• Marko Hoikka, Tom Silfvast, and Tero I Ala-Kokko.
• University of Oulu, Medical Research Centre, Research Unit of Surgery, Anaesthesia and Intensive Care and Department of Anaesthesiology, Division of Intensive Care, Oulu University Hospital, PO BOX 21, FI-90029 OYS, Oulu, Finland. marko.hoikka@student.oulu.fi.
• Scand J Trauma Resus. 2018 Jun 7; 26 (1): 48.

ObjectivesThe prehospital research field has focused on studying patient survival in cardiac arrest, as well as acute coronary syndrome, stroke, and trauma. There is little known about the overall short-term mortality and its predictability in unselected prehospital patients. This study examines whether a prehospital National Early Warning Score (NEWS) predicts 1-day and 30-day mortalities.MethodsData from all emergency medical service (EMS) situations were coupled to the mortality data obtained from the Causes of Death Registry during a six-month period in Northern Finland. NEWS values were calculated from first clinical parameters obtained on the scene and patients were categorized to the low, medium and high-risk groups accordingly. Sensitivities, specificities, positive predictive values (PPVs), negative predictive values (NPVs), and likelihood ratios (PLRs and NLRs) were calculated for 1-day and 30-day mortalities at the cut-off risks.ResultsA total of 12,426 EMS calls were included in the study. The overall 1-day and 30-day mortalities were 1.5 and 4.3%, respectively. The 1-day mortality rate for NEWS values ≤12 was lower than 7% and for values ≥13 higher than 20%. The high-risk NEWS group had sensitivities for 1-day and 30-day mortalities 0.801 (CI 0.74-0.86) and 0.42 (CI 0.38-0.47), respectively.ConclusionIn prehospital environment, the high risk NEWS category was associated with 1-day mortality well above that of the medium and low risk NEWS categories. This effect was not as noticeable for 30-day mortality. The prehospital NEWS may be useful tool for recognising patients at early risk of death, allowing earlier interventions and responds to these patients.

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