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- Title
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.
- Authors
Lamping, Florian; Jack, Thomas; Rübsamen, Nicole; Sasse, Michael; Beerbaum, Philipp; Mikolajczyk, Rafael T.; Boehne, Martin; Karch, André; Rübsamen, Nicole; Karch, André
- Abstract
<bold>Background: </bold>Since early antimicrobial therapy is mandatory in septic patients, immediate diagnosis and distinction from non-infectious SIRS is essential but hampered by the similarity of symptoms between both entities. We aimed to develop a diagnostic model for differentiation of sepsis and non-infectious SIRS in critically ill children based on routinely available parameters (baseline characteristics, clinical/laboratory parameters, technical/medical support).<bold>Methods: </bold>This is a secondary analysis of a randomized controlled trial conducted at a German tertiary-care pediatric intensive care unit (PICU). Two hundred thirty-eight cases of non-infectious SIRS and 58 cases of sepsis (as defined by IPSCC criteria) were included. We applied a Random Forest approach to identify the best set of predictors out of 44 variables measured at the day of onset of the disease. The developed diagnostic model was validated in a temporal split-sample approach.<bold>Results: </bold>A model including four clinical (length of PICU stay until onset of non-infectious SIRS/sepsis, central line, core temperature, number of non-infectious SIRS/sepsis episodes prior to diagnosis) and four laboratory parameters (interleukin-6, platelet count, procalcitonin, CRP) was identified in the training dataset. Validation in the test dataset revealed an AUC of 0.78 (95% CI: 0.70-0.87). Our model was superior to previously proposed biomarkers such as CRP, interleukin-6, procalcitonin or a combination of CRP and procalcitonin (maximum AUC = 0.63; 95% CI: 0.52-0.74). When aiming at a complete identification of sepsis cases (100%; 95% CI: 87-100%), 28% (95% CI: 20-38%) of non-infectious SIRS cases were assorted correctly.<bold>Conclusions: </bold>Our approach allows early recognition of sepsis with an accuracy superior to previously described biomarkers, and could potentially reduce antibiotic use by 30% in non-infectious SIRS cases. External validation studies are necessary to confirm the generalizability of our approach across populations and treatment practices.<bold>Trial Registration: </bold>ClinicalTrials.gov number: NCT00209768; registration date: September 21, 2005.
- Subjects
SEPSIS; AEROMONAS diseases; PATHOGENIC microorganisms; DISEASE progression; INTENSIVE care units
- Publication
BMC Pediatrics, 2018, Vol 18, p1
- ISSN
1471-2431
- Publication type
journal article
- DOI
10.1186/s12887-018-1082-2