Skip to main content

Advertisement

Log in

Predictors of treatment-warranted retinopathy of prematurity in the SUNDROP cohort: influence of photographic features

  • Retinal Disorders
  • Published:
Graefe's Archive for Clinical and Experimental Ophthalmology Aims and scope Submit manuscript

Abstract

Purpose

The Stanford University Network for the Diagnosis of Retinopathy of Prematurity (SUNDROP) initiative—an ongoing telemedicine-based initiative for in-hospital screening of high-risk infants for treatment-warranted ROP (TW-ROP)—has been shown to be a safe, reliable, and cost-effective supplement to the efforts of ROP specialists. We utilized data collected in the SUNDROP initiative to determine demographic (birth weight, sex, multiplicity), weight gain, and ocular imaging (media haze, peripapillary atrophy, fundus pigmentation) predictors of TW-ROP.

Methods

This was a retrospective nested case-control study. Cases and controls were selected from a cohort of 843 low birth weight, premature newborns who survived to an estimated gestational age of 31 weeks and underwent screening through the SUNDROP initiative. Infants were screened at one of six neonatal intensive care units from December 1, 2005, to April 1, 2016. Cases (n = 37) were newborns with TW-ROP who underwent retinal ablative therapy. Two controls (n = 74) without TW-ROP were matched to each case by gestational age. One reviewer graded media haze, presence of peripapillary atrophy, and fundus pigmentation in images taken at the baseline exam for each newborn. The main outcome measure was association of TW-ROP with predictive factors.

Results

In the SUNDROP trial, 37 out of 843 (4.4%) newborns developed TW-ROP. In a multivariable model, birth weight (OR, 0.32; 95% CI, 0.15–0.70) was inversely associated with TW-ROP. In contrast to prior reports, we found no significant difference in sex, multiplicity, or fundus pigmentation at baseline exam in those with TW-ROP as compared to controls. High levels of media haze (>2, scale 0 to 5) were found in the majority of cases (67.6%, 25/37) and controls (65.7%, 44/67). Presence of peripapillary atrophy did not improve prediction of the development of TW-ROP compared to birth weight and weight gain rate alone.

Conclusions

The finding of high levels of media haze at baseline ROP screening exams is novel. This study supports the current model for detection of TW-ROP using birth weight, gestational age, and weight gain rate. We found no significant difference between newborns with TW-ROP and controls in baseline presence of media haze, fundus pigmentation or peripapillary atrophy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Hartnett ME, Penn JS (2012) Mechanisms and management of retinopathy of prematurity. N Engl J Med 367:2515–2526. doi:10.1056/NEJMra1208129

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Smith LE, Hard AL, Hellstrom A (2013) The biology of retinopathy of prematurity: how knowledge of pathogenesis guides treatment. Clin Perinatol 40:201–214. doi:10.1016/j.clp.2013.02.002

    Article  PubMed  PubMed Central  Google Scholar 

  3. Gilbert C, Fielder A, Gordillo L, Quinn G, Semiglia R, Visintin P, Zin A (2005) Characteristics of infants with severe retinopathy of prematurity in countries with low, moderate, and high levels of development: implications for screening programs. Pediatrics 115:e518–e525. doi:10.1542/peds.2004-1180

    Article  PubMed  Google Scholar 

  4. Maguire AA (2006) Screening examination of premature infants for retinopathy of prematurity. Pediatrics 117:572–576. doi:10.1542/peds.2005-2749

    Article  Google Scholar 

  5. Fortes Filho JB, Eckert GU, Procianoy L, Barros CK, Procianoy RS (2009) Incidence and risk factors for retinopathy of prematurity in very low and in extremely low birth weight infants in a unit-based approach in southern Brazil. Eye (Lond) 23:25–30. doi:10.1038/sj.eye.6702924

