Colorado retinopathy of prematurity model: a multi-institutional validation study

Comparison of Weight-Gain-Based Prediction Models for Retinopathy of Prematurity in an Australian Population

Purpose

Four weight-gain-based algorithms are compared for the prediction of type 1 ROP in an Australian cohort: the weight, insulin-like growth factor, neonatal retinopathy of prematurity (WINROP) algorithm, the Children's Hospital of Philadelphia Retinopathy of Prematurity (CHOPROP), the Colorado Retinopathy of Prematurity (CO-ROP) algorithm, and the postnatal growth, retinopathy of prematurity (G-ROP) algorithm.

Methods

A four-year retrospective cohort analysis of infants screened for ROP in a tertiary neonatal intensive care unit in Brisbane, Australia. The main outcome measures were sensitivities, specificities, and positive and negative predictive values.

Results

531 infants were included (mean gestational age 28 + 3). 24 infants (4.5%) developed type 1 ROP. The sensitivities, specificities, and negative predictive values, respectively, for type 1 ROP (95% confidence intervals) were for WINROP 83.3% (61.1-93.3%), 52.3% (47.8-56.7%), and 98.4% (96.1-99.4%); for CHOPROP 100% (86.2-100%), 46.0% (41.7-50,3%), and 100% (98.4-100%); for CO-ROP 100% (86.2-100%), 32.0% (28.0%-36.1%), and 100% (98.3-100%); and for G-ROP 100% (86.2-100%), 28.2% (24.5-32.3%), and 100% (97.4-100%). Of the five infants with persistent nontype 1 ROP that underwent treatment, only CO-ROP was able to successfully identify all.

Conclusions

CHOPROP, CO-ROP, and G-ROP performed well in this Australian population. CHOPROP, CO-ROP, and G-ROP would reduce the number of infants requiring examinations by 43.9%, 30.5%, and 26.9%, respectively, compared to current ROP screening guidelines. Weight-gain-based algorithms would be a useful adjunct to the current ROP screening.

Validation of DIGIROP models and decision support tool for prediction of treatment for retinopathy of prematurity on a contemporary Swedish cohort

BACKGROUND/AIMS

Retinopathy of prematurity (ROP) is currently diagnosed through repeated eye examinations to find the low percentage of infants that fulfil treatment criteria to reduce vision loss. A prediction model for severe ROP requiring treatment that might sensitively and specifically identify infants that develop severe ROP, DIGIROP-Birth, was developed using birth characteristics. DIGIROP-Screen additionally incorporates first signs of ROP in different models over time. The aim was to validate DIGIROP-Birth, DIGIROP-Screen and their decision support tool on a contemporary Swedish cohort.

METHODS

Data were retrieved from the Swedish national registry for ROP (2018-2019) and two Swedish regions (2020), including 1082 infants born at gestational age (GA) 24 to <31 weeks. The predictors were GA at birth, sex, standardised birth weight and age at the first sign of ROP. The outcome was ROP treatment. Sensitivity, specificity and area under the receiver operating characteristic curve (AUC) with 95% CI were described.

RESULTS

For DIGIROP-Birth, the AUC was 0.93 (95% CI 0.90 to 0.95); for DIGIROP-Screen, it ranged between 0.93 and 0.97. The specificity was 49.9% (95% CI 46.7 to 53.0) and the sensitivity was 96.5% (95% CI 87.9 to 99.6) for the tool applied at birth. For DIGIROP-Screen, the cumulative specificity ranged between 50.0% and 78.7%. One infant with Beckwith-Wiedemann syndrome who fulfilled criteria for ROP treatment and had no missed/incomplete examinations was incorrectly flagged as not needing screening.

CONCLUSIONS

DIGIROP-Birth and DIGIROP-Screen showed high predictive ability in a contemporary Swedish cohort. At birth, 50% of the infants born at 24 to <31 weeks of gestation were predicted to have low risk of severe ROP and could potentially be released from ROP screening examinations. All routinely screened treated infants, excluding those screened for clinical indications of severe illness, were correctly flagged as needing ROP screening.

Validation of the postnatal growth and retinopathy of prematurity (G-ROP) screening criteria in a Thai cohort

PURPOSE

To validate Postnatal Growth and Retinopathy of Prematurity (G-ROP) criteria for Thai infants.

STUDY DESIGN

A retrospective review of infants receiving ROP screening during 2009-2020.

METHODS

Baseline characteristics, clinical progression and final ROP outcomes were collected. G-ROP was applied to infants who met at least one of the following 6 criteria: birth weight (BW) below 1051 g, gestational age (GA) under 28 weeks, weight gain (WG) less than 120 g during postnatal day 10-19, WG less than 180 g during day 20-29, WG less than 170 g during day 30-39 and hydrocephalus.

RESULTS

A total of 684 infants (boys, 53.4%) were included. Median (IQR) BW was 1200 (960-1470) grams and median GA was 30 (28-32) weeks. Prevalence of ROP was 26.6%, with 28 (4.1%) having type 1, 19 (2.8%) type 2 and, 135 (19.7%) having other ROP. Treatment was performed in 26 infants (3.8%). Sensitivity of G-ROP to include type 1, 2 or treatment-requiring ROP cases was 100% with 36.9% specificity, excluding 235 (34.4%) cases of unnecessary screening. To adjust for our setting of initial eye examination at 4 weeks' postnatal date, the last 2 criteria of G-ROP were replaced by the occurrence of grade 3 or 4 intraventricular hemorrhage (IVH). This modified G-ROP criteria yielded 100% sensitivity, 42.5% specificity and excluded 271 (39.6%) cases of unnecessary screening.

