Daniel J Lane1, Hannah Wunsch2, Refik Saskin2, Sheldon Cheskes2, Steve Lin2, Laurie J Morrison2, Damon C Scales2. 1. Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health (Lane, Wunsch, Saskin, Lin, Scales), Interdepartmental Division of Critical Care (Wunsch, Scales), Division of Emergency Medicine, Department of Family and Community Medicine (Cheskes), and Division of Emergency Medicine, Department of Medicine (Lin, Morrison), University of Toronto; Rescu, Li Ka Shing Knowledge Institute (Lane, Cheskes, Lin, Morrison), St. Michael's Hospital; Department of Critical Care Medicine (Wunsch) and Sunnybrook Centre for Prehospital Medicine (Cheskes), Sunnybrook Health Sciences Centre, Toronto, Ont. djlane@ucalgary.ca. 2. Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health (Lane, Wunsch, Saskin, Lin, Scales), Interdepartmental Division of Critical Care (Wunsch, Scales), Division of Emergency Medicine, Department of Family and Community Medicine (Cheskes), and Division of Emergency Medicine, Department of Medicine (Lin, Morrison), University of Toronto; Rescu, Li Ka Shing Knowledge Institute (Lane, Cheskes, Lin, Morrison), St. Michael's Hospital; Department of Critical Care Medicine (Wunsch) and Sunnybrook Centre for Prehospital Medicine (Cheskes), Sunnybrook Health Sciences Centre, Toronto, Ont.
Abstract
BACKGROUND: In the prehospital setting, differentiating patients who have sepsis from those who have infection but no organ dysfunction is important to initiate sepsis treatments appropriately. We aimed to identify which published screening strategies for paramedics to use in identifying patients with sepsis provide the most certainty for prehospital diagnosis. METHODS: We identified published strategies for screening by paramedics through a literature search. We then conducted a validation study in Alberta, Canada, from April 2015 to March 2016. For adult patients (≥ 18 yr) who were transferred by ambulance, we linked records to an administrative database and then restricted the search to patients with infection diagnosed in the emergency department. For each patient, the classification from each strategy was determined and compared with the diagnosis recorded in the emergency department. For all strategies that generated numeric scores, we constructed diagnostic prediction models to estimate the probability of sepsis being diagnosed in the emergency department. RESULTS: We identified 21 unique prehospital screening strategies, 14 of which had numeric scores. We linked a total of 131 745 eligible patients to hospital databases. No single strategy had both high sensitivity (overall range 0.02-0.85) and high specificity (overall range 0.38-0.99) for classifying sepsis. However, the Critical Illness Prediction (CIP) score, the National Early Warning Score (NEWS) and the Quick Sepsis-Related Organ Failure Assessment (qSOFA) score predicted a low to high probability of a sepsis diagnosis at different scores. The qSOFA identified patients with a 7% (lowest score) to 87% (highest score) probability of sepsis diagnosis. INTERPRETATION: The CIP, NEWS and qSOFA scores are tools with good predictive ability for sepsis diagnosis in the prehospital setting. The qSOFA score is simple to calculate and may be useful to paramedics in screening patients with possible sepsis.
BACKGROUND: In the prehospital setting, differentiating patients who have sepsis from those who have infection but no organ dysfunction is important to initiate sepsis treatments appropriately. We aimed to identify which published screening strategies for paramedics to use in identifying patients with sepsis provide the most certainty for prehospital diagnosis. METHODS: We identified published strategies for screening by paramedics through a literature search. We then conducted a validation study in Alberta, Canada, from April 2015 to March 2016. For adult patients (≥ 18 yr) who were transferred by ambulance, we linked records to an administrative database and then restricted the search to patients with infection diagnosed in the emergency department. For each patient, the classification from each strategy was determined and compared with the diagnosis recorded in the emergency department. For all strategies that generated numeric scores, we constructed diagnostic prediction models to estimate the probability of sepsis being diagnosed in the emergency department. RESULTS: We identified 21 unique prehospital screening strategies, 14 of which had numeric scores. We linked a total of 131 745 eligible patients to hospital databases. No single strategy had both high sensitivity (overall range 0.02-0.85) and high specificity (overall range 0.38-0.99) for classifying sepsis. However, the Critical Illness Prediction (CIP) score, the National Early Warning Score (NEWS) and the Quick Sepsis-Related Organ Failure Assessment (qSOFA) score predicted a low to high probability of a sepsis diagnosis at different scores. The qSOFA identified patients with a 7% (lowest score) to 87% (highest score) probability of sepsis diagnosis. INTERPRETATION: The CIP, NEWS and qSOFA scores are tools with good predictive ability for sepsis diagnosis in the prehospital setting. The qSOFA score is simple to calculate and may be useful to paramedics in screening patients with possible sepsis.
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