    Article  CAS  Google Scholar 

  6. Binenbaum G, G-s Y, Quinn GE, Huang J, Dreiseitl S, Antigua J, Foroughi N, Abbasi S (2012) The CHOP postnatal weight gain, birth weight, and gestational age retinopathy of prematurity risk model. Arch Ophthalmol 130:1560. doi:10.1001/archophthalmol.2012.2524

    Article  PubMed  Google Scholar 

  7. Binenbaum G, Gs Y, Quinn GE, Dreiseitl S, Karp K, Roberts RS, Kirpalani H (2011) A clinical prediction model to stratify retinopathy of prematurity risk using postnatal weight gain. Pediatrics 127:e607–e614. doi:10.1542/peds.2010-2240

    Article  PubMed  PubMed Central  Google Scholar 

  8. Hellström A, Smith LEH, Dammann O (2013) Retinopathy of prematurity. Lancet 382:1445–1457. doi:10.1016/s0140-6736(13)60178-6

    Article  PubMed  PubMed Central  Google Scholar 

  9. Kumar P, Sankar MJ, Deorari A, Azad R, Chandra P, Agarwal R, Paul V (2011) Risk factors for severe retinopathy of prematurity in preterm low birth weight neonates. Indian J Pediatr 78:812–816. doi:10.1007/s12098-011-0363-7

    Article  PubMed  Google Scholar 

  10. Chen ML, Guo L, Smith LEH, Dammann CEL, Dammann O (2010) High or low oxygen saturation and severe retinopathy of prematurity: a meta-analysis. Pediatrics 125:e1483–e1492. doi:10.1542/peds.2009-2218

    Article  PubMed  PubMed Central  Google Scholar 

  11. Hakeem AH, Mohamed GB, Othman MF (2012) Retinopathy of prematurity: a study of prevalence and risk factors. Middle East Afr J Ophthalmol 19:289–294. doi:10.4103/0974-9233.97927

    Article  PubMed  PubMed Central  Google Scholar 

  12. Mittal M, Dhanireddy R, Higgins RD (1998) Candida sepsis and association with retinopathy of prematurity. Pediatrics 101:654–657. doi:10.1542/peds.101.4.654

    Article  CAS  PubMed  Google Scholar 

  13. Manzoni P, Maestri A, Leonessa M, Mostert M, Farina D, Gomirato G (2005) Fungal and bacterial sepsis and threshold ROP in preterm very low birth weight neonates. J Perinatol 26:23–30. doi:10.1038/sj.jp.7211420

    Article  Google Scholar 

  14. AAP (2013) Retinopathy of prematurity. Am Assoc Pediatr Ophthalmol Strabismus 117(2):572 108(3):809

    Google Scholar 

  15. Tasman W (1988) Multicenter trial of cryotherapy for retinopathy of prematurity. Preliminary results. Cryotherapy for retinopathy of prematurity cooperative group. Arch Ophthalmol 106:471–479

    Article  Google Scholar 

  16. Palmer EA, Hardy RJ, Dobson V, Phelps DL, Quinn GE, Summers CG, Krom CP, Tung B (2005) 15-year outcomes following threshold retinopathy of prematurity: final results from the multicenter trial of cryotherapy for retinopathy of prematurity. Arch Ophthalmol 123:311–318. doi:10.1001/archopht.123.3.311

    Article  PubMed  Google Scholar 

  17. Early Treatment For Retinopathy Of Prematurity Cooperative G (2003) Revised indications for the treatment of retinopathy of prematurity: results of the early treatment for retinopathy of prematurity randomized trial. Arch Ophthalmol 121:1684–1694. doi:10.1001/archopht.121.12.1684

    Article  Google Scholar 

  18. Mintz-Hittner HA, Kennedy KA, Chuang AZ (2011) Efficacy of intravitreal bevacizumab for stage 3+ retinopathy of prematurity. N Engl J Med 364:603–615. doi:10.1056/NEJMoa1007374

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Fierson WM (2013) Screening examination of premature infants for retinopathy of prematurity. Pediatrics 131:189–195. doi:10.1542/peds.2012-2996