CONCLUSION

G-ROP criteria can be applied to our hospital setting. Occurrence of IVH grade 3 or 4 was proposed as an alternative in modified G-ROP criteria.

Modifiable Risk Factors and Preventative Strategies for Severe Retinopathy of Prematurity

Severe ROP is characterized by the development of retinal fibrovascular proliferation that may progress to retinal detachment. The purpose of this report is to review five of the most common and well-studied perinatal and neonatal modifiable risk factors for the development of severe ROP. Hyperoxemia, hypoxia, and associated prolonged respiratory support are linked to the development of severe ROP. While there is a well-established association between clinical maternal chorioamnionitis and severe ROP, there is greater variability between histologic chorioamnionitis and severe ROP. Neonatal sepsis, including both bacterial and fungal subtypes, are independent predictors of severe ROP in preterm infants. Although there is limited evidence related to platelet transfusions, the risk of severe ROP increases with the number and volume of red blood cell transfusions. Poor postnatal weight gain within the first six weeks of life is also strongly tied to the development of severe ROP. We also discuss preventative strategies that may reduce the risk of severe ROP. Limited evidence-based studies exist regarding the protective effects of caffeine, human milk, and vitamins A and E.

Retrospective validation of G-ROP, CO-ROP, Alex-ROP, and ROPscore predictive algorithms in two Chinese medical centers

Purpose

To evaluate the sensitivity and specificity of four predictive algorithms (G-ROP, CO-ROP, Alex-ROP, and ROPscore) for retinopathy of prematurity and compare their performances in the Chinese population.

Methods

A retrospective study was conducted at two medical centers in China of infants born at Women's Hospital School of Medicine Zhejiang University and Yiwu Maternal and Child Health Hospital. A total of 1,634 infants who met the criteria and who were GA < 32 weeks or BW < 2,000 g according to Chinese guidelines for ROP screening were included. The ROP group was further grouped into severe ROP and mild ROP. The sensitivity and specificity of G-ROP, two simplified G-ROPs, CO-ROP, Alex-ROP, and ROPscore were analyzed.

Results

Severe ROP and any ROP were identified in 25 and 399 of 1,634 infants, respectively. According to the criteria of different models, 844, 1,122, 1,122, and 587 infants were eligible in the G-ROP, CO-ROP, Alex-ROP, and ROPscore, respectively. G-ROP had 96.0% sensitivity and 35.0% specificity for severe ROP. For two simplified G-ROPs (180 g and 200 g models), similar sensitivity was showed with original G-ROP and they had specificity of 21.8% and 14.0%, respectively. The sensitivity and specificity of Co-ROP were 96% and 64.3% for severe ROP, while Alex-ROP only had sensitivity of 56.0% and specificity of 61.4% for severe ROP. ROPscore had a sensitivity of 91.3% and a specificity of 62.4% for severe ROP. In 546 infants who met all 4 models' inclusion criteria and included 23 infants with severe ROP, the validation outcomes showed the sensitivity of G-ROP, ROPscore, CO-ROP, and Alex-ROP for severe ROP was 95.6%, 91.3%, 100%, and 56.0%, and their specificity was 38.0%, 60.8%, 39.9%, and 52.9%, respectively.

Conclusion

G-ROP, ROPscore, and CO-ROP had high sensitivity for severe ROP in the Chinese population, but both the sensitivity and specificity of Alex-ROP were low. CO-ROP (not high-grade CO-ROP) provided the best performance for severe ROP in a fair comparison. For further application, ROP screening models need to be adjusted by local populations.

Trends in Neonatal Ophthalmic Screening Methods

Neonatal ophthalmic screening should lead to early diagnosis of ocular abnormalities to reduce long-term visual impairment in selected diseases. If a treatable pathology is diagnosed within a few days after the birth, adequate therapy may be indicated to facilitate the best possible conditions for further development of visual functions. Traditional neonatal ophthalmic screening uses the red reflex test (RRT). It tests the transmittance of the light through optical media towards the retina and the general disposition of the central part of the retina. However, RRT has weaknesses, especially in posterior segment affections. Wide-field digital imaging techniques have shown promising results in detecting anterior and posterior segment pathologies. Particular attention should be paid to telemedicine and artificial intelligence. These methods can improve the specificity and sensitivity of neonatal eye screening. Both are already highly advanced in diagnosing and monitoring of retinopathy of prematurity.

Validation of the Postnatal Growth and Retinopathy of Prematurity Screening Criteria in a Taiwanese Cohort

PURPOSE

To validate the performance of Postnatal Growth and Retinopathy of Prematurity (G-ROP) screening criteria in a Taiwanese cohort.

DESIGN

Screening evaluation with retrospective data.

METHOD

Premature infants who underwent retinopathy of prematurity (ROP) screening between January 2015 and April 2019 at a tertiary hospital were examined. Infants with known final ROP results and complete longitudinal weight records were included. G-ROP screening criteria, both original and simplified (G-ROP 180 g), were applied as the prediction model for type 1 ROP; sensitivity and specificity were analyzed. The reduction in the number of infants requiring ROP screening and the number of funduscopic examinations were calculated.

RESULT

A total of 303 infants with documented ROP outcomes and complete weight gain records were examined. Of these, 103 infants developed ROP, of whom 29 developed type 1 ROP, whereas the other 200 did not develop ROP. For the detection of type 1 ROP, the sensitivity and specificity of the original G-ROP screening criteria were 96.6% and 42.3%, and 100% and 31%, for the simplified G-ROP 180 g model, respectively. The reduction in the number of infants requiring screening and funduscopic examinations was 32.6% and 33.5% for the original G-ROP criteria, and 28.1% and 23.2% for the G-ROP 180 g model, respectively.

