Efficacy of the WINROP algorithm for retinopathy of prematurity screening in Southern China

Changes of the peripapillary vascular parameters in premature infants without retinopathy of prematurity using U-net segmentation

AIM

To quantitatively assess the changes in mean vascular tortuosity (mVT) and mean vascular width (mVW) around the optic disc and their correlation with gestational age (GA) and birth weight (BW) in premature infants without retinopathy of prematurity (ROP).

METHODS

A single-center retrospective study included a total of 133 (133 eyes) premature infants [mean corrected gestational age (CGA) 43.6wk] without ROP as the premature group and 130 (130 eyes) CGA-matched full-term infants as the control group. The peripapillary mVT and mVW were quantitatively measured using computer-assisted techniques.

RESULTS

Premature infants had significantly higher mVT (P=0.0032) and lower mVW (P=0.0086) by 2.68 (104 cm-3) and 1.85 µm, respectively. Subgroup analysis with GA showed significant differences (P=0.0244) in mVT between the early preterm and middle to late preterm groups, but the differences between mVW were not significant (P=0.6652). The results of the multiple linear regression model showed a significant negative correlation between GA and BW with mVT after adjusting sex and CGA (P=0.0211 and P=0.0006, respectively). For each day increase in GA at birth, mVT decreased by 0.1281 (104 cm-3) and for each 1 g increase in BW, mVT decreased by 0.006 (104 cm-3). However, GA (P=0.9402) and BW (P=0.7275) were not significantly correlated with mVW.

CONCLUSION

Preterm birth significantly affects the peripapillary vascular parameters that indicate higher mVT and narrower mVW in premature infants without ROP. Alterations in these parameters may provide new insights into the pathogenesis of ocular vascular disease.

Validation of WINROP algorithm as screening tool of retinopathy of prematurity among Egyptian preterm neonates

BACKGROUND

Retinopathy of prematurity (ROP) is a leading cause of preventable childhood blindness worldwide. Proper screening for ROP can prevent loss of vision. WINROP (weight, insulin-like growth factor 1, neonatal, retinopathy of prematurity) is an online surveillance system based on gestational age, birth weight and weekly weight gain that can predict infants at risk of sight-threatening retinopathy of prematurity.

AIMS

To evaluate the diagnostic accuracy of WINROP algorithm in detecting sight-threatening ROP in Egyptian preterm neonates.

METHODS

Birth weight (BW), gestational age (GA) and weekly weight measurement of 365 preterm infants were prospectively entered into WINROP algorithm. Based on these inputs, the algorithm would output and a screening was performed as is standard. Sensitivity, specificity, and predictive values were calculated by comparing WINROP outcomes with ROP screening outcomes.

RESULTS

Of the infants included in the study the mean GA was ±31.24 and mean BW was ±1508.78. A high risk WINROP alarm was triggered in 62 infants of whom 16 infants develop type 1 or type 2 ROP. These infants had associated comorbidities including sepsis, Intraventricular hemorrhage (IVH), Necrotizing enterocolitis (NEC), history of transfusion of packed red blood cells (RBCS) and history of platelet transfusion. A low risk WINROP alarm was triggered in 303 infants of whom 15 infants developed type 1 or type 2ROP. WINROP showed a sensitivity of 51.6%, a specificity of 86.2%, a positive predictive value (PPV) of 52.8% and a negative predictive value (NPV) of 95% for detection of type 1 or type 2 ROP.

CONCLUSION

WINROP has low sensitivity and high specificity for detection of ROP. It may help in ROP prediction but can't be used alone. Modification of WINROP algorithm taking into account other risk factors may improve sensitivity and reduce number for ROP examination.

Nomogram to predict severe retinopathy of prematurity in Southeast China

AIM

To define the predictive factors of severe retinopathy of prematurity (ROP) and develop a nomogram for predicting severe ROP in southeast China.

METHODS

Totally 554 infants diagnosed with ROP hospitalized in the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University and hospitalized in Taizhou Women and Children's Hospital were included. Clinical data and 43 candidate predictive factors of ROP infants were collected retrospectively. Logistic regression model was used to identify predictive factors of severe ROP and to propose a nomogram for individual risk prediction, which was compared with WINROP model and Digirop-Birth model.

