Diagnostic Accuracy of WINROP, CHOP-ROP and ROPScore in Detecting Type 1 Retinopathy of Prematurity
Deena Thomas1, Shamnad Madathil1, Anu Thukral2
1Division of Neonatology, Department of Pediatrics, All India Institute of Medical Sciences, New Delhi.
Insights
Predicting retinopathy of prematurity (ROP) requires validated algorithms. WINROP, CHOP-ROP, and ROPScore showed insufficient sensitivity for type 1 ROP in Indian neonates, failing to replace current screening methods.
Area of Science:
- Neonatology
- Ophthalmology
- Medical Informatics
Background:
- Retinopathy of prematurity (ROP) screening algorithms need validation in Indian settings.
- Current screening relies on gestational age and weight-based cutoffs.
- Reducing screening burden without compromising sensitivity is a key goal.
Purpose of the Study:
- Evaluate WINROP, CHOP-ROP, and ROPScore algorithms for predicting type 1 ROP.
- Assess the time from alarm to treatment for each algorithm.
- Determine if these algorithms can replace existing screening criteria in India.
Main Methods:
- Ambispective observational study in a tertiary care NICU in India.
- Included 578 neonates born <32 weeks gestation or <1500g between July 2013 and June 2019.
- Primary outcomes: sensitivity, specificity, and time from alarm to treatment.
Main Results:
- Sensitivity for type 1 ROP: WINROP (85%), CHOP-ROP (54%), ROPScore (73%).
- Specificity for type 1 ROP: WINROP (36%), CHOP-ROP (71%), ROPScore (67%).
- Median time from alarm to treatment varied: WINROP (7 weeks), CHOP-ROP (7 weeks), ROPScore (3 weeks).
Conclusions:
- WINROP, CHOP-ROP, and ROPScore algorithms were not sufficiently sensitive to replace current ROP screening methods.
- Gestational age, weight, and risk factor-based screening remain crucial.
- Further research may be needed for algorithm refinement in diverse populations.
Background:
Algorithms for predicting retinopathy of prematurity (ROP) requiring treatment need to be validated in Indian settings to determine if the burden of screening can be reduced without compromising the sensitivity of existing gestation and weight-based cut offs.
Objective:
To evaluate the performance of the available algorithms namely, WINROP (Weight, Insulin-like growth factor I, Neonatal ROP), CHOP-ROP (Children's Hospital of Philadelphia ROP) and ROPScore in predicting type 1 ROP and time from alarm to treatment by each algorithm.
Study Design:
Ambispective observational.
Setting:
Tertiary care neonatal intensive care unit in India.
Participants:
Neonates less than 32 weeks or less than 1500 g born between July, 2013 to June, 2019 (N=578), who underwent ROP screening.
Primary Outcome:
Sensitivity, specificity and time from alarm to treatment by each algorithm.
Results:
The sensitivity and specificity of WINROP was 85% and 36%, for CHOP-ROP it was 54% and 71%, and for ROPScore it was 73% and 67%, respectively in detecting type 1 ROP. A total of 50/51 (98%) of neonates with type 1 ROP underwent treatment at median gestation of 9 weeks and median time from alarm to treatment by WINROP, CHOP-ROP and ROPScore was 7, 7 and 3 weeks, respectively.
Conclusion:
WINROP, CHOP-ROP and ROPScore were not sensitive enough to replace the gestational age, weight and risk factor-based screening criteria for type 1 ROP.
