Development and validation of a diagnostic model for early differentiation of sepsis and non-infectious SIRS in critically ill children - A data-driven approach using machine-learning algorithms

BMC Pediatrics

Volumn 18, Issue 1, 2018, Pages

  Lamping, Florian ^a,b,c   Jack, Thomas ^b   Rübsamen, Nicole ^a   Sasse, Michael ^b   Beerbaum, Philipp ^b   Mikolajczyk, Rafael T ^a,c   Boehne, Martin ^b   Karch, André ^a,c  

^a HELMHOLTZ CENTRE FOR INFECTION RESEARCH   (Germany)

^b HANNOVER MEDICAL SCHOOL   (Germany)

^c Center for Experimental and Clinical Infection Research   (Germany)

Author keywords

Diagnosis; Intensive care unit; Pediatric; Random Forest; Sepsis; SIRS

Indexed keywords

C REACTIVE PROTEIN; INTERLEUKIN 6; PROCALCITONIN;

ARTICLE; CHILD; CONTROLLED STUDY; CORE TEMPERATURE; CRITICALLY ILL PATIENT; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; FEMALE; GERMANY; HUMAN; INFANT; LENGTH OF STAY; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; PEDIATRIC INTENSIVE CARE UNIT; PLATELET COUNT; RANDOM FOREST; RANDOMIZED CONTROLLED TRIAL (TOPIC); RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; SEPSIS; SYSTEMIC INFLAMMATORY RESPONSE SYNDROME; ADOLESCENT; ALGORITHM; CRITICAL ILLNESS; DECISION SUPPORT SYSTEM; DIFFERENTIAL DIAGNOSIS; EARLY DIAGNOSIS; FOLLOW UP; NEWBORN; PRESCHOOL CHILD; PROSPECTIVE STUDY; RANDOMIZED CONTROLLED TRIAL; REPRODUCIBILITY;

ADOLESCENT; ALGORITHMS; CHILD; CHILD, PRESCHOOL; CRITICAL ILLNESS; DECISION SUPPORT TECHNIQUES; DIAGNOSIS, DIFFERENTIAL; EARLY DIAGNOSIS; FEMALE; FOLLOW-UP STUDIES; HUMANS; INFANT; INFANT, NEWBORN; MACHINE LEARNING; MALE; PROSPECTIVE STUDIES; REPRODUCIBILITY OF RESULTS; SEPSIS; SYSTEMIC INFLAMMATORY RESPONSE SYNDROME;

EID: 85043773463     PISSN: None     EISSN: 14712431     Source Type: Journal    
DOI: 10.1186/s12887-018-1082-2     Document Type: Article

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