    Article  PubMed  Google Scholar 

  20. Ells AL, Holmes JM, Astle WF, Williams G, Leske DA, Fielden M, Uphill B, Jennett P, Hebert M (2003) Telemedicine approach to screening for severe retinopathy of prematurity: a pilot study. Ophthalmology 110:2113–2117. doi:10.1016/s0161-6420(03)00831-5

    Article  PubMed  Google Scholar 

  21. Ying GS, Quinn GE, Wade KC, Repka MX, Baumritter A, Daniel E (2015) Predictors for the development of referral-warranted retinopathy of prematurity in the telemedicine approaches to evaluating acute-phase retinopathy of prematurity (e-ROP) study. JAMA Ophthalmol 133:304–311. doi:10.1001/jamaophthalmol.2014.5185

    Article  PubMed  PubMed Central  Google Scholar 

  22. Kim J, Jin JY, Kim SS (2015) Postnatal weight gain in the first two weeks as a predicting factor of severe retinopathy of prematurity requiring treatment. Korean J Pediatr 58:52–59. doi:10.3345/kjp.2015.58.2.52

    Article  PubMed  PubMed Central  Google Scholar 

  23. Celebi AR, Petricli IS, Hekimoglu E, Demirel N, Bas AY (2014) The incidence and risk factors of severe retinopathy of prematurity in extremely low birth weight infants in Turkey. Med Sci Monit 20:1647–1653. doi:10.12659/msm.892262

    Article  PubMed  PubMed Central  Google Scholar 

  24. Cerman E, Balci SY, Yenice OS, Kazokoglu H, Celiker H, Eraslan M (2014) Screening for retinopathy of prematurity in a tertiary ophthalmology Department in Turkey: incidence, outcomes, and risk factors. Ophthal Surg Lasers Imaging Retin 45:550–555. doi:10.3928/23258160-20141118-10

    Article  Google Scholar 

  25. Fortes Filho JB, Bonomo PP, Maia M, Procianoy RS (2009) Weight gain measured at 6 weeks after birth as a predictor for severe retinopathy of prematurity: study with 317 very low birth weight preterm babies. Graefes Arch Clin Exp Ophthalmol 247:831–836. doi:10.1007/s00417-008-1012-3

    Article  PubMed  Google Scholar 

  26. Authors N (2001) Screening examination of premature infants for retinopathy of prematurity. Pediatrics 108:809–811

    Article  Google Scholar 

  27. Jabs DA, Nussenblatt RB, Rosenbaum JT (2005) Standardization of uveitis nomenclature for reporting clinical data. Results of the first international workshop. Am J Ophthalmol 140:509–516

    Article  PubMed  Google Scholar 

  28. Nussenblatt RB, Palestine AG, Chan CC, Roberge F (1985) Standardization of vitreal inflammatory activity in intermediate and posterior uveitis. Ophthalmology 92:467–471

    Article  CAS  PubMed  Google Scholar 

  29. Mosier MA, Lieberman MF, Green WR, Knox DL (1978) Hypoplasia of the optic nerve. Arch Ophthalmol 96:1437–1442

    Article  CAS  PubMed  Google Scholar 

  30. Fenton TR, Nasser R, Eliasziw M, Kim JH, Bilan D, Sauve R (2013) Validating the weight gain of preterm infants between the reference growth curve of the fetus and the term infant. BMC Pediatr 13:92. doi:10.1186/1471-2431-13-92

    Article  PubMed  PubMed Central  Google Scholar 

  31. Viera AJ, Garrett JM (2005) Understanding interobserver agreement: the kappa statistic. Fam Med 37:360–363

    PubMed  Google Scholar 

  32. Evans JD (1996) Straightforward statistics for the behavioral sciences. Brooks/Cole Publishing, Pacific Grove

    Google Scholar 

  33. Schaffer DB, Palmer EA, Plotsky DF, Metz HS, Flynn JT, Tung B, Hardy RJ (1993) Prognostic factors in the natural course of retinopathy of prematurity. Ophthalmology 100:230–237. doi:10.1016/s0161-6420(93)31665-9

