ArticleNPJ digital medicine2024
A scoping review on pediatric sepsis prediction technologies in healthcare.
Article in NPJ digital medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis 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
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Applications of artificial intelligence in early childhood health management: a systematic review from fetal to pediatric periods.Frontiers in pediatrics · 2025Pooled it
- Explainable AI: Ethical Frameworks, Bias, and the Necessity for Benchmarks.European journal of pediatric surgery : official journal of Austrian Association of Pediatric Surgery ... [et al] = Zeitschrift fur Kinderchirurgie · 2026Review
- An explainable machine learning model for early pediatric sepsis prediction using cytokine and routine laboratory data.Pediatric research · 2026Article
- Care Pathway and Outcomes in Pediatric Septic Shock: A Narrative Review from Emergency Department Recognition to PICU Management.Children (Basel, Switzerland) · 2026Review
- Proteomic biomarkers for early diagnosis and prognosis in pediatric sepsis.World journal of clinical pediatrics · 2026Article
- Effectiveness of a flipped classroom combined with case-based learning in the clinical training of pediatric interns: a randomized controlled study.Frontiers in medicine · 2026Article
- Pediatric sepsis prediction: Human in the loop framework.PLOS digital health · 2025Article
- Artificial intelligence in pediatric healthcare: current applications, potential, and implementation considerations.Clinical and experimental pediatrics · 2025Article
- Artificial intelligence should genuinely support clinical reasoning and decision making to bridge the translational gap.NPJ digital medicine · 2025Review
- Management of Burns: Multi-Center Assessment Comparing AI Models and Experienced Plastic Surgeons.Journal of clinical medicine · 2025Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This scoping review evaluates recent advancements in data-driven technologies for predicting non-neonatal pediatric sepsis, including artificial intelligence, machine learning, and other methodologies. Of the 27 included studies, 23 (85%) were single-center investigations, and 16 (59%) used logistic regression. Notably, 20 (74%) studies used datasets with a low prevalence of sepsis-related outcomes, with area under the receiver operating characteristic scores ranging from 0.56 to 0.99. Prediction time points varied widely, and development characteristics, performance metrics, implementation outcomes, and considerations for human factors-especially workflow integration and clinical judgment-were inconsistently reported. The variations in endpoint definitions highlight the potential significance of the 2024 consensus criteria in future development. Future research should strengthen the involvement of clinical users to enhance the understanding and integration of human factors in designing and evaluating these technologies, ultimately aiming for safe and effective integration in pediatric healthcare.
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.