WINROP can modify ROP screening praxis: a validation of WINROP in populations in Sörmland and Västmanland

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.

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.

Use of an online screening algorithm - Weight, Insulin-derived growth factor 1, Neonatal Retinopathy of Prematurity (WINROP) for predicting retinopathy of prematurity in Indian preterm babies

Purpose:

Inopathy of prematurity (WINROP) Weight, insulin-derived growth factor 1, neonatal ROP algorithm is an online tool that has been validated as a predictor of retinopathy of prematurity (ROP) in various countries. The current study was designed to evaluate the predictive ability of WINROP algorithm (http://winrop.com) using postnatal weight gain in detecting Type 1 ROP in Indian babies.

Methods:

Prospective single centre observational study of 153 consecutive preterm babies who were eligible for screening for ROP as per the standard guidelines. Sixteen babies were excluded from the study because of various reasons. Thirty-five babies had gestational age ≥32 weeks and were ineligible for WINROP algorithm. Online WINROP algorithm was used for 102 babies with gestation at birth less than 32 weeks. The alarms triggered by WINROP were documented.

Results:

Laser treatment was done in 30 babies who developed Type 1 ROP. Of these, WINROP alarm was signaled in 24 babies and 6 babies developed ROP without any WINROP alarm. These babies had associated comorbidities like respiratory distress syndrome, patent ductus arteriosus, bacterial sepsis, and ventilatory support. WINROP alarm was significantly associated with Type 1 ROP (P < 0.001). The sensitivity of WINROP was 80% and specificity was 80.6% with a positive predictive value of 63.2% and negative predictive value of 90.6% in detecting Type 1 ROP. In the present study, no baby who was ineligible for WINROP developed Type 1 ROP.

Conclusion:

WINROP provides a novel online monitoring screening tool for identifying babies at risk of developing Type 1 ROP. In our cohort, none of the babies whose period of gestation was more than or equal to 32 weeks developed sight threatening Type 1 ROP. WINROP algorithm may also be useful in Indian population.

Efficacy of WINROP as a Screening Tool for Retinopathy of Prematurity in the East Coast of Malaysia

Purpose

To evaluate the efficacy of the “weight, insulin-like growth factor 1, neonatal retinopathy of prematurity” (WINROP) algorithm in predicting retinopathy of prematurity (ROP) requiring treatment in Malaysia.

Participants

This was a retrospective study involving premature infants with gestational age less than 32 weeks treated from September 2016 to March 2019 in Hospital Universiti Sains Malaysia. Clinical diagnosis was made based on Early Treatment Retinopathy of Prematurity study. Participants’ weekly weight gain since birth was entered in the website (http://winrop.com), along with date of birth, gestational age and final clinical examination outcome. WINROP software signals an alarm if an infant is at high risk of developing ROP requiring treatment during weight data entry. By using the alarm status, the sensitivity and specificity of this algorithm for predicting ROP requiring treatment were obtained.

Results

Ninety-two infants were included in this study. An alarm was detected in 67 infants (72.8%). There were a total of 53 infants (54.6%) with no ROP, 15 (16.3%) of whom developed stage 1 ROP, 10 (10.8%) who developed stage 2 ROP and 14 infants (15.2%) who developed stage 3 ROP. In our study, WINROP sensitivity was 95.2% and specificity was 33.8%.

Conclusion

WINROP is recommended as an initial screening tool for premature infants at risk of developing treatment-requiring ROP in Malaysia. It may help to alert clinicians managing severely ill infants when clinical examinations are less possible.

Prediction of ROP Treatment and Evaluation of Screening Criteria in VLBW Infants-a Population Based Analysis

BACKGROUND

The incidence of retinopathy of prematurity (ROP) and ROP screening criteria differ between countries. We assessed whether ROP screening could be reduced based on the local ROP incidence.

METHODS

Observational cohort study of infants born in Switzerland between 2006 and 2015 <32 0/7 weeks. Chronological and postmenstrual ages at ROP treatment were analyzed. A model to identify ROP treatment on patients born between 2006 and 2012 (training set) was developed and tested on patients born between 2013 and 2015 (validation set).

RESULTS

Of 7817 live-born infants, 1098 died within the first 5 weeks of life. The remaining 6719 infants were included into analysis. All patients requiring ROP treatment would have been identified if screening had been performed before reaching 60 days of life or 37 3/7 weeks postmenstrual age, whichever came first. The training and validation sets included 4522 and 2197 preterm infants encompassing 56 and 20 patients receiving ROP treatment, respectively. All patients would have required screening to reach 100% sensitivity. To reach a sensitivity of 95.0% and a specificity of 87.6%, we predicted a reduction in 13.2% of patients requiring screening (c-statistic = 0.916).

