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Evaluation of a Risk Screening Tool for Retinopathy of Prematurity (ROP) in a German Cohort
Insights
The DIGIROP-Birth algorithm effectively identifies infants at risk for retinopathy of prematurity (ROP). Incorporating peri- and postnatal factors improves ROP screening accuracy for preterm infants.
Area of Science:
- Ophthalmology
- Neonatology
- Medical Informatics
Background:
- Retinopathy of prematurity (ROP) is a leading cause of visual impairment in preterm infants.
- Early identification of infants at risk for ROP is crucial for timely intervention and prevention of vision loss.
- Existing screening methods may benefit from enhanced predictive algorithms.
Purpose of the Study:
- To evaluate the predictive efficacy of the DIGIROP-Birth algorithm for identifying infants at risk of developing retinopathy of prematurity (ROP).
- To assess the performance of the DIGIROP-Birth calculator in a cohort of preterm infants.
Main Methods:
- Retrospective analysis of 897 preterm infants (24 0/7 to 30 6/7 weeks gestational age) from 2010-2020.
- Validation of the DIGIROP-Birth algorithm using receiver-operating characteristic (ROC) curves.
- Calculation of area under the curve (AUC), sensitivity, specificity, and predictive values.
Main Results:
- The DIGIROP-Birth algorithm demonstrated good predictive power with an AUC of 0.860 for ROP requiring treatment.
- Sensitivity and specificity equilibrium was observed at a 4.12% probability threshold.
- Negative predictive value was high at 99.36%, indicating effective identification of infants not requiring treatment.
- Identified emergency cesarean section and mass blood transfusions as significant independent risk factors.
Conclusions:
- The DIGIROP-Birth calculator exhibits strong predictive capabilities for therapy-requiring ROP in the studied preterm infant population.
- The incidence of therapy-requiring ROP in the cohort was 3.79%.
- Integrating peri- and postnatal risk factors into ROP screening protocols is recommended for improved clinical outcomes.
Purpose:
To assess the efficacy of the DIGIROP-Birth algorithm in identifying infants at risk for developing retinopathy of prematurity (ROP).
Methods:
In a retrospective study, we included preterm infants over 11 years, 2010-2020, meeting the inclusion criteria for the DIGIROP-Birth calculator (24 + 0/7 to 30 + 6/7 weeks of gestational age). We assessed the validity of DIGIROP-Birth using receiver-operating characteristic (ROC) curves and calculated area-under-curve (AUC), sensitivity, specificity, and positive and negative predictive values.
Results:
897 infants were included in the analysis. The median age of the first ophthalmological examination was 40 days (IQR 32-50), the median gestational age was 198 days (IQR 185-209; corresponding to 28 + 2/7 gestational weeks), median birth weight was 1000 g (IQR 790-1300). Of 897 screened children, 458 (51.1%) were diagnosed with ROP, and 34 of 897 (3.8%) required treatment.Analysis of ROP requiring treatment predicted by DIGIROP showed an AUC of 0.860 [95%-CI 0.795-0.925]. An equilibrium of sensitivity and specificity existed at a probability of 4.12%. The positive predictive value was 10.95%, and the negative predictive value was 99.36%. Independent significant peri- and postnatal risk factors were emergency cesarean section and mass blood transfusions.
Conclusions:
The DIGIROP-Birth calculator showed good predictive power in our studied population, with an incidence of 3.79% for therapy-requiring ROP. Peri- and postnatal risk factors should be included in ROP screening.
