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C. A. Lofqvist, I. Pupp, E. Engstrom, A. Niklasson, A.-L. Hard, E. Andersson, D. Ley, L. Smith, A. Hellstrom; Early Prediction of ROP - Preliminary Validation of Our Web Based Method. Invest. Ophthalmol. Vis. Sci. 2008;49(13):5048.
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We have developed an algorithm (www.winrop.se) for predicting ROP (Archives of Ophthalmology, 2006) based on longitudinal (weekly) measurements of weight gain and serum insulin-like growth factor-1 (IGF-I) levels from birth until postmentrual age 36 weeks. This monitoring method in the initial study predicted 100% of proliferative and totally excluded 20% of the preterm infants who did not develop proliferative disease. The majority of the infants (80%) who needed no treatment were cleared by the algorithm after an additional follow-up test (including gestational age and birth weight) thus suggesting significantly less screening also in this cohort.
We have initiated a collaborative national study in Sweden to validate this monitoring method. At the neonatal ward in Lund 50 preterm infants have been followed with weekly sampling of blood for IGF-I and weight measurements.
Again 20% of the children who would normally be screened were classified as being "at no risk of developing ROP" and hence could have been totally freed from traditionally screening. At the end of the study none of these children developed any ROP. The initial validation also showed that again 100% of the children who developed proliferative ROP were detected by the program and classified as "at risk of developing proliferative ROP" before signs of proliferative ROP could be seen by the ophthalmologist. In addition we have validated a sampling technique for measuring IGF-I utilizing either serum or blood spots on filter papers in order to minimize blood volumes needed for analysis in fragile preterm children as well as facilitate storing and transportation.
These results are promising and we have initiated an international study to evaluate our web based model on a large cohort of preterm children to improve diagnostics and study possible interventions.
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