RESULTS

Infants from the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University (n=478) were randomly allocated into training (n=402) and internal validation group (n=76). Infants from Taizhou Women and Children's Hospital were set as external validation group (n=76). Severe ROP were found in 52 of 402 infants, 12 of 76 infants, and 7 of 76 infants in training group, internal validation group, and external validation group, respectively. Birth weight [odds ratio (OR), 0.997; 95% confidence interval (CI), 0.996-0.999; P<0.001], multiple births (OR, 1.885; 95%CI, 1.013-3.506; P=0.045), and non-invasive ventilation (OR, 0.288; 95%CI, 0.146-0.570; P<0.001) were identified as predictive factors for the prediction of severe ROP, by univariate analysis and multivariate analysis. For predicting severe ROP based on the internal validation group, the areas under receiver operating characteristic curve (AUC) was 78.1 (95%CI, 64.2-92.0) for the nomogram, 32.9 (95%CI, 15.3-50.5) for WINROP model, 70.2 (95%CI, 55.8-84.6) for Digirop-Birth model. In external validation group, AUC of the nomogram was also higher than that of WINROP model and Digirop-Birth model (80.2 versus 51.1 and 63.4). The decision curve analysis of the nomogram demonstrated better clinical efficacy than that of WINROP model and Digirop-Birth model. The calibration curves demonstrated a good consistency between the actual severe ROP incidence and the predicted probability.

CONCLUSION

Birth weight, multiple births, and non-invasive ventilation are independent predictors of severe ROP. The nomogram has a good ability to predict severe ROP and performed well on internal validation and external validation in southeast China.

Retinopathy of Prematurity-Targeting Hypoxic and Redox Signaling Pathways

Retinopathy of prematurity (ROP) is a proliferative vascular ailment affecting the retina. It is the main risk factor for visual impairment and blindness in infants and young children worldwide. If left undiagnosed and untreated, it can progress to retinal detachment and severe visual impairment. Geographical variations in ROP epidemiology have emerged over recent decades, attributable to differing levels of care provided to preterm infants across countries and regions. Our understanding of the causes of ROP, screening, diagnosis, treatment, and associated risk factors continues to advance. This review article aims to present the pathophysiological mechanisms of ROP, including its treatment. Specifically, it delves into the latest cutting-edge treatment approaches targeting hypoxia and redox signaling pathways for this condition.

Retrospective validation of the postnatal Growth and Retinopathy of Prematurity (G-ROP) criteria in a developing country

Background

The characteristics of premature infants vary from country to country rendering it challenging to apply retinopathy of prematurity (ROP) screening algorithm globally. The screening criteria for postnatal growth and ROP (G-ROP) for preterm infants are known to be beneficial, but it is not clear whether these criteria can be used universally.

Aim

The aim of this study is to validate the accuracy of the G-ROP criteria in screening preterm infants in Saudi Arabia.

Subjects and Methods

This single-center retrospective study included 300 premature infants (mean gestational age [GA], 28.72 ± 2.2 weeks; range, 21-36 weeks) at a referral center who were screened for ROP between 2015 and 2021. The inclusion criteria were the availability of data on ROP outcome and body weight up until day 40 after birth. The G-ROP 1 and G-ROP 2 models were examined for their ability and accuracy in identifying infants with any stage ROP and treatable ROP.

Results

The G-ROP 1 and G-ROP 2 models identified 233 and 255 infants for screening, respectively. The sensitivity of G-ROP 1 and G-ROP 2 for detecting treated ROP was 96.7% and 100%, respectively, and the specificity for detecting treatable ROP was 24.4% and 16.7%, respectively. Incorporation of the G-ROP 2 model, which did not miss any infant with type 1 ROP, would have reduced the number of screened infants by 15%.

Conclusion

G-ROP 2 was more sensitive than G-ROP 1 for identifying infants who required treatment and could potentially reduce the burden of ROP screening.

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.

Haemoglobin Levels in Early Life among Infants with and without Retinopathy of Prematurity

Retinopathy of prematurity (ROP) is a proliferative retinal vascular disorder attributed to an ischaemic stimulus in preterm infants. Haemoglobin, the main component for oxygen transportation, may be implicated in ROP development. This retrospective study compared the mean weekly haemoglobin levels between infants with and without ROP over the first six weeks of life. Premature infants of less than 32 weeks gestational age and less than 1.5 kg birth weight were grouped into age and birth weight-matched ROP cases and controls. Weekly mean haemoglobin levels were documented. An independent t-test was used to analyze the difference in mean haemoglobin levels between infants with ROP and infants without ROP. Adjustment for confounders was performed using one-way analysis of covariance. There was a statistically significant difference in adjusted mean haemoglobin levels between the ROP and non-ROP group during the first week of life (p = 0.038). No significant intergroup differences were observed at the other weeks. Haemoglobin monitoring during the first week of postnatal life may be useful to guide ROP screening in premature infants.