CONCLUSIONS

A substantial reduction of infants requiring screening seems possible, but necessitates prospective testing of new screening criteria.

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 WINROP for detecting retinopathy of prematurity in a North American cohort of preterm infants

BACKGROUND

WINROP (weight, insulin-like growth factor 1, neonatal, retinopathy of prematurity) is a web-based retinopathy of prematurity (ROP) risk algorithm that uses postnatal weight gain as a surrogate of insulin-like growth factor-1 (IGF-1) to predict the risk of severe ROP in premature infants. The purpose of this study was to validate the web-based algorithm WINROP in detecting severe (type 1 or type 2) ROP in a North American cohort of infants.

METHODS

The records of consecutive infants who underwent ROP examinations between 2008 and 2011 were reviewed retrospectively. Infants were classified into categories of "alarm" (at risk for developing severe ROP) and "no alarm" (minimal risk for severe ROP).

RESULTS

A total of 483 were included. Alarm occurred in 241 neonates (50%), with the median time from birth to alarm of 2 weeks. WINROP had a sensitivity of 81.8% (95% CI, 67.3%-91.8%) and specificity of 53.3% (95% CI, 48.5%-58.0%) for identifying infants with severe ROP. Eight of the 44 infants with severe ROP were not detected (5 with type 1 and 3 with type 2). Of these 8 infants, 7 (88%) had birth weight in excess of the 70^th pecentile. With additional weight data entry, sensitivity of WINROP rose to 88.6%.

CONCLUSIONS

Very preterm infants (gestational age of ≤27 weeks) with relatively high birth weight for gestational age may not be detected by WINROP as high risk for developing severe ROP.

Assessment of WINROP algorithm as screening tool for preterm infants in Manitoba to detect retinopathy of prematurity

Objective

Developing less invasive methods for early detection of retinopathy of prematurity (ROP) is vital to minimizing blindness in premature infants. Lofqvist and colleagues developed a computer-based ROP risk algorithm (WINROP) (https://winrop.com), which detects downtrends in postnatal weight gain that correlate with the development of sight-threatening ROP. The aim of this study is to investigate the sensitivity and specificity of the WINROP algorithm to detect vision-threatening ROP.

Methods

This is a retrospective chart review study between January 2008 and December 2013. This study was conducted in the neonatal intensive care unit in Children's Hospital at Health Sciences Centre, Winnipeg, Manitoba, Canada. The study included preterm infants, less than 32 weeks' gestation, who were admitted to the hospital during the study period. The included 215 infants were eligible for ROP screening and had sufficient data to be entered into the WINROP algorithm. Infants were screened by a paediatric ophthalmologist for retinopathy of prematurity. The body weight of infants was measured weekly and entered into the WINROP algorithm; the sensitivity and the specificity of the WINROP algorithm were assessed.

Results

The mean gestational age was 28.6 ± 1.8 weeks. The mean body weight was 1244 ± 294 g. The sensitivity of the WINROP algorithm to detect vision-threatening retinopathy of prematurity in our cohort was 90% (P=0.021) with a specificity of 60% (P=0.002).

Conclusion

The WINROP algorithm lacks sufficient sensitivity to be used clinically in our population. The algorithm needs to be reassessed in contemporary populations.

Screening and Treatment in Retinopathy of Prematurity

BACKGROUND

More than 11 000 children are examined for possible retinopathy of prematurity in Germany each year, and 2-5% of them are treated for it. Even though screening and treatment programs are in place, the affected children can still suffer visual impairment.

METHODS

In this article, we summarize the pathogenesis, screening, and treatment of retinopathy of prematurity on the basis of a selective review of pertinent literature, retrieved by a PubMed search. The article centers on publications from 2011 to 2015 on the new option of treatment with VEGF inhibitors and discusses it in comparison to laser therapy.

RESULTS

All premature neonates with a low gestational age at birth, low birth weight, or prolonged exposure to supplemental oxygen must undergo screening by an ophthalmologist. Laser therapy is effective for stages 1-3 and for aggressive posterior retinopathy of prematurity. Its disadvantages are the induction of scarring and the development of severe myopia in 17-40% of the children so treated. Anti-VEGF treatment (VEGF = vascular endothelial growth factor) does not induce any visible scarring and seems to cause less myopia, but long-term data on safety, dosing, and the choice of anti-VEGF drug are still lacking.

