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Multicenter validation study of the WINROP algorithm as a method for detecting retinopathy of prematurity
María J Chaves-Samaniego1,2, Cristina Gómez Cabrera3, María C Chaves-Samaniego4
1Doctoral Program in Clinical Medicine and Public Health, University of Granada, Granada, Spain.
Summary
The WINROP algorithm for retinopathy of prematurity (ROP) showed moderate accuracy in Spanish premature infants. Further criteria are needed to improve its sensitivity for detecting treatable ROP cases.
Area of Science:
- Ophthalmology
- Neonatology
- Medical Informatics
Background:
- Retinopathy of prematurity (ROP) is a significant cause of visual impairment in premature infants.
- Early detection and treatment of ROP are crucial to prevent vision loss.
- The online WINROP algorithm was developed as a screening tool for ROP.
Purpose of the Study:
- To evaluate the diagnostic accuracy of the online WINROP algorithm.
- To assess the WINROP algorithm's validity in two distinct Spanish premature infant populations.
- To determine the algorithm's effectiveness in identifying infants requiring ROP treatment.
Main Methods:
- A retrospective study involving 502 premature infants born between 2000 and 2015.
- Application of the WINROP algorithm to establish an alarm threshold for ROP.
- Comparison of WINROP algorithm results with serial clinical examinations for ROP diagnosis.
Main Results:
- The global WINROP algorithm demonstrated a sensitivity of 62% and specificity of 74%.
- Positive predictive value (PPV) was 59%, and negative predictive value (NPV) was 77%.
- The algorithm showed higher sensitivity (76%) for detecting severe ROP.
Conclusions:
- The WINROP screening algorithm exhibited moderate sensitivity in the studied populations.
- A significant number of treatable ROP cases were missed by the algorithm.
- Enhancements, such as incorporating additional criteria, are recommended to improve the algorithm's sensitivity for ROP detection.
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