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Performance of Pediatric Mortality Prediction Models in Low- and Middle-Income Countries: A Systematic Review and
Fiona Muttalib1, Virginie Clavel2, Lauren H Yaeger3
1Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada; Center for Global Child Health, Hospital for Sick Children, Toronto, Ontario, Canada.
Insights
Pediatric prognostic models for child mortality show good discrimination but require rigorous validation. Further research and updating are needed before clinical use in low- and middle-income countries.
Area of Science:
- Pediatric critical care medicine
- Epidemiology
- Health outcomes research
Background:
- Prognostic models are crucial for predicting outcomes in hospitalized children.
- Existing models developed or validated in low- and middle-income countries (LMICs) need thorough evaluation.
- Assessing the performance and risk of bias of these models is essential for clinical implementation.
Purpose of the Study:
- To systematically review and describe the performance of prognostic models for mortality or clinical deterioration in hospitalized children in LMICs.
- To identify models with robust validation and good predictive accuracy.
- To evaluate the risk of bias in the development and validation of these pediatric prognostic models.
Main Methods:
- Systematic literature search of multiple databases (EMBASE, Medline, Scopus, etc.) from 2000 to October 2019.
- Inclusion of studies on the development or validation of pediatric prognostic models for hospital mortality or clinical deterioration in LMICs.
- Data extraction on model performance and risk of bias assessment using the Prediction model Risk Of Bias Assessment Tool (PROBAST).
Main Results:
- Fifteen studies describing 15 mortality and 3 clinical deterioration models were included.
- The Lambarene Organ Dysfunction Score and Signs of Inflammation in Children that Kill showed the highest discrimination (C-statistics of 0.85).
- All models exhibited a high risk of bias due to methodological limitations, including predictor selection and handling of missing data; calibration and classification were poorly reported.
Conclusions:
- While some pediatric prognostic models demonstrate good discrimination for mortality and clinical deterioration in LMICs, significant methodological limitations exist.
- Rigorous external validation and adherence to current standards for prediction model development are necessary.
- Updating existing models and further research are required before widespread clinical implementation in resource-limited settings.
Objective:
To describe the performance of prognostic models for mortality or clinical deterioration events among hospitalized children developed or validated in low- and middle-income countries.
Study Design:
A medical librarian systematically searched EMBASE, Ovid Medline, Scopus, Cochrane Library, EBSCO Global Health, LILACS, African Index Medicus, African Journals Online, African Healthline, Med-Carib, and Global Index Medicus (from 2000 to October 2019). We included citations that described the development or validation of a pediatric prognostic model for hospital mortality or clinical deterioration events in low- and middle-income countries. In duplicate and independently, we extracted data on included populations and model prognostic performance and evaluated risk of bias using the Prediction model Risk Of Bias Assessment Tool.
Results:
Of 41 279 unique citations, we included 15 studies describing 15 prognostic models for mortality and 3 models for clinical deterioration events. Six models were validated in >1 external cohort. The Lambarene Organ Dysfunction Score (0.85 [0.77-0.92]) and Signs of Inflammation in Children that Kill (0.85 [0.82-0.88]) had the highest summary C-statistics (95% CI) for discrimination. Calibration and classification measures were poorly reported. All models were at high risk of bias owing to inappropriate selection of predictor variables and handling of missing data and incomplete performance measure reporting.
Conclusions:
Several prognostic models for mortality and clinical deterioration events have been validated in single cohorts, with good discrimination. Rigorous validation that conforms to current standards for prediction model studies and updating of existing models are needed before clinical implementation.
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