WINROP

WINROP predicts the risk of developing sight‑threatening retinopathy of prematurity (ROP) in premature infants (<32 weeks gestational age) using longitudinal weight gain data, insulin‑like growth factor 1 (IGF‑1) levels, and neonatal characteristics.

Key Features:

• Algorithm Basis: Integrates weight gain, insulin‑like growth factor 1 (IGF‑1) levels, and neonatal characteristics to evaluate risk of severe ROP in infants born at less than 32 weeks gestational age.
• Data Inputs: Uses longitudinal weekly weight measurements together with date of birth, gestational age, and final clinical examination outcomes as input variables.
• Alarm System: Generates an alarm signal when computed risk metrics indicate a high likelihood of ROP requiring treatment.
• Efficacy Evaluation: Retrospective evaluation at Hospital Universiti Sains Malaysia (September 2016–March 2019) reported sensitivity 95.2% and specificity 33.8% in a cohort of 92 infants, with alarms detected in 72.8% of cases.
• Clinical Outcomes Observed: In the reported cohort 54.6% had no ROP, 16.3% had stage 1 ROP, 10.8% had stage 2 ROP, and 15.2% had stage 3 ROP.

Scientific Applications:

• Initial screening: Identification of premature infants at elevated risk of developing treatment‑requiring ROP to guide further diagnostic evaluation.
• Triage and prioritization: Support for prioritizing infants for clinical examination or intervention when examinations are logistically or clinically challenging.

Methodology:

The algorithm evaluates longitudinal weekly weight data, measured IGF‑1 levels, and neonatal characteristics (including date of birth and gestational age) to assess risk and trigger an alarm when thresholds for high risk of treatment‑requiring ROP are reached.