Prospective evaluation of an automated method to identify patients with severe sepsis or septic shock in the emergency department

BMC Emergency Medicine

Volumn 16, Issue 1, 2016, Pages

  Brown, Samuel M ^a,b   Jones, Jason ^c   Kuttler, Kathryn Gibb ^a,d   Keddington, Roger K ^d   Allen, Todd L ^d   Haug, Peter ^d  

^a INTERMOUNTAIN MEDICAL CENTER   (United States)

^b UNIVERSITY OF UTAH SCHOOL OF MEDICINE   (United States)

^c KAISER PERMANENTE   (United States)

^d INTERMOUNTAIN HEALTHCARE   (United States)

Author keywords

Automated detection; Bayesian classifier; Sepsis

Indexed keywords

ADULT; AGE; ARTICLE; AUTOMATION; BODY TEMPERATURE; CONTROLLED STUDY; DISEASE SEVERITY; EMERGENCY WARD; FALSE POSITIVE RESULT; FEMALE; HEART RATE; HUMAN; LEUKOCYTE COUNT; MAJOR CLINICAL STUDY; MALE; MEAN ARTERIAL PRESSURE; PATIENT IDENTIFICATION; PROSPECTIVE STUDY; SEPTIC SHOCK; BAYES THEOREM; BLOOD PRESSURE; EMERGENCY HEALTH SERVICE; HOSPITAL EMERGENCY SERVICE; MIDDLE AGED; PROCEDURES; RECEIVER OPERATING CHARACTERISTIC; RETROSPECTIVE STUDY; SENSITIVITY AND SPECIFICITY; SEPSIS; STATISTICS AND NUMERICAL DATA;

ADULT; AGE FACTORS; BAYES THEOREM; BLOOD PRESSURE; BODY TEMPERATURE; EMERGENCY SERVICE, HOSPITAL; FEMALE; HEART RATE; HUMANS; LEUKOCYTE COUNT; MALE; MIDDLE AGED; RETROSPECTIVE STUDIES; ROC CURVE; SENSITIVITY AND SPECIFICITY; SEPSIS; SHOCK, SEPTIC; TRIAGE;

EID: 84983527180     PISSN: None     EISSN: 1471227X     Source Type: Journal    
DOI: 10.1186/s12873-016-0095-0     Document Type: Article

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