CONCLUSION

Both the original G-ROP and G-ROP 180 g criteria attained high sensitivities in detecting type 1 ROP in the current Taiwanese cohort, with the G-ROP 180-g model outperforming the original one. Validation and modification may be required before applying G-ROP screening criteria to different populations.

The Use of Postnatal Weight Gain Algorithms to Predict Severe or Type 1 Retinopathy of Prematurity: A Systematic Review and Meta-analysis

IMPORTANCE

The currently recommended method for screening for retinopathy of prematurity (ROP) is binocular indirect ophthalmoscopy, which requires frequent eye examinations entailing a heavy clinical workload. Weight gain-based algorithms have the potential to minimize the need for binocular indirect ophthalmoscopy and have been evaluated in different setups with variable results to predict type 1 or severe ROP.

OBJECTIVE

To synthesize evidence regarding the ability of postnatal weight gain-based algorithms to predict type 1 or severe ROP.

DATA SOURCES

PubMed, MEDLINE, Embase, and the Cochrane Library databases were searched to identify studies published between January 2000 and August 2021.

STUDY SELECTION

Prospective and retrospective studies evaluating the ability of these algorithms to predict type 1 or severe ROP were included.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently extracted data. This meta-analysis was performed according to the Cochrane guidelines and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis of Diagnostic Test Accuracy Studies (PRISMA-DTA) guidelines.

MAIN OUTCOMES AND MEASURES

Ability of algorithms to predict type 1 or sever ROP was measured using statistical indices (pooled sensitivity, specificity, and summary area under the receiver operating characteristic curves, as well as pooled negative likelihood ratios and positive likelihood ratios and diagnostic odds ratios).

RESULTS

A total of 61 studies (>37 000 infants) were included in the meta-analysis. The pooled estimates for sensitivity and specificity, respectively, were 0.89 (95% CI, 0.85-0.92) and 0.57 (95% CI, 0.51-0.63) for WINROP (Weight, IGF-1 [insulinlike growth factor 1], Neonatal, ROP), 1.00 (95% CI, 0.88-1.00) and 0.60 (95% CI, 0.15-0.93) for G-ROP (Postnatal Growth and ROP), 0.95 (95% CI, 0.71-0.99) and 0.52 (95% CI, 0.36-0.68) for CHOP ROP (Children's Hospital of Philadelphia ROP), 0.99 (95% CI, 0.73-1.00) and 0.49 (95% CI, 0.03-0.74) for ROPScore, 0.98 (95% CI, 0.94-0.99) and 0.35 (95% CI, 0.22-0.51) for CO-ROP (Colorado ROP). The original PINT (Premature Infants in Need of Transfusion) ROP study reported a sensitivity of 0.98 (95% CI, 0.91-0.99) and a specificity of 0.36 (95% CI, 0.30-0.42). The pooled negative likelihood ratios were 0.19 (95% CI, 0.13-0.27) for WINROP, 0.0 (95% CI, 0.00-0.32) for G-ROP, 0.10 (95% CI, 0.02-0.53) for CHOP ROP, 0.03 (95% CI, 0.00-0.77) for ROPScore, and 0.07 (95% CI, 0.03-0.16) for CO-ROP. The pooled positive likelihood ratios were 2.1 (95% CI, 1.8-2.4) for WINROP, 2.5 (95% CI, 0.7-9.1) for G-ROP, 2.0 (95% CI, 1.5-2.6) for CHOP ROP, 1.9 (95% CI, 1.1-3.3) for ROPScore, and 1.5 (95% CI, 1.2-1.9) for CO-ROP.

CONCLUSIONS AND RELEVANCE

This study suggests that weight gain-based algorithms have adequate sensitivity and negative likelihood ratios to provide reasonable certainty in ruling out type 1 ROP or severe ROP. Given the implications of missing even a single case of severe ROP, algorithms with very high sensitivity (close to 100%) and low negative likelihood ratios (close to zero) need to be chosen to safely reduce the number of unnecessary examinations in infants at lower risk of severe ROP.

Individual Risk Prediction for Sight-Threatening Retinopathy of Prematurity Using Birth Characteristics

Question

Can a prediction model be constructed for retinopathy of prematurity needing treatment by using only birth characteristics data and applying advanced statistical methods?

Findings

In this cohort study of 6947 infants born at gestational age 24 to 30 weeks, the prediction model incorporating only postnatal age, gestational age, sex, and birth weight provided a predictive ability for retinopathy of prematurity needing treatment that was comparable to current models requiring postnatal data (not always available). The risk for retinopathy of prematurity needing treatment increased up to 12 weeks’ postnatal age irrespective of the infants’ gestational age.

Meaning

This prediction model identifying infants with a high risk for developing sight-threatening disease at an early time may improve the conditions for optimal screening.

Importance

To prevent blindness, repeated infant eye examinations are performed to detect severe retinopathy of prematurity (ROP), yet only a small fraction of those screened need treatment. Early individual risk stratification would improve screening timing and efficiency and potentially reduce the risk of blindness.

Objectives

To create and validate an easy-to-use prediction model using only birth characteristics and to describe a continuous hazard function for ROP treatment.

Design, Setting, and Participants

In this retrospective cohort study, Swedish National Patient Registry data from infants screened for ROP (born between January 1, 2007, and August 7, 2018) were analyzed with Poisson regression for time-varying data (postnatal age, gestational age [GA], sex, birth weight, and important interactions) to develop an individualized predictive model for ROP treatment (called DIGIROP-Birth [Digital ROP]). The model was validated internally and externally (in US and European cohorts) and compared with 4 published prediction models.