CONCLUSION

The available evidence for anti-VEGF treatment is on a much lower level than the evidence for laser therapy. Anti-VEGF may be a way to avoid the disadvantages of laser therapy (scarring and severe myopia). Unlike laser therapy, however, the intravitreal injection of VEGF inhibitors may suppress systemic VEGF levels and potentially harm the developing brain, lungs, or other organs. The currently open questions about anti-VEGF treatment concern its dosing, choice of drug, and long-term safety.

Prediction of severe retinopathy of prematurity using the screening algorithm WINROP in preterm infants

PURPOSE

To assess the sensitivity and specificity of weight gain, insulin-like growth factor 1 (IGF-1), and neonatal retinopathy of prematurity (WINROP) algorithm to predict proliferative retinopathy of prematurity (ROP), in a Turkish population of preterm infants.

METHODS

The medical records of infants screened and monitored for ROP from 2007 to 2014 were analyzed retrospectively. Birth weights of infants born before 32 weeks' gestation were recorded on the WINROP online database system weekly until postmenstrual week 36. The sensitivity, specificity, and positive and negative predictive values of the WINROP algorithm were analyzed.

RESULTS

A total of 223 infants were included. WINROP yielded a low-risk result in 106 infants (48%) and a high-risk result (red alarm) in the remaining 117 infants (53%). The sensitivity of the WINROP online system was found to be 84.3% (27/32), whereas its specificity was found to be 52.8% (101/191). The time between the first alarm and treatment was 8.59 ± 3.92 (2-15) weeks. Using this algorithm, 106 infants would not have needed eye examinations, possibly resulting in a 40% decrease in the total number of examinations.

CONCLUSIONS

The WINROP online system is a valuable and easy-to-use monitoring system that could decrease the number of infant ROP examinations.

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

PURPOSE

The Colorado retinopathy of prematurity (ROP) prediction model (CO-ROP), developed using a cohort of infants from Colorado, calls for ROP examination of infants meeting all of the following criteria: gestational age of ≤30 weeks, birth weight of ≤1500 g, and a net weight gain of ≤650 g between birth and 4 weeks of age. The purpose of this study was to perform an external validation to assess the sensitivity and specificity of the CO-ROP model in a larger cohort of babies screened for ROP from four academic institutions in the United States.

METHODS

The medical records of neonates screened for ROP according current national guidelines was conducted at 4 US academic centers were retrospectively reviewed. Sensitivity, specificity, and respective 95% confidence intervals in detecting ROP using CO-ROP were calculated for type 1, type 2, and any grade of ROP.

RESULTS

A total of 858 cases were included. The CO-ROP algorithm had a sensitivity of 98.1% (95% CI, 93.3%-99.8%) for type 1 ROP, 95.6% (95% CI 78.0-99.9%) for type 2 ROP, and 95.0% (95% CI, 93.1-97.4%) for all grades of ROP. The CO-ROP model would have reduced the total number of infants screened by 23.9% compared to current 2013 screening guidelines.

CONCLUSIONS

CO-ROP demonstrated high sensitivity in predicting ROP and would have greatly reduced the number of infants needing examination.

Retinopathy of prematurity: Past, present and future

Retinopathy of prematurity (ROP) is a vasoproliferative disorder of the retina occurring principally in new born preterm infants. It is an avoidable cause of childhood blindness. With the increase in the survival of preterm babies, ROP has become the leading cause of preventable childhood blindness throughout the world. A simple screening test done within a few weeks after birth by an ophthalmologist can avoid this preventable blindness. Although screening guidelines and protocols are strictly followed in the developed nations, it lacks in developing economies like India and China, which have the highest number of preterm deliveries in the world. The burden of this blindness in these countries is set to increase tremendously in the future, if corrective steps are not taken immediately. ROP first emerged in 1940s and 1950s, when it was called retrolental fibroplasia. Several epidemics of this disease were and are still occurring in different regions of the world and since then a lot of research has been done on this disease. However, till date very few comprehensive review articles covering all the aspects of ROP are published. This review highlights the past, present and future strategies in managing this disease. It would help the pediatricians to update their current knowledge on ROP.

The Colorado-retinopathy of prematurity model (CO-ROP): postnatal weight gain screening algorithm

PURPOSE

To describe a novel retinopathy of prematurity (ROP) screening model incorporating birth weight, gestational age, and postnatal weight gain that maintains sensitivity but improves specificity in detecting all grades of ROP compared to current 2013 screening guidelines.

