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dc.contributor.authorShoshany, Talia
dc.date.accessioned2020-09-15T14:51:37Z
dc.date.created2020-05
dc.date.issued2020-06-24
dc.date.submitted2020
dc.identifier.citationShoshany, Talia. 2020. The Boston Amblyopia Project: Analyzing Real-World Outcomes in Amblyopia Treatment, Identifying Major Challenges in Management, and Characterizing Unique Patient Subgroups Through a Large Retrospective Database. Doctoral dissertation, Harvard Medical School.
dc.identifier.urihttps://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37365219*
dc.description.abstractObjective: Amblyopia is a major cause of vision loss, and questions remain regarding optimal treatment and outcomes. The objective of this study was to develop and query a large retrospective database of amblyopia patients treated at Boston Children’s Hospital to assess specific aspects of follow-up and treatment and to characterize one particularly rare subtype. Methods: A comprehensive database was created of 2037 patients diagnosed with amblyopia at Boston Children’s Hospital from 2010-2014 to conduct three distinct but interrelated analyses. IRIS analysis: Amblyopia treatment success was measured using the AAO IRIS7 and IRIS50 criteria, and multiple demographic and baseline measures were evaluated as independent predictors of success. Lost-to-follow-up analysis: Rate of LTFU was calculated, and multivariate logistic regression was used to create a risk score for predicting LTFU status. Asymmetric, bilateral amblyopia analysis: Patients meeting criteria for asymmetric, bilateral amblyopia were divided into primary and secondary occlusion groups based on timing of patching prescription. Improvement in VA was measured at first, 12-18mo, and last visits and compared between groups. Results: IRIS analysis: 71% were successful by IRIS7 and 81% by IRIS50 (p=0.006). Initial IOD and insurance status correlated with IRIS7 success, while no variables correlated with IRIS50 success. LTFU analysis: A large proportion of patients (23%) were LTFU after first visit. Older age, non-white race, lack of insurance, previous glasses or atropine treatment, and longer requested follow-up intervals were independent predictors of LTFU status. A multivariable risk score was created to predict probability of LTFU (AUC 0.68). Asymmetric, bilateral amblyopia analysis: Of all patients in the database, 7.6% had asymmetric, bilateral amblyopia. The 98 patients meeting inclusion criteria for analysis were divided equally between primary (n=50) and secondary (n=48) occlusion groups. VA in both eyes, IOD, and stereopsis improved similarly between groups, even after stratifying by amblyopia subtype (p≥0.48). Conclusions: Our comprehensive amblyopia database allows us to evaluate the AAO’s new IRIS criteria as a concrete measure for defining amblyopia treatment success, predict which patients are more likely to be LTFU after baseline visit, and develop strategies to mitigate these effects. Finally, we identified a sub-population of patients with asymmetric, bilateral amblyopia, concluding that in this cohort, primary patching or atropine therapy provides no benefit to spectacle correction alone. These findings may help with practice efficiency and improve patient outcomes in the future by transitioning these analyses to an electronic medical record that could be programmed to provide continually updated decision support for individual patients based on large datasets.
dc.description.sponsorshipHonors in a Special Field
dc.format.mimetypeapplication/pdf
dc.language.isoen
dash.licenseLAA
dc.subjectamblyopia
dc.subjectstrabismus
dc.subjectophthalmology
dc.subjectpediatric ophthalmology
dc.subjectpatching
dc.titleThe Boston Amblyopia Project: Analyzing Real-World Outcomes in Amblyopia Treatment, Identifying Major Challenges in Management, and Characterizing Unique Patient Subgroups Through a Large Retrospective Database
dc.typeThesis or Dissertation
dash.depositing.authorShoshany, Talia
dc.date.available2020-09-15T14:51:37Z
thesis.degree.date2020
thesis.degree.grantorHarvard Medical School
thesis.degree.grantorHarvard Medical School
thesis.degree.levelDoctoral
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Medicine
thesis.degree.nameDoctor of Medicine
dc.type.materialtext
dash.identifier.vireo
dc.identifier.orcid0000-0002-9106-6966
dash.author.emailtalia.shosh@gmail.com


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