Main Outcomes and Measures

The study outcome was ROP treatment. The measures were estimated momentary and cumulative risks, hazard ratios with 95% CIs, area under the receiver operating characteristic curve (hereinafter referred to as AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

Results

Among 7609 infants (54.6% boys; mean [SD] GA, 28.1 [2.1] weeks; mean [SD] birth weight, 1119 [353] g), 442 (5.8%) were treated for ROP, including 142 (40.1%) treated of 354 born at less than 24 gestational weeks. Irrespective of GA, the risk for receiving ROP treatment increased during postnatal weeks 8 through 12 and decreased thereafter. Validations of DIGIROP-Birth for 24 to 30 weeks’ GA showed high predictive ability for the model overall (AUC, 0.90 [95% CI, 0.89-0.92] for internal validation, 0.94 [95% CI, 0.90-0.98] for temporal validation, 0.87 [95% CI, 0.84-0.89] for US external validation, and 0.90 [95% CI, 0.85-0.95] for European external validation) by calendar periods and by race/ethnicity. The sensitivity, specificity, PPV, and NPV were numerically at least as high as those obtained from CHOP-ROP (Children’s Hospital of Philadelphia–ROP), OMA-ROP (Omaha-ROP), WINROP (weight, insulinlike growth factor 1, neonatal, ROP), and CO-ROP (Colorado-ROP), models requiring more complex postnatal data.

Conclusions and Relevance

This study validated an individualized prediction model for infants born at 24 to 30 weeks’ GA, enabling early risk prediction of ROP treatment based on birth characteristics data. Postnatal age rather than postmenstrual age was a better predictive variable for the temporal risk of ROP treatment. The model is an accessible online application that appears to be generalizable and to have at least as good test statistics as other models requiring longitudinal neonatal data not always readily available to ophthalmologists.

Validation of the Postnatal Growth and Retinopathy of Prematurity Screening Criteria

Importance

The first Postnatal Growth and Retinopathy of Prematurity Study (G-ROP-1) developed new screening criteria with 100% sensitivity for type 1 retinopathy of prematurity (ROP) and 30% reduction of infants requiring examinations in a retrospective development cohort of 7483 infants from 29 North American hospitals in 2006-2012. Infants meeting 1 or more of the following criteria undergo examinations: gestational age less than 28 weeks or birth weight less than 1051 g; weight gain less than 120 g during age 10 to 19 days, weight gain less than 180 g during age 20 to 29 days, or weight gain less than 170 g during age 30 to 39 days; or hydrocephalus.

Objective

To evaluate the generalizability of the G-ROP screening criteria in a new cohort of at-risk infants.

Design, Setting, and Participants

This prospective validation cohort study (G-ROP-2) was conducted at 41 hospitals in the United States and Canada (25 G-ROP-1 hospitals and 16 new hospitals) from September 8, 2015, to June 13, 2017, among 3981 premature infants at risk for ROP and with known ROP outcomes.

Main Outcomes and Measures

Sensitivity for Early Treatment for Retinopathy of Prematurity Study type 1 ROP and potential reduction in infants receiving examinations.

Results

Among the 3981 infants in the study (1878 girls and 2103 boys; median gestational age, 28 weeks [range, 22-35 weeks]; median birth weight, 1072 g [range, 350-4080 g]; 1966 white; 942 black; 321 Latino; 120 Asian; 22 Native Hawaian or Pacific Islander; and 25 American Indian or Alaskan Native), the G-ROP criteria correctly predicted 219 of 219 cases of type 1 ROP (sensitivity, 100%; 95% CI, 98.3%-100%), while reducing the number of infants undergoing examinations by 35.6% (n = 1418). In a combined G-ROP-1 and G-ROP-2 cohort of 11 463 infants, the G-ROP criteria predicted 677 of 677 cases of type 1 ROP (sensitivity, 100%; 95% CI, 99.4%-100%), reducing the number of infants receiving examinations by 32.5% (n = 3730), while current criteria (birth weight <1501 g or gestational age ≤30 weeks 0 days) predicted 674 of 677 type 1 cases (sensitivity, 99.6%; 95% CI, 98.7%-99.8%).

Conclusions and Relevance

This study found that the G-ROP screening criteria were generalizable on validation and, if used clinically in the United States and Canada, could reduce the number of infants receiving examinations. The large G-ROP cohorts provide evidence-based screening criteria that have higher sensitivity and higher specificity (fewer infants receiving examinations) for type 1 ROP than currently recommended guidelines.

New evidence on the protector effect of weight gain in retinopathy of prematurity

INTRODUCTION

Retinopathy of prematurity (ROP) is characterised by insufficient vascular development in the retina, and requires early treatment to avoid visual disability in severe cases. ROP is currently the second leading cause of preventable child blindness in the world.

PATIENTS AND METHODS

This was an observational, retrospective, case-control study including 233 preterm infants examined between 1999 and 2019.

RESULTS

Postnatal weight gain in the first 4 weeks of life, birth weight, gestational age, mechanical ventilation, transfusion, presence of sepsis, persistence of arterial ductus, necrotising enterocolitis, intraventricular haemorrhage, or periventricular leukomalacia were found to be significantly different between the ROP groups requiring and not requiring treatment. The mean postnatal weight gain in the ROP group not requiring treatment was 12.75 ± 5.99 g/day, whereas it was 9.50 ± 5.45 g/day in the ROP group requiring treatment. The risk of developing ROP that required treatment decreased with an increase in weight gain. The risk reduction was 2.76%-8.35% in preterm infants gaining 10 g/day, and 7.17%-12.76% in infants gaining 20 g/day.

CONCLUSIONS

The risk of developing ROP requiring treatment decreased with increasing weight gain in the first 4 weeks of life. This was applicable in infants with postnatal weight gain ≥14 g/day. However, gestational age, birth weight, time of mechanical ventilation, and comorbidity should be taken into account when evaluating the risk of ROP requiring treatment.

