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

Koçak, Nurullah; Niyaz, Leyla; Arıtürk, Nurşen

doi:10.1016/j.jaapos.2016.08.008

Cited by 22 publications

(25 citation statements)

References 20 publications

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“…This is comparable to results from other developing countries, majority of which show sensitivity ranging from 80% to 90% [ Table 4 ]. [ 8 9 11 12 13 14 15 16 17 18 19 ] In contrast, data from Sweden and the USA show a sensitivity of 100%. [ 8 9 ] This difference may be due to diverse populations and NICU protocols.…”

Section: Discussionmentioning

confidence: 99%

WINROP algorithm for prediction of sight threatening retinopathy of prematurity: Initial experience in Indian preterm infants

Sanghi

Narang

Narula

et al. 2018

Indian J Ophthalmol

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Purpose:To determine the efficacy of the online monitoring tool, WINROP (https://winrop.com/) in detecting sight-threatening type 1 retinopathy of prematurity (ROP) in Indian preterm infants.Methods:Birth weight, gestational age, and weekly weight measurements of seventy preterm infants (<32 weeks gestation) born between June 2014 and August 2016 were entered into WINROP algorithm. Based on weekly weight gain, WINROP algorithm signaled an alarm to indicate that the infant is at risk for sight-threatening Type 1 ROP. ROP screening was done according to standard guidelines. The negative and positive predictive values were calculated using the sensitivity, specificity, and prevalence of ROP type 1 for the study group. 95% confidence interval (CI) was calculated.Results:Of the seventy infants enrolled in the study, 31 (44.28%) developed Type 1 ROP. WINROP alarm was signaled in 74.28% (52/70) of all infants and 90.32% (28/31) of infants treated for Type 1 ROP. The specificity was 38.46% (15/39). The positive predictive value was 53.84% (95% CI: 39.59–67.53) and negative predictive value was 83.3% (95% CI: 57.73–95.59).Conclusion:This is the first study from India using a weight gain-based algorithm for prediction of ROP. Overall sensitivity of WINROP algorithm in detecting Type 1 ROP was 90.32%. The overall specificity was 38.46%. Population-specific tweaking of algorithm may improve the result and practical utility for ophthalmologists and neonatologists.

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Section: Discussionmentioning

confidence: 99%

WINROP algorithm for prediction of sight threatening retinopathy of prematurity: Initial experience in Indian preterm infants

Sanghi

Narang

Narula

et al. 2018

Indian J Ophthalmol

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“…Table 4 summarizes the results of 12 countries of both high-and moderate-/low-income status who have participated in the WINROP study, including our study. [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16] Overall, WINROP has been reported to have good efficacy as a screening tool. However, the sensitivity of WINROP varies among countries.…”

Section: Discussionmentioning

confidence: 99%

“…The study outcome has been described in numerous countries. [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16] In Asia, it has been reported in China, Korea, Taiwan, India and Japan. 6,7,11,15,16 Based on a PubMed search, no similar reports are available from the South East Asia region, especially in a developing country.…”

Section: Introductionmentioning

confidence: 99%

<p>Efficacy of WINROP as a Screening Tool for Retinopathy of Prematurity in the East Coast of Malaysia</p>

Lim¹,

Oo²,

Tai³

et al. 2020

OPTH

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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.

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“…9 When the accumulated sum exceeds a critical limit, an alarm is signaled to indicate that the infant is at risk for developing severe ROP 9 .The exact threshold for alarms is not revealed to the users. 16 Brazil 366 90.5% 55% Zepeda, 17 Mexico 352 84.7% 26.6% Sun et al, 18 China 590 89.3% 89% Choi et al, 19 South Korea 314 90% 52.6% Ko et al, 20 Taiwan 148 64.7% 55% Kocak et al, 21 Turkey 223 84.3 % 52.8% Current study India 45 90% 48.6%…”

Section: Discussionmentioning

confidence: 99%

Validation of weight, insulin like growth factor 1, neonatal retinopathy of prematurity for detecting retinopathy of prematurity among Indian preterm neonates

Marthandappa

Vandanapriya

Surabhi

et al. 2019

Int J Contemp Pediatr

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Background: Among the premature infants, WINROP (weight, insulin like growth factor 1, neonatal retinopathy of prematurity), a web- based retinopathy of prematurity (ROP) risk algorithm, uses postnatal weight gain in predicting the risk of severe ROP. This retrospective study assess the sensitivity and specificity of WINROP algorithm to predict proliferative ROP (type 1, type 2).Methods: This was a tertiary hospital based retrospective study conducted in level 3 - NICU from February -November 2018. The data was entered in WINROP website. 45 neonates enrolled in the study, were classified as either alarm given (increased risk of severe ROP) or not given (no risk of severe ROP/ no ROP). Timing of alarm was also noted.Result: 10 neonates (22%) had severe ROP requiring treatment. The mean gestational age was 30 weeks and mean birth weight was 1275 grams. In this study, sensitivity to WINROP online system was found to be 90%, specificity of 48.6%, positive predictive value of 33.3% and negative predictive value of 94.4%. The median time from alarm to treatment was 6 weeks (3-8 weeks).Conclusion: WINROP algorithm has a good sensitivity in detection of treatable ROP.

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

Cited by 22 publications

References 20 publications

WINROP algorithm for prediction of sight threatening retinopathy of prematurity: Initial experience in Indian preterm infants

WINROP algorithm for prediction of sight threatening retinopathy of prematurity: Initial experience in Indian preterm infants

<p>Efficacy of WINROP as a Screening Tool for Retinopathy of Prematurity in the East Coast of Malaysia</p>

Validation of weight, insulin like growth factor 1, neonatal retinopathy of prematurity for detecting retinopathy of prematurity among Indian preterm neonates

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