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Risk Factors and Prediction Models for Retinopathy of Prematurity.
Mallika Prem Senthil1, Mohamad Aziz Salowi2, Mohamad Adam Bujang3
1Department of Ophthalmology, Faculty of Medicine and Health Sciences, University Malaysia Sarawak (UNIMAS), Lot 77, Seksyen 22, Kuching Town Land District, Jalan Tun Ahmad Zaidi Adruce, 93150 Kuching, Sarawak, Malaysia.
The Malaysian Journal of Medical Sciences : MJMS
|February 28, 2017
Summary
A new prediction model using gestational age and birth weight can effectively pre-screen preterm infants for Retinopathy of Prematurity (ROP), enabling early detection and preventing poor outcomes.
Area of Science:
- Neonatal Medicine
- Ophthalmology
- Biostatistics
Background:
- Retinopathy of Prematurity (ROP) is a significant cause of visual impairment in preterm infants.
- Early detection and intervention are crucial to prevent severe visual outcomes.
Purpose of the Study:
- To develop a simple and effective prediction model for pre-screening ROP in preterm neonates.
- To identify key clinical factors for early ROP risk assessment.
Main Methods:
- A prospective study design was employed.
- Two logistic regression models were developed using a test dataset (2007-2010) and validated on a separate dataset (2011-2012).
- Model 1 included gestational age, birth weight, intraventricular hemorrhage, and respiratory distress syndrome; Model 2 included gestational age and birth weight.
Main Results:
- Model 1 demonstrated 82% sensitivity and 81.7% specificity.
- Model 2 achieved 80.5% sensitivity and 80.3% specificity.
- Model 2, utilizing only gestational age and birth weight, was deemed preferable due to its simplicity.
Conclusions:
- A prediction model incorporating gestational age and birth weight offers a practical approach for ROP pre-screening.
- This model facilitates early detection of ROP, potentially mitigating adverse visual outcomes in preterm infants.
