction of development of critical illness during hospitalization. Design and Setting Population-based cohort study of an emergency medical services (EMS) system in greater King County, Washington (excluding metropolitan Seattle), that transports to 16 receiving facilities. Patients Nontrauma, non cardiac arrest adult patients transported to a hospital by King County EMS from 2002 through 2006. Eligible records with complete data (N=144 913) were linked to hospital discharge data and randomly split into development (n=87 266 [60%]) and validation (n=57 647 [40%]) cohorts. Main Outcome Measure Development of critical illness, defined as severe sepsis, delivery of mechanical ventilation, or death during hospitalization. Results Critical illness occurred during hospitalization in 5% of the development (n=4835) and validation (n=3121) cohorts. Multivariable predictors of critical illness included older age, lower systolic blood pressure, abnormal respiratory rate, lower Glasgow Coma Scale score, lower pulse oximetry, and nursing home residence during out-of-hospital care (P<.01 for all). When applying a summary critical illness prediction score to the validation cohort (range, 0-8), the area under the receiver operating characteristic curve was 0.77 (95% confidence interval [CI], 0.76-0.78), with satisfactory calibration slope (1.0). Using a score threshold of 4 or higher, sensitivity was 0.22 (95% CI, 0.20-0.23), specificity was 0.98 (95% CI, 0.98-0.98), positive likelihood ratio was 9.8 (95% Cl, 8.9-10.6), and negative likelihood ratio was 0.80 (95% Cl, 0.79- 0.82). A threshold of 1 or greater for critical illness improved sensitivity (0.98; 95% CI, 0.97-0.98) but reduced specificity (0.17; 95% CI, 0.17-0.17). Conclusions In a population-based cohort, the score on a prediction rule using out-of-hospital factors was significantly associated with the development of critical illness during hospitalization. This score requires external validation in an independent population. JAMA. 2010;304(7):747-754 www.jama.com

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