Validation of the DIGIROP-birth model in a Chinese cohort

Background

We aimed to validate the predictive performance of the DIGIROP-Birth model for identifying treatment-requiring retinopathy of prematurity (TR-ROP) in Chinese preterm infants to evaluate its generalizability across countries and races.

Methods

We retrospectively reviewed the medical records of preterm infants who were screened for retinopathy of prematurity (ROP) in a single Chinese hospital between June 2015 and August 2020. The predictive performance of the model for TR-ROP was assessed through the construction of a receiver-operating characteristic (ROC) curve and calculating the areas under the ROC curve (AUC), sensitivity, specificity, and positive and negative predictive values.

Results

Four hundred and forty-two infants (mean (SD) gestational age = 28.8 (1.3) weeks; mean (SD) birth weight = 1237.0 (236.9) g; 64.7% males) were included in the study. Analyses showed that the DIGIROP-Birth model demonstrated less satisfactory performance than previously reported in identifying infants with TR-ROP, with an area under the receiver-operating characteristic curve of 0.634 (95% confidence interval = 0.564–0.705). With a cutoff value of 0.0084, the DIGIROP-Birth model showed a sensitivity of 48/93 (51.6%), which increased to 89/93 (95.7%) after modification with the addition of postnatal risk factors. In infants with a gestational age < 28 weeks or birth weight < 1000 g, the DIGIROP-Birth model exhibited sensitivities of 36/39 (92.3%) and 20/23 (87.0%), respectively.

Conclusions

Although the predictive performance was less satisfactory in China than in developed countries, modification of the DIGIROP-Birth model with postnatal risk factors shows promise in improving its efficacy for TR-ROP. The model may also be effective in infants with a younger gestational age or with an extremely low birth weight.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12886-021-01952-0.

Development and validation of a new clinical decision support tool to optimize screening for retinopathy of prematurity

BACKGROUND/AIMS

Prematurely born infants undergo costly, stressful eye examinations to uncover the small fraction with retinopathy of prematurity (ROP) that needs treatment to prevent blindness. The aim was to develop a prediction tool (DIGIROP-Screen) with 100% sensitivity and high specificity to safely reduce screening of those infants not needing treatment. DIGIROP-Screen was compared with four other ROP models based on longitudinal weights.

METHODS

Data, including infants born at 24-30 weeks of gestational age (GA), for DIGIROP-Screen development (DevGroup, N=6991) originate from the Swedish National Registry for ROP. Three international cohorts comprised the external validation groups (ValGroups, N=1241). Multivariable logistic regressions, over postnatal ages (PNAs) 6-14 weeks, were validated. Predictors were birth characteristics, status and age at first diagnosed ROP and essential interactions.

RESULTS

ROP treatment was required in 287 (4.1%)/6991 infants in DevGroup and 49 (3.9%)/1241 in ValGroups. To allow 100% sensitivity in DevGroup, specificity at birth was 53.1% and cumulatively 60.5% at PNA 8 weeks. Applying the same cut-offs in ValGroups, specificities were similar (46.3% and 53.5%). One infant with severe malformations in ValGroups was incorrectly classified as not needing screening. For all other infants, at PNA 6-14 weeks, sensitivity was 100%. In other published models, sensitivity ranged from 88.5% to 100% and specificity ranged from 9.6% to 45.2%.

CONCLUSIONS

DIGIROP-Screen, a clinical decision support tool using readily available birth and ROP screening data for infants born GA 24-30 weeks, in the European and North American populations tested can safely identify infants not needing ROP screening. DIGIROP-Screen had equal or higher sensitivity and specificity compared with other models. DIGIROP-Screen should be tested in any new cohort for validation and if not validated it can be modified using the same statistical approaches applied to a specific clinical setting.

Prenatal intrauterine growth restriction and risk of retinopathy of prematurity

Low birthweight and decreased postnatal weight gain are known predictors of worse retinopathy of prematurity (ROP) but the role of prenatal growth patterns in ROP remains inconclusive. To distinguish small for gestational age (SGA) from intrauterine growth restriction (IUGR) as independent predictors of ROP, we performed a retrospective cohort study of patients who received ROP screening examinations at a level IV neonatal intensive care unit over a 7-year period. Data on IUGR and SGA status, worst stage of and need for treatment for ROP, and postnatal growth was obtained. 343 infants were included for analysis (mean gestational age = 28.6 weeks and birth weight = 1138.2 g). IUGR infants were more likely to have a worse stage of ROP and treatment-requiring ROP (both p < 0.0001) compared to non-IUGR infants. IUGR infants were more likely to be older at worst stage of ROP (p < 0.0001) and to develop postnatal growth failure (p = 0.01) than non-IUGR infants. Independent of postnatal growth failure status, IUGR infants had a 4-5 × increased risk of needing ROP treatment (p < 0.001) compared to non-IUGR infants. SGA versus appropriate for gestational age infants did not demonstrate differences in retinopathy outcomes, age at worst ROP stage, or postnatal growth failure. These findings emphasize the importance of prenatal growth on ROP development.

POOR POSTNATAL WEIGHT GAIN AS A PREDICTOR OF RETINOPATHY OF PREMATURITY

The purpose of this study was to re-evaluate cut-off values used in screening for retinopathy of prematurity (ROP) in Croatia and to propose postnatal weight gain as an additional criterion, based on the Colorado Retinopathy of Prematurity prediction model. Medical records of 267 premature infants from the Zagreb University Hospital Centre that underwent ROP screening between January 2009 and December 2010 were reviewed retrospectively. Collected data included gestational age, birth weight, sex, weekly weight measurements and fundus examination records. Results showed the cut-off values of gestational age (GA) and birth weight (BW) used in Croatia to be appropriate and postnatal weight gain in the first 28 days could be used as an additional criterion on screening in the following way: net weight gain in the first 28 days of ≤932 g for prediction of any form of ROP and of ≤660 g for prediction of severe ROP should be added to the existing criteria of GA (≤32 weeks) and/or BW (≤1500 g). Infants with a non-physiological postnatal weight gain are exception. This is the first Croatian study to propose postnatal weight gain as an additional criterion on ROP screening and requires further validation on a larger sample of Croatian infants.

