Prognostic factors and models to predict pediatric sepsis mortality: A scoping review - Yuniar, Irene; Hafifah, Cut Nurul; Adilla, Sharfina Fulki; Shadrina, Arifah Nur; Darmawan, Anthony Christian; Nasution, Kholisah; Ranakusuma, Respati W.; Safitri, Eka Dian (Frontiers in Pediatrics, 2023)
Introduction: Several scoring systems are available to assess the severity of sepsis in pediatric patients in diverse settings worldwide. This study investigates the quality and applicability of predictive models for determining pediatric sepsis mortality, especially in acute care and limited-resource settings. Data Sources: Mortality prediction factors and models were searched in four databases using the following criteria: developed for pediatric health care, especially in acute settings, and mortality as an outcome. Study Selection: Two or more reviewers performed the study selection to ensure no bias occurred. Any disagreements were solved by consensus or by the decision of a third reviewer. Data Extraction: The authors extracted the results and mapped the selected studies qualitatively to describe the prognostic properties of the risk factors and models proposed in the study. The models were divided into various categories: models used to predict a potential complication of severe sepsis, models used to predict mortality as an outcome, and models used to predict the severity of sepsis. Data Synthesis: Final analysis included twenty-eight mortality prediction models. Characteristics, analysis, and performance measures of the models were summarized. Performance was described in calibration and discrimination, including assessing for risk of bias and applicability. Modified PRISM-III based on physiologic criteria (PRISM-III-APS) increased its predictive value to 0.85-0.95.38,39. Vasoactive-Inotropic Score at 12 hours had a strong independent association with death. Albumin had an excellent predictive value when combined with other variables. Lactate level as a biomarker widely measured in sepsis patients was highly associated with mortality. The bioimpedance phase angle was considered not applicable in our setting. Measurement using more straightforward methods, such as mid-upper arm circumference, was feasible in numerous healthcare facilities. Conclusion: Leveraging prognostic models to predict mortality among pediatric patients with sepsis remains an important and well-recognized area of study. While much validation and development work remains needed, available prognostic models could aid clinicians at the bedside of children with sepsis. Furthermore, mortality prediction models are essential and valuable tools for assessing the quality of care provided to pediatric patients with critically ill conditions. Keywords: mortality, pediatric, prognostic model, sepsis