Performance of Pediatric Mortality Prediction Models in Low- and Middle-Income Countries: A Systematic Review and Meta-Analysis.

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.

Access to urban acute care services in high- vs. middle-income countries: an analysis of seven cities.

PURPOSE: Cities are expanding rapidly in middle-income countries, but their supply of acute care services is unknown. We measured acute care services supply in seven cities of diverse economic background. METHODS: In a cross-sectional study, we compared cities from two high-income (Boston, USA and Paris, France), three upper-middle-income (Bogota, Colombia; Recife, Brazil; and Liaocheng, China), and two lower-middle-income (Chennai, India and Kumasi, Ghana) countries. We collected standardized data on hospital beds, intensive care unit beds, and ambulances. Where possible, information was collected from local authorities. We expressed results per population (from United Nations) and per acute illness deaths (from Global Burden of Disease project). RESULTS: Supply of hospital beds where intravenous fluids could be delivered varied fourfold from 72.4/100,000 population in Kumasi to 241.5/100,000 in Boston. Intensive care unit (ICU) bed supply varied more than 45-fold from 0.4/100,000 population in Kumasi to 18.8/100,000 in Boston. Ambulance supply varied more than 70-fold. The variation widened when supply was estimated relative to disease burden (e.g., ICU beds varied more than 65-fold from 0.06/100 deaths due to acute illnesses in Kumasi to 4.11/100 in Bogota; ambulance services varied more than 100-fold). Hospital bed per disease burden was associated with gross domestic product (GDP) (R (2) = 0.88, p = 0.01), but ICU supply was not (R (2) = 0.33, p = 0.18). No city provided all requested data, and only two had ICU data. CONCLUSIONS: Urban acute care services vary substantially across economic regions, only partially due to differences in GDP. Cities were poor sources of information, which may hinder their future planning.