Validation of the postnatal growth and retinopathy of prematurity screening criteria

The objective of this study was to validate the generalizability of the Postnatal Growth and Retinopathy of Prematurity Study screening criteria in a new cohort of infants at risk for retinopathy of prematurity (ROP). This retrospective validation study conducted at a single academic medical center included 484 infants at risk for ROP born between January 14, 2014, and December 21, 2019. The primary outcomes evaluated were sensitivity for both type 1 and type 2 ROP, as defined by the Early Treatment of Retinopathy of Prematurity Study, as well as the reduction in total number of infants requiring ROP examinations. Secondary outcomes included the total number of ROP examinations avoided and the potential cost reduction of eliminating these examinations. In a cohort of 484 infants at risk for ROP, the criteria identified 40 of 40 (100%, 95% confidence interval 91.19%-100%) type 1 ROP cases and 27 of 27 (100%, 95% confidence interval 87.23%-100%) type 2 ROP cases while reducing the total number of infants screened by 35.7%. The Postnatal Growth and Retinopathy of Prematurity Study criteria were found in this study to be generalizable to a cohort of infants at a single teaching institution in central Texas. If applied during the studied interval, these criteria could have significantly reduced the number of infants undergoing ROP examinations and maintained excellent sensitivity for type 1 ROP.

Evaluation of the economic impact of modified screening criteria for retinopathy of prematurity from the Postnatal Growth and ROP (G-ROP) study

IMPORTANCE

The Postnatal Growth and Retinopathy of Prematurity (G-ROP) Study showed that the addition of postnatal weight gain to birth weight and gestational age detects similar numbers of infants with ROP, but requires examination of fewer infants.

OBJECTIVE

To determine the incremental cost-effectiveness of screening with G-ROP compared with conventional screening.

DESIGN, SETTING AND PARTICIPANTS

We built a microsimulation model of a 1-year US birth cohort <32 weeks gestation, using data from the G-ROP study. We obtained resource utilization estimates from the G-ROP dataset and from secondary sources, and test characteristics from the G-ROP cohort.

RESULTS

Among 78,281 infants nationally, screening with G-ROP detected ~25 additional infants with Type 1 ROP. This was accomplished with 36,233 fewer examinations, in 14,073 fewer infants, with annual cost savings of approximately US$2,931,980 through hospital discharge.

CONCLUSIONS

Screening with G-ROP reduced costs while increasing the detection of ROP compared with current screening guidelines.

Risk of development of treated retinopathy of prematurity in very low birth weight infants

OBJECTIVE

Quantify the risk of treatment for retinopathy of prematurity (ROP) among infants meeting current U.S. screening guidelines.

STUDY DESIGN

Among infants ≤1500 g birth weight or ≤30 weeks gestation screened for ROP from 2006-2015, we developed a risk prediction model to identify infants treated for ROP. We applied our model to a separate infant cohort discharged in 2016.

RESULT

Seventy-five thousand eight hundred and twenty one infants met inclusion criteria; 2306 (3%) were treated for ROP. Infants with several risk factor combinations (no ventilator support or oxygen on postnatal day 28, no history of necrotizing enterocolitis, and no intraventricular hemorrhage) were at low risk of ROP. Applied to 6127 infants discharged in 2016, our model had 97.9% sensitivity, 63.3% specificity, positive predictive value of 4.0%, and negative predictive value of 99.9%.

CONCLUSION

Large numbers of infants at low risk of developing ROP are required to undergo screening. Refining current ROP guidelines may reduce unnecessary examinations.

Development of Modified Screening Criteria for Retinopathy of Prematurity: Primary Results From the Postnatal Growth and Retinopathy of Prematurity Study

Importance

Current retinopathy of prematurity (ROP) guidelines, which are based on studies of high-risk infants and expert opinion, have low specificity for disease requiring treatment. Postnatal weight gain-based models improve specificity but have been limited by complexity and small development cohorts, which results in model overfitting and resultant decreased sensitivity in validation studies.

Objective

To develop a birth weight (BW), gestational age (GA), and weight gain (WG) prediction model using data from a broad-risk cohort of premature infants.

Design, Setting, and Participants

The Postnatal Growth and ROP Study was a retrospective multicenter cohort study conducted in 29 hospitals in the United States and Canada from 2006 to 2012 that included 7483 premature infants at risk for ROP with a known ROP outcome. A hybrid modeling approach was used that combined BW/GA criteria, weight comparison with expected growth from infants without ROP, multiple growth-interval assessments, consideration of nonphysiological WG, and user-friendly screening criteria. Numerous BW/GA levels, postnatal age periods, time intervals, and WG percentile thresholds were evaluated to identify the most robust parameters.

Main Outcome and Measures

Sensitivity for Early Treatment of ROP Study type 1 ROP and potential reduction in infants who require examinations.

