ArticleCritical care explorations2021
Prediction of Impending Septic Shock in Children With Sepsis.
Article in Critical care explorations, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.
- Artificial intelligence in pediatric intensive care units: current applications in sepsis management.World journal of pediatrics : WJP · 2026Pooled it
- Prognostic accuracy of SOFA and qSOFA for mortality among children with infection: a meta-analysis.Pediatric research · 2023Pooled it
- Aligning prediction models with clinical information needs: infant sepsis case study.JAMIA open · 2025Article
- Predicting Escalation of Care for Childhood Pneumonia Using Machine Learning: Retrospective Analysis and Model Development.JMIRx med · 2025Article
- Machine Learning in Pediatric Healthcare: Current Trends, Challenges, and Future Directions.Journal of clinical medicine · 2025Review
- A scoping review on pediatric sepsis prediction technologies in healthcare.NPJ digital medicine · 2024Article
- Pediatric septic shock estimation using deep learning and electronic medical records.Acute and critical care · 2024Article
- The use of machine learning and artificial intelligence within pediatric critical care.Pediatric research · 2023Review
- A data-driven model for early prediction of need for invasive mechanical ventilation in pediatric intensive care unit patients.PloS one · 2023Observational
- About gladiators and a sacred disease.Biomedical journal · 2022Article
- Comparison of Pediatric Risk of Mortality-III, Phoenix Sepsis, and pediatric Sequential Organ Failure Assessment scores for predicting septic shock in Vietnamese children with sepsis.The Brazilian journal of infectious diseases : an official publication of the Brazilian Society of Infectious DiseasesArticle
- Predicting Pediatric Sepsis Outcomes: A Comparison of 3 Sepsis Risk Scores in Bangladesh.Sage open pediatricsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesSepsis and septic shock are leading causes of in-hospital mortality. Timely treatment is crucial in improving patient outcome, yet treatment delays remain common. Early prediction of those patients with sepsis who will progress to its most severe form, septic shock, can increase the actionable window for interventions. We aim to extend a time-evolving risk score, previously developed in adult patients, to predict pediatric sepsis patients who are likely to develop septic shock before its onset, and to determine whether or not these risk scores stratify into groups with distinct temporal evolution once this prediction is made.
designRetrospective cohort study.
settingAcademic medical center from July 1, 2016, to December 11, 2020. PATIENTS: Six-thousand one-hundred sixty-one patients under 18 admitted to the Johns Hopkins Hospital PICU.
interventionsNone. MEASUREMENTS AND MAIN
resultsWe trained risk models to predict impending transition into septic shock and compute time-evolving risk scores representative of a patient's probability of developing septic shock. We obtain early prediction performance of 0.90 area under the receiver operating curve, 43% overall positive predictive value, patient-specific positive predictive value as high as 62%, and an 8.9-hour median early warning time using Sepsis-3 labels based on age-adjusted Sequential Organ Failure Assessment score. Using spectral clustering, we stratified pediatric sepsis patients into two clusters differing in septic shock prevalence, mortality, and proportion of patients adequately fluid resuscitated.
conclusionsWe demonstrate the applicability of our methodology for early prediction and stratification for risk of septic shock in pediatric sepsis patients. Through analyses of risk score evolution over time, we corroborate our past finding of an abrupt transition preceding onset of septic shock in children and are able to stratify pediatric sepsis patients using their risk score trajectories into low and high-risk categories.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.