SynthesisBMJ open2022
Applicability of predictive models for 30-day unplanned hospital readmission risk in paediatrics: a systematic review.
Synthesis in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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Who cites it
9 citing papers in PubMed.
- Article
- Clinically-applicable prediction of hospital stay and patient similarity retrieval in paediatric cardiology using machine learning.Nature communications · 2026Article
- Predicting non-emergency healthcare use in Australia using machine learning on longitudinal household data.Scientific reports · 2026Article
- Prediction of 30-day unplanned hospital readmission among elderly patients using patient and ward level factors.Scientific reports · 2025Article
- Diverging pathways: exploring the interplay between hospital readmission and postdischarge mortality in paediatric sepsis in low-income settings.BMJ global health · 2025Observational
- Preventing Urgent Pediatric Readmissions: The Need for and Promise of Real-Time Monitoring.JMIR pediatrics and parenting · 2025Article
- Validation of 30-Day Pediatric Hospital Readmission Risk Prediction Models.JAMA network open · 2025Article
- Hospital readmission following acute illness among children 2-23 months old in sub-Saharan Africa and South Asia: a secondary analysis of CHAIN cohort.EClinicalMedicine · 2024Article
- Factors associated with hospital admission and 30-day readmission for children less than 18 years of age in 2018 in France: a one-year nationwide observational study.BMC health services research · 2023Observational
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo summarise multivariable predictive models for 30-day unplanned hospital readmissions (UHRs) in paediatrics, describe their performance and completeness in reporting, and determine their potential for application in practice.
designSystematic review. DATA SOURCE: CINAHL, Embase and PubMed up to 7 October 2021. ELIGIBILITY CRITERIA: English or German language studies aiming to develop or validate a multivariable predictive model for 30-day paediatric UHRs related to all-cause, surgical conditions or general medical conditions were included. DATA EXTRACTION AND SYNTHESIS: Study characteristics, risk factors significant for predicting readmissions and information about performance measures (eg, c-statistic) were extracted. Reporting quality was addressed by the 'Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis' (TRIPOD) adherence form. The study quality was assessed by applying six domains of potential biases. Due to expected heterogeneity among the studies, the data were qualitatively synthesised.
resultsBased on 28 studies, 37 predictive models were identified, which could potentially be used for determining individual 30-day UHR risk in paediatrics. The number of study participants ranged from 190 children to 1.4 million encounters. The two most common significant risk factors were comorbidity and (postoperative) length of stay. 23 models showed a c-statistic above 0.7 and are primarily applicable at discharge. The median TRIPOD adherence of the models was 59% (P
conclusionPredictive models may be useful in identifying paediatric patients at increased risk of readmission. To support the application of predictive models, more attention should be placed on completeness in reporting, particularly for those items that may be relevant for implementation in practice.
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Registered trials
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