{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T15:21:38Z","timestamp":1787844098911,"version":"build-2784847793"},"reference-count":25,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"5","content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,5]]},"abstract":"<jats:sec>\n                    <jats:title>Purpose:<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>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 \u226532 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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>\n                      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 (\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt; 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.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.4103\/ijo.ijo_1521_20","type":"journal-article","created":{"date-parts":[[2021,5,2]],"date-time":"2021-05-02T11:32:28Z","timestamp":1619955148000},"page":"1214-1218","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":8,"title":["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"],"prefix":"10.4103","volume":"69","author":[{"given":"Smith Snehal","family":"Sute","sequence":"first","affiliation":[{"name":"Departments of Ophthalmology, Government Medical College and Hospital, Chandigarh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suksham","family":"Jain","sequence":"additional","affiliation":[{"name":"Neonatology, Government Medical College and Hospital, Chandigarh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deepak","family":"Chawla","sequence":"additional","affiliation":[{"name":"Neonatology, Government Medical College and Hospital, Chandigarh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Subina","family":"Narang","sequence":"additional","affiliation":[{"name":"Departments of Ophthalmology, Government Medical College and Hospital, Chandigarh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2021,4,30]]},"reference":[{"issue":"Suppl 10","key":"B1-20240828","doi-asserted-by":"crossref","first-page":"S2","DOI":"10.1186\/1742-4755-10-S1-S2","article-title":"Born too soon:The global epidemiology of 15 million preterm births","volume":"10","author":"Blencowe","year":"2013","journal-title":"Reprod Health"},{"issue":"Suppl 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