ArticlePediatric pulmonology2025
Machine Learning Models for Predicting Pediatric Hospitalizations Due to Air Pollution and Humidity: A Retrospective Study.
Article in Pediatric pulmonology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Environmental and socioeconomic influences on childhood asthma and pneumonia: burden and healthcare utilization in a population-based cohort study.Frontiers in medicine · 2026Article
- Article
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
Abstract
backgroundExposure to air pollution and meteorological conditions, such as humidity, has been linked to adverse respiratory health outcomes in children. This study aims to develop predictive models for pediatric hospitalizations based on both environmental exposures and clinical features.
methodsWe conducted a retrospective analysis of 2500 children (aged 1-18) who presented with respiratory symptoms at the emergency department, during 2016-2017. Air pollution data, including NOx and NO
resultsBoys were more likely to be hospitalized than girls (60.6% vs. 39.4%, p = 4.31e-06). Hospital visits peaked during winter (p = 3.56e-37). Increased emergency room visits were statistically significantly associated with highly polluted days (p = 0.038). Hospitalized children were exposed to lower RH (median 64.9%) compared to nonhospitalized children (median 69.4%, p = 0.005). The RF and XGBoost models were reliable, with accuracy rates of 0.7-0.98, Precision scores of 0.88-0.99, and AUC scores of 81%-99%. Key features included temperature, NOx levels, RH, and exposure to SO
conclusionThis study investigates the effects of air pollution and humidity on pediatric respiratory health. The models developed offer valuable tools for predicting hospitalizations and are intended to support public health planning and resource allocation.
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.