Results

Of 7483 infants, the median (SD) BW was 1099 (359) g, the median GA was 28 weeks (range, 22-35), 3575 (47.8%) were female, 3615 (48.4%) were white, 2310 (30.9%) were black, 233 (3.1%) were Asian, 93 (1.2%) were Pacific Islander, and 40 (0.5%) were American Indian/Alaskan Native. Infants who met any of 6 criteria would undergo examinations: (1) a GA of younger than 28 weeks; (2) a BW of less than 1051 g; a WG of less than 120 g, 180 g, or 170 g during ages 10 to 19, 20 to 29, or 30 to 39 days, respectively; or hydrocephalus. These criteria predicted 459 of 459 (100%) type 1 (sensitivity, 100%; 95% CI, 99.2%-100%), 524 of 524 (100%) treated, and 466 of 472 (98.7%) type 2 cases while reducing the number of infants who required examinations by 2269 (30.3%).

Conclusions and Relevance

This cohort study, broadly representative of infants who are undergoing ROP examinations, provides evidence-based screening criteria. With validation, the Postnatal Growth and ROP Study criteria could be incorporated into ROP screening guidelines to reduce the number of infants who require examinations in North America.

Postnatal weight gain and retinopathy of prematurity

Infants meeting retinopathy of prematurity (ROP) screening guidelines based on birth weight and gestational age undergo serial examinations by ophthalmologists for detection and treatment. However, less than 10% require treatment, and less than half develop ROP. Slow postnatal weight gain is highly predictive of ROP, and investigators have incorporated weight gain measures to develop more specific criteria for ROP screening. Such clinical prediction model use involves a large development study, validation studies specific to the target populations, and ongoing impact surveillance, with adjustment as necessary. Of the many weight gain inclusive prediction models intended to improve the precision of ROP screening, the Postnatal Growth and ROP (G-ROP) modified screening criteria were developed using the largest dataset and may provide the most robust model for clinical use. A recently completed G-ROP validation study will evaluate the generalizability of these modified criteria prior to clinical use.

Screening Examination of Premature Infants for Retinopathy of Prematurity

This policy statement revises a previous statement on screening of preterm infants for retinopathy of prematurity (ROP) that was published in 2013. ROP is a pathologic process that occurs in immature retinal tissue and can progress to a tractional retinal detachment, which may then result in visual loss or blindness. For more than 3 decades, treatment of severe ROP that markedly decreases the incidence of this poor visual outcome has been available. However, severe, treatment-requiring ROP must be diagnosed in a timely fashion to be treated effectively. The sequential nature of ROP requires that infants who are at-risk and preterm be examined at proper times and intervals to detect the changes of ROP before they become destructive. This statement presents the attributes of an effective program to detect and treat ROP, including the timing of initial and follow-up examinations.

Implementation of a Clinical Prediction Model Using Daily Postnatal Weight Gain, Birth Weight, and Gestational Age to Risk Stratify ROP

PURPOSE

To develop a simple prognostic model using postnatal weight gain, birth weight, and gestational age to identify infants at risk for developing severe retinopathy of prematurity (ROP).

METHODS

Medical records from two tertiary referral centers with the diagnosis code "Retinopathy of Prematurity" were evaluated. Those with a birth weight of 1,500 g or less, gestational age of 30 weeks or younger, and unstable clinical courses were included. Multivariate regression analysis was applied to transform three independent variables into a growth rate algorithm.

RESULTS

Seventeen of 191 neonates had severe ROP. Weight gain of at least 23 g/d was determined as a protective cut-off value against development of severe ROP. This value maintained 100% sensitivity with 62% specificity to ensure all neonates who require treatment would be captured. Overall, the Omaha (OMA)-ROP model calculated a 58% reduction in eye examinations within the cohort.

CONCLUSIONS

Inclusion of postnatal growth rate in risk stratification will minimize the number of eye examinations performed without increasing adverse visual outcomes. The OMA-ROP model predicts neonates who gain less than 23 g/d are at higher risk for developing severe ROP. Although promising, larger cohort studies may be necessary to validate and implement new screening practices among preterm infants. [J Pediatr Ophthalmol Strabismus. 2018;55(5):326-334.].

Retinopathy of prematurity: a review of risk factors and their clinical significance

Retinopathy of prematurity (ROP) is a retinal vasoproliferative disease that affects premature infants. Despite improvements in neonatal care and management guidelines, ROP remains a leading cause of childhood blindness worldwide. Current screening guidelines are primarily based on two risk factors: birth weight and gestational age; however, many investigators have suggested other risk factors, including maternal factors, prenatal and perinatal factors, demographics, medical interventions, comorbidities of prematurity, nutrition, and genetic factors. We review the existing literature addressing various possible ROP risk factors. Although there have been contradictory reports, and the risk may vary between different populations, understanding ROP risk factors is essential to develop predictive models, to gain insights into pathophysiology of retinal vascular diseases and diseases of prematurity, and to determine future directions in management of and research in ROP.

Validation of the Colorado Retinopathy of Prematurity Screening Model

Importance

The Colorado Retinopathy of Prematurity (CO-ROP) model uses birth weight, gestational age, and weight gain at the first month of life (WG-28) to predict risk of severe retinopathy of prematurity (ROP). In previous validation studies, the model performed very well, predicting virtually all cases of severe ROP and potentially reducing the number of infants who need ROP examinations, warranting validation in a larger, more diverse population.

Objective

To validate the performance of the CO-ROP model in a large multicenter cohort.

Design, Setting, Participants

This study is a secondary analysis of data from the Postnatal Growth and Retinopathy of Prematurity (G-ROP) Study, a retrospective multicenter cohort study conducted in 29 hospitals in the United States and Canada between January 2006 and June 2012 of 6351 premature infants who received ROP examinations.

Main Outcomes and Measures

Sensitivity and specificity for severe (early treatment of ROP [ETROP] type 1 or 2) ROP, and reduction in infants receiving examinations. The CO-ROP model was applied to the infants in the G-ROP data set with all 3 data points (infants would have received examinations if they met all 3 criteria: birth weight, <1501 g; gestational age, <30 weeks; and WG-28, <650 g). Infants missing WG-28 information were included in a secondary analysis in which WG-28 was considered fewer than 650 g.