    Article  CAS  PubMed  Google Scholar 

  34. Good WV, Hardy RJ, Dobson V, Palmer EA, Phelps DL, Quintos M, Tung B (2005) The incidence and course of retinopathy of prematurity: findings from the early treatment for retinopathy of prematurity study. Pediatrics 116:15–23. doi:10.1542/peds.2004-1413

    Article  PubMed  Google Scholar 

  35. Hardy RJ, Palmer EA, Dobson V, Summers CG, Phelps DL, Quinn GE, Good WV, Tung B (2003) Risk analysis of prethreshold retinopathy of prematurity. Arch Ophthalmol 121:1697–1701. doi:10.1001/archopht.121.12.1697

    Article  PubMed  Google Scholar 

  36. Hellstrom A, Perruzzi C, Ju M, Engstrom E, Hard AL, Liu JL, Albertsson-Wikland K, Carlsson B, Niklasson A, Sjodell L, LeRoith D, Senger DR, Smith LEH (2001) Low IGF-I suppresses VEGF-survival signaling in retinal endothelial cells: direct correlation with clinical retinopathy of prematurity. Proc Natl Acad Sci 98:5804–5808. doi:10.1073/pnas.101113998

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Hellstrom A, Engstrom E, Hard AL, Albertsson-Wikland K, Carlsson B, Niklasson A, Lofqvist C, Svensson E, Holm S, Ewald U, Holmstrom G, Smith LEH (2003) Postnatal serum insulin-like growth factor I deficiency is associated with retinopathy of prematurity and other complications of premature birth. Pediatrics 112:1016–1020. doi:10.1542/peds.112.5.1016

    Article  PubMed  Google Scholar 

  38. Smith LE, Shen W, Perruzzi C, Soker S, Kinose F, Xu X, Robinson G, Driver S, Bischoff J, Zhang B, Schaeffer JM, Senger DR (1999) Regulation of vascular endothelial growth factor-dependent retinal neovascularization by insulin-like growth factor-1 receptor. Nat Med 5:1390–1395. doi:10.1038/70963

    Article  CAS  PubMed  Google Scholar 

  39. Lofqvist C, Andersson E, Sigurdsson J, Engstrom E, Hard AL, Niklasson A, Smith LE, Hellstrom A (2006) Longitudinal postnatal weight and insulin-like growth factor I measurements in the prediction of retinopathy of prematurity. Arch Ophthalmol 124:1711–1718. doi:10.1001/archopht.124.12.1711

    Article  PubMed  Google Scholar 

  40. Lofqvist C, Hansen-Pupp I, Andersson E, Holm K, Smith LE, Ley D, Hellstrom A (2009) Validation of a new retinopathy of prematurity screening method monitoring longitudinal postnatal weight and insulinlike growth factor I. Arch Ophthalmol 127:622–627. doi:10.1001/archophthalmol.2009.69

    Article  PubMed  Google Scholar 

  41. Hellstrom A, Hard AL, Engstrom E, Niklasson A, Andersson E, Smith L, Lofqvist C (2009) Early weight gain predicts retinopathy in preterm infants: new, simple, efficient approach to screening. Pediatrics 123:e638–e645. doi:10.1542/peds.2008-2697

    Article  PubMed  Google Scholar 

  42. Wallace DK, Kylstra JA, Phillips SJ, Hall JG (2000) Poor postnatal weight gain: a risk factor for severe retinopathy of prematurity. J aapos 4:343–347. doi:10.1067/mpa.2000.110342

