Evidence map›Paper›PMID 42058470›Full record

ArticleFrontiers in pediatrics2026

Risk factors for progression to bronchitis or pneumonia in hospitalized children with human rhinovirus infection: a retrospective cohort study using machine learning.

Qiaoyan Dai, Jingying Zhou, Ying Chen, Qidong Ye

Abstract read
In one paragraph

Article in Frontiers in pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from 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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Qiaoyan DaiDepartment of Pediatrics, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Jingying ZhouDepartment of Pediatrics, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Ying ChenDepartment of Pediatrics, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Qidong YeDepartment of Pediatrics, The First Affiliated Hospital of Ningbo University, Ningbo, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Human rhinovirus (HRV) is a leading cause of acute respiratory infections and hospitalization in children. However, risk factors for progression to bronchitis vs. pneumonia remain incompletely characterized. Objective: This study aimed to identify and distinguish independent predictors for these outcomes using a machine learning approach. Methods: A retrospective cohort study was conducted among hospitalized children with HRV infection at the First Affiliated Hospital of Ningbo University. A two-stage feature selection method (Random Forest and LASSO) was used, followed by multinomial logistic regression to quantify associations with progression to bronchitis or pneumonia. Results: Of 1,125 children, 29% progressed to bronchitis and 59% to pneumonia. Multinomial logistic regression revealed distinct risk profiles. Progression to bronchitis was strongly associated with lower airway obstruction, including dyspnea ( Conclusion: Bronchitis progression is primarily associated with airway obstruction, whereas pneumonia is linked to more complex clinical scenarios, including prior medication, co-infections, and coagulopathy. These findings can improve early risk stratification and guide targeted interventions.

Indexed as

bronchitismachine learningpediatric infectious diseasespneumoniarhinovirus

Identifiers

PMID42058470
PMCPMC13121338

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Registered trials

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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.