Risk Factors for Bronchopulmonary Dysplasia in Preterm Infants from Shenzhen, 2022-2023

A dataset of 1,336 preterm infants with gestational age under 32 weeks, collected prospectively from 28 hospitals in Shenzhen from January 2022 to December 2023. The data was used to develop and validate a nomogram model for predicting bronchopulmonary dysplasia risk based on six perinatal and postnatal factors available within the first week of life. The model was created by Yanping Guo and shows an area under the curve of 0.810 in external validation.

Use Cases

• Train a logistic regression model for BPD risk stratification based on gestational age and birth weight.
• Validate a clinical prediction nomogram using the provided training and validation cohorts.
• Analyze the association between invasive mechanical ventilation in the first week and subsequent BPD diagnosis.
• Assess model calibration and discrimination performance for a binary medical outcome.

Strengths

• Includes 1,336 patient records from a prospective multicenter study.
• Model validation uses three distinct cohorts: training (n=801), internal validation (n=214), and external validation (n=321).
• The predictive model is based on six clearly defined clinical factors, including gestational age and birth weight.

Limitations

• Row count and column-level documentation are unknown, which limits suitability assessment.
• Data is specific to 28 hospitals in Shenzhen, which may limit generalizability to other populations.
• The dataset is very small at 17.8 KB, indicating limited scope.

Provenance

Source

Prospective data collection from 28 hospitals in Shenzhen, China.

Collection Method

Clinical data was prospectively collected from neonatal intensive care units.

Time Range

January 2022 to December 2023

Freshness

Last updated 2026-04-30 05:40:44; freshness should be verified.

Geography

Shenzhen, China