Taiwan Preterm Infant Database: Analysis and Comparison of Birth Conditions and Exploration of Prognostic Factors

This study uses Taiwan's Preterm Infant Database to analyze gestational age, birth conditions, and long-term developmental outcomes in preterm infants. Participants are classified by gestational age and birth weight into subgroups, with demographic, clinical, and follow-up data (e.g., Bayley-III, neurodevelopmental exams, rehabilitation records) systematically collected. All data are de-identified, coded, and validated, with confidentiality maintained under IRB oversight. Statistical methods include ANOVA, chi-square, Kruskal-Wallis, repeated-measures ANOVA, and multiple regression models to identify predictive and risk factors. Standardized procedures govern data collection, management, and analysis, with strategies to address missing or inconsistent values. This framework ensures rigor, supports predictive modeling, and provides clinically relevant insights to guide early intervention and healthcare strategies.