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14 Initial prehospital vital signs to predict subsequent adverse hospital outcomes
  1. TA Williams1,2,3,7,
  2. KM Ho7,8,
  3. H Tohira1,3,
  4. DM Fatovich6,
  5. P Bailey1,2,
  6. D Brink1,2,
  7. P Gowens9,
  8. GD Perkins5,
  9. J Finn1,2,3,4
  1. 1Prehospital Resuscitation and Emergency Care Research Unit, Curtin University
  2. 2St John Ambulance Western Australia
  3. 3Emergency Medicine, The University of Western Australia
  4. 4School of Public Health and Preventive Medicine, Monash University
  5. 5Warwick Medical School, University of Warwick; Heart of England NHS Foundation Trust
  6. 6Emergency Medicine Royal Perth Hospital; and the Centre for Clinical Research in Emergency Medicine, Harry Perkins Institute of Medical Research
  7. 7Intensive Care Unit, Royal Perth Hospital
  8. 8School of Population Health, The University of Western Australia
  9. 9Lead Consultant Paramedic, Clinical Directorate Scottish Ambulance Service

Abstract

Aim There is growing interest to improve identification of the critically ill patient in the prehospital setting.1–3 We aimed to assess whether initial vital physiological signs in the prehospital setting can predict subsequent adverse hospital outcomes, defined as intensive care (ICU) admission or death in the emergency department (ED).

Methods The initial prehospital physiological data of all adult patients, transported by the St John Ambulance Service to the metropolitan public EDs were linked to the ED information system in this retrospective cohort study. Cardiac arrest unwitnessed by paramedics, rural, inter-hospital, non-emergency, and air transfers were excluded. Area under receiver operating characteristic curve (AUROC) was assessed. Logistic regression with a restricted cubic spline function was used to assess the ability of four physiological variables: systolic blood pressure (BP), heart rate (HR), respiratory rate (RR) and Glasgow Coma Score (GCS) to predict adverse hospital outcomes.

Results Of the 1 79 374 patients, 2268 (1.3%) were subsequently admitted to ICU or died in the ED. AUROC was 0.829 (95% confidence interval 0.820–0.839). The GCS was the most important vital sign, and explained about 56% of the variability of the outcome compared to <11% by each of the other vital signs. A strong non-linearity between initial BP and adverse hospital outcomes was also observed but not with GCS, HR or RR.

Conclusion Initial prehospital vital signs, in particular GCS, may predict subsequent adverse hospital outcomes. Non-linear associations between initial physiological signs and subsequent outcomes should be considered in developing prehospital alert systems.

References

  1. Royal College of physicians. National Early Warning Score (NEWS): Standardising the assessment of acute illness severity in the NHS. Report of a working party. London: RCP. 2012.

  2. Silcock DJ, Corfield AR, Gowens PA, Rooney KD. Validation of the National Early Warning Score in the prehospital setting. Resuscitation2015;89:31–5.

  3. Williams TA, Tohira H, Finn J, Perkins GD, Ho KM. The ability of early warning scores (EWS) to detect critical illness in the prehospital setting: A systematic review. Resuscitation2016;102:35–43.

Conflict of interest P. Bailey is the Clinical Services Director of St John Ambulance-Western Australia. D. Brink is the Executive Manager Clinical Governance St John Ambulance-Western Australia. J. Finn receives partial salary support from St John Ambulance-Western Australia T.A. Williams, K.M. Ho, H. Tohira, D. M. Fatovich, P. Gowens, G. D. Perkins has no conflict of interest St John Ambulance Western Australia played no role in the study design, conduct or interpretation of the results.

Funding None declared.

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