    Article  CAS  PubMed  Google Scholar 

  43. Stenson BJ, Tarnow-Mordi WO, Darlow BA, Simes J, Juszczak E, Askie L, Battin M, Bowler U, Broadbent R, Cairns P, Davis PG, Deshpande S, Donoghoe M, Doyle L, Fleck BW, Ghadge A, Hague W, Halliday HL, Hewson M, King A, Kirby A, Marlow N, Meyer M, Morley C, Simmer K, Tin W, Wardle SP, Brocklehurst P (2013) Oxygen saturation and outcomes in preterm infants. N Engl J Med 368:2094–2104. doi:10.1056/NEJMoa1302298

    Article  PubMed  Google Scholar 

  44. Carlo WA, Finer NN, Walsh MC, Rich W, Gantz MG, Laptook AR, Yoder BA, Faix RG, Das A, Poole WK, Schibler K, Newman NS, Ambalavanan N, Frantz ID 3rd, Piazza AJ, Sanchez PJ, Morris BH, Laroia N, Phelps DL, Poindexter BB, Cotten CM, Van Meurs KP, Duara S, Narendran V, Sood BG, O’Shea TM, Bell EF, Ehrenkranz RA, Watterberg KL, Higgins RD (2010) Target ranges of oxygen saturation in extremely preterm infants. N Engl J Med 362:1959–1969. doi:10.1056/NEJMoa0911781

    Article  CAS  PubMed  Google Scholar 

  45. Authors N (1985) An international classification of retinopathy of prematurity. Int Ophthalmol 8:3–10

    Article  Google Scholar 

  46. Hartnett ME (2003) Features associated with surgical outcome in patients with stages 4 and 5 retinopathy of prematurity. Retina 23:322–329

    Article  PubMed  Google Scholar 

  47. Ozdek S, Unlu M, Gurelik G, Hasanreisoglu B (2013) Intravitreal anti-VEGF therapy as an adjunct to laser photocoagulation for severe aggressive posterior retinopathy of prematurity. J Optom 6:51–59. doi:10.1016/j.optom.2012.08.004

    Article  Google Scholar 

  48. Monos T, Rosen SD, Karplus M, Yassur Y (1996) Fundus pigmentation in retinopathy of prematurity. Pediatrics 97:343–348

    CAS  PubMed  Google Scholar 

  49. Saunders RA (1997) Racial variation in retinopathy of prematurity. Arch Ophthalmol 115:604. doi:10.1001/archopht.1997.01100150606005

    Article  CAS  PubMed  Google Scholar 

  50. Yang MB, Rao S, Copenhagen DR, Lang RA (2013) Length of day during early gestation as a predictor of risk for severe retinopathy of prematurity. Ophthalmology 120:2706–2713. doi:10.1016/j.ophtha.2013.07.051

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Many thanks to Julia Simard, Sc.D. and Rita Popat, Ph.D. who played critical advisory roles in study design and analysis. We thank Andrew Martin at the Stanford Center for Clinical Informatics who provided database design and management. The Research Electronic Data Capture (REDCap) database tool hosted by Stanford University is maintained by the Stanford Center for Clinical Informatics grant support (Stanford CTSA award number UL1 RR025744 from NIH/NCRR). The authors report no conflict of interest.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Darius M. Moshfeghi.

Ethics declarations

Funding

Funding for this project was provided in the form of a grant from the Giannini Foundation. Additionally, the project described herein was conducted with financial support for Cassie A. Ludwig from the TL1 component of the Stanford Clinical and Translational Science Award to Spectrum (NIH TL1 TR 001084). Neither sponsor had any role in the design or conduct of this research.

Conflict of interest

All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. For this type of study formal consent is not required.

Electronic supplementary material

ESM 1

(XLSX 51 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ludwig, C.A., Greven, M.A. & Moshfeghi, D.M. Predictors of treatment-warranted retinopathy of prematurity in the SUNDROP cohort: influence of photographic features. Graefes Arch Clin Exp Ophthalmol 255, 1935–1946 (2017). https://doi.org/10.1007/s00417-017-3745-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00417-017-3745-3

Keywords

Navigation