Pediatric Respiratory Infection Risk Factors and Nomogram, 2016–2025 Cohort

6,026 children were included in a 10-year real-world cohort study (2016–2025), with 1,227 (20.4%) developing recurrent respiratory tract infections (RRTIs). The dataset, authored by Hehua Cai and shared on figshare under CC-BY-4.0, was used to develop and validate a predictive nomogram. The model identified independent predictors including allergy history, asthma history, vitamin levels, birth weight, passive smoking, and hemoglobin.

Use Cases

• Developing risk stratification models based on clinical history and nutritional indicators.
• Evaluating the predictive power of factors like vitamin A/D levels and passive smoking exposure.
• Validating clinical decision-support tools using bootstrap resampling and decision-curve analysis.
• Studying the epidemiology of recurrent respiratory infections in a pediatric population.

Strengths

• Dataset includes 6,026 children from a 10-year cohort (2016–2025).
• Model was developed using a training set of 4,219 children and validated on a separate testing set of 1,807.
• Multivariable analysis identified seven independent predictors with statistically significant odds ratios (all P < 0.001).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the underlying data is unknown, which may limit suitability assessment.
• Data may reflect temporal and source bias inherent to the specific cohort study.

Provenance

Source

Hehua Cai via figshare.

Collection Method

Real-world cohort study with predefined screening and follow-up criteria.

Time Range

2016–2025

Freshness

Last updated 2026-05-12 05:43:20; freshness should be verified.