Results

Of 7438 infants in the G-ROP study, 3575 (48.1%) were girls, and maternal race/ethnicity was 2310 (31.1%) African American, 3615 (48.6%) white, 233 (3.1%) Asian, 40 (0.52%) American Indian/Alaskan Native, and 93 (1.3%) Pacific Islander. In the study cohort, 747 infants (11.8%) had type 1 or 2 ROP, 2068 (32.6%) had lower-grade ROP, and 3536 (55.6%) had no ROP. The CO-ROP model had a sensitivity of 96.9% (95% CI, 95.4%-97.9%) and a specificity of 40.9% (95% CI, 39.3%-42.5%). It missed 23 (3.1%) infants who developed severe ROP. The CO-ROP model would have reduced the number of infants who received examinations by 26.1% (95% CI, 25.0%-27.2%).

Conclusions and Relevance

The CO-ROP model demonstrated high but not 100% sensitivity for severe ROP and missed infants who might require treatment in this large validation cohort. The model requires all 3 criteria to be met to signal a need for examinations, but some infants with a birth weight or gestational age above the thresholds developed severe ROP. Most of these infants who were not detected by the CO-ROP model had obvious deviation in expected weight trajectories or nonphysiologic weight gain. These findings suggest that the CO-ROP model needs to be revised before considering implementation into clinical practice.

Factors associated with retinopathy of prematurity ophthalmology workload

OBJECTIVE

This article reports on retinopathy of prematurity (ROP) workload in the NICU related to severity of disease, gestational age at discharge, and practice variation.

STUDY DESIGN

Data analysis on 1771 patients ≤ 30 weeks of gestation at birth from a de-identified data set of 13 NICUs.

RESULTS

There was a positive relationship between the severity of ROP and (1) the number of exams per patient, (2) the severity of ROP, and (3) postmenstrual age at discharge. The progression between the stages of ROP added to exam workload and postmenstrual age at NICU discharge. The addition of plus disease did not increase the exam burden. There was significant practice variation in the number of exams performed independent of ROP severity.

CONCLUSION

The progression of the severity of ROP independent of plus disease, and practice variations both contribute to ROP workload. Addressing these factors could decrease ROP workload without compromising American Academy of Pediatrics (AAP) guidelines.

Hot Topics in Retinopathy of Prematurity

Retinopathy of prematurity (ROP) is a condition seen in premature infants that is characterized by abnormal retinal blood vessel growth incited by relative hyperoxia and followed by hypoxia. It can have severe consequences ranging from high myopia to blindness. This article reviews recent "hot" topics related to ROP, specifically the changing incidence of ROP worldwide, the advent of predictive algorithms for screening for ROP, the emerging data behind efficacy of anti-vascular endothelial growth factor treatments for ROP, and advanced retinal imaging in children who were born premature. [Pediatr Ann. 2017;46(11):e415-e422.].

Validation of the Children's Hospital of Philadelphia Retinopathy of Prematurity (CHOP ROP) Model

Importance

The Children's Hospital of Philadelphia Retinopathy of Prematurity (CHOP ROP) model uses birth weight (BW), gestational age at birth (GA), and weight gain rate to predict the risk of severe retinopathy of prematurity (ROP). In a model development study, it predicted all infants requiring treatment, while greatly reducing the number of examinations compared with current screening guidelines.

Objective

To validate the CHOP ROP model in a multicenter cohort that is large enough to obtain a precise estimate of the model's sensitivity for treatment-requiring ROP.

Design, Setting, and Participants

This investigation was a secondary analysis of data from the Postnatal Growth and Retinopathy of Prematurity (G-ROP) Study. The setting was 30 hospitals in the United States and Canada between January 1, 2006, and June 30, 2012. The dates of analysis were September 28 to October 5, 2015. Participants were premature infants at risk for ROP with a known ROP outcome.

Main Outcomes and Measures

Sensitivity for Early Treatment of Retinopathy of Prematurity type 1 ROP and potential reduction in the number of infants requiring examinations. In the primary analysis, the CHOP ROP model was applied weekly to predict the risk of ROP. If the risk was above a cut-point level (high risk), examinations were indicated, while low-risk infants received no examinations. In a secondary analysis, low-risk infants received fewer examinations rather than no examinations.

Results

Participants included 7483 premature infants at risk for ROP with a known ROP outcome. Their median BW was 1070 g (range, 310-3000 g), and their median GA was 28 weeks (range, 22-35 weeks). Among them, 3575 (47.8%) were female, and their race/ethnicity was 3615 white (48.3%), 2310 black (30.9%), 233 Asian (3.1%), 93 Pacific Islander (1.2%), and 40 American Indian/Alaskan native (0.5%). The original CHOP ROP model correctly predicted 452 of 459 infants who developed type 1 ROP (sensitivity, 98.5%; 95% CI, 96.9%-99.3%), reducing the number of infants requiring examinations by 34.3% if only high-risk infants received examinations. Lowering the cut point to capture all type 1 ROP cases (sensitivity, 100%; 95% CI, 99.2%-100%) resulted in only 6.8% of infants not requiring examinations. However, if low-risk infants were examined at 37 weeks' postmenstrual age and followed up only if ROP was present at that examination, all type 1 ROP cases would be captured, and the number of examinations performed among infants with GA exceeding 27 weeks would be reduced by 28.4%.

Conclusion and Relevance

The CHOP ROP model demonstrated high but not 100% sensitivity and may be better used to reduce examination frequency. The model might be used reliably to guide a modified ROP screening schedule and decrease the number of examinations performed.