METHODS

The medical records of 499 neonates from a single tertiary referral center who met the 2013 screening guidelines for ROP were retrospectively reviewed. Weekly weights were analyzed using standard logistic regression to determine the age at which the weekly net weight gain best predicted the development of ROP, which was designated as the postnatal weight gain criterion. The 2013 birth weight and gestational age criteria were included in an "and" fashion to form the CO-ROP model. Sensitivities and specificities in detecting high grade (type 1 and 2) and all grades of ROP were calculated.

RESULTS

The CO-ROP model screens infants with a gestational age at birth of ≤30 weeks and birth weight of ≤1500 g and net weight gain of ≤650 g between birth and 1 month of age. In our cohort, CO-ROP had a sensitivity of 100% (95% CI, 92.1%-100.0%) for high-grade (type 1 and 2) ROP and 96.4% (95% CI, 92.3%-98.7%) for all grades of ROP. It would reduce the number of infants screened by 23.7% compared to 2013 guidelines. Calibrating the model to detect only high-grade ROP would result in a 45.9% reduction in the total number of infants screened.

CONCLUSIONS

CO-ROP is a simple model that maintains a statistically similar sensitivity in detecting all grades of ROP while significantly reducing the total number of required ROP screenings compared to 2013 guidelines. The study had a small sample size but shows promise for future research and clinical efforts.

Clinical Models and Algorithms for the Prediction of Retinopathy of Prematurity: A Report by the American Academy of Ophthalmology

OBJECTIVE

To assess the accuracy with which available retinopathy of prematurity (ROP) predictive models detect clinically significant ROP and to what extent and at what risk these models allow for the reduction of screening examinations for ROP.

METHODS

A literature search of the PubMed and Cochrane Library databases was conducted last on May 1, 2015, and yielded 305 citations. After screening the abstracts of all 305 citations and reviewing the full text of 30 potentially eligible articles, the panel members determined that 22 met the inclusion criteria. One article included 2 studies, for a total of 23 studies reviewed. The panel extracted information about study design, study population, the screening algorithm tested, interventions, outcomes, and study quality. The methodologist divided the studies into 2 categories-model development and model validation-and assigned a level of evidence rating to each study. One study was rated level I evidence, 3 studies were rated level II evidence, and 19 studies were rated level III evidence.

RESULTS

In some cohorts, some models would have allowed reductions in the number of infants screened for ROP without failing to identify infants requiring treatment. However, the small sample size and limited generalizability of the ROP predictive models included in this review preclude their widespread use to make all-or-none decisions about whether to screen individual infants for ROP. As an alternative, some studies proposed approaches to apply the models to reduce the number of examinations performed in low-risk infants.

CONCLUSIONS

Additional research is needed to optimize ROP predictive model development, validation, and application before such models can be used widely to reduce the burdensome number of ROP screening examinations.

The Specificity of the WINROP Algorithm Can Be Significantly Increased by Reassessment of the WINROP Alarm

BACKGROUND

Retinopathy of prematurity (ROP) is a sight-threatening disease affecting extremely preterm infants. The introduction of new ROP screening surveillance systems, with higher sensitivity and specificity than established ROP screening guidelines, has the potential to reduce the number of stressful eye examinations in these infants.

OBJECTIVES

To improve the specificity of the WINROP (Weight, Insulin-like growth factor-I, Neonatal, ROP) surveillance system, identifying extremely preterm infants requiring treatment for ROP.

METHODS

Two cohorts that had previously been subjected to WINROP analyses were included and reevaluated in this study. The weight at WINROP alarm for extremely preterm infants, born at gestational age <27 weeks, was reevaluated and by establishing 'safe' WINROP alarm weight limits, an intersample reassessment of WINROP alarm was performed. The two cohorts were as follows: (1) the Extremely Preterm Infants in Sweden Study (EXPRESS) cohort, infants born in Sweden during 2004-2007 (n = 407), and (2) extremely preterm infants in a North American cohort, born during 2006-2009 (n = 566).

RESULTS

In the EXPRESS cohort, 12.5% (40/319) of the infants who previously received a WINROP alarm were now reassessed as having no alarm; the specificity of WINROP in EXPRESS increased from 23.9% (86/360) to 35.0% (126/360). In the North American cohort, 15.4% (81/526) were reassessed as having no alarm; the specificity increased from 8.5% (38/447) to 26.6% (119/447). The sensitivity persisted as 97.5% in EXPRESS (45/47) and 98.3% (117/119) in the North American cohort.

CONCLUSIONS

The specificity of the WINROP surveillance system for extremely preterm infants can be significantly improved by reassessment using the weight at WINROP alarm.