Alison X Chan1,2,3, Bharanidharan Radha Saseendrakumar1,2, Daniel J Ozzello3, Michelle Ting3, Jin Sook Yoon3, Catherine Y Liu3, Bobby S Korn3, Don O Kikkawa3, Sally L Baxter1,2. 1. Division of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, California, USA. 2. Ucsd Health Department of Biomedical Informatics, University of California San Diego, La Jolla, California, USA. 3. Division of Oculofacial Plastic and Reconstructive Surgery, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, California, USA.
Abstract
PURPOSE: To identify common factors associated with the loss of an eye using the NIH All of Us database. METHODS: In this case-controlled study, we extracted electronic health record and socio-demographic data for 231 cases of eye loss from All of Us enrollment sites. Controls (N = 924) matched the demographic characteristics of the 2020 United States Census. Bivariate analyses and multivariable logistic regression identified variables significantly associated with increased odds of eye loss. OUTCOME MEASURES: Medical and social determinants associated with increased odds of losing an eye. RESULTS: Among cases, the average age (standard deviation) was 60.1 (14.4) years. The majority (125, 54.1%) were male. 87 (37.7%) identified as African American, and 49 (21.2%) identified as Hispanic or Latino. Loss of eye was more likely in those with ocular tumor (odds ratio [OR] 421.73, 25 95% confidence interval [CI] 129.81-1959.80, p < .001), trauma (OR 13.38, 95% CI 6.64-27.43, p < .001), infection (OR 11.46, 95% CI 4.11-32.26, p = .001) or glaucoma (OR 8.33, 95% CI 4.43- 15.81, p < .001). African American (OR 2.39, 95% CI 1.39-4.09, p = .002) and Hispanic or Latino (OR 1.80, 95% CI 1.01-3.15, p = .04) participants were disproportionately affected. CONCLUSIONS: Racial and ethnic disparities exist among those with loss of an eye from underlying conditions. Addressing health inequities may mitigate the risk of this morbid outcome.
PURPOSE: To identify common factors associated with the loss of an eye using the NIH All of Us database. METHODS: In this case-controlled study, we extracted electronic health record and socio-demographic data for 231 cases of eye loss from All of Us enrollment sites. Controls (N = 924) matched the demographic characteristics of the 2020 United States Census. Bivariate analyses and multivariable logistic regression identified variables significantly associated with increased odds of eye loss. OUTCOME MEASURES: Medical and social determinants associated with increased odds of losing an eye. RESULTS: Among cases, the average age (standard deviation) was 60.1 (14.4) years. The majority (125, 54.1%) were male. 87 (37.7%) identified as African American, and 49 (21.2%) identified as Hispanic or Latino. Loss of eye was more likely in those with ocular tumor (odds ratio [OR] 421.73, 25 95% confidence interval [CI] 129.81-1959.80, p < .001), trauma (OR 13.38, 95% CI 6.64-27.43, p < .001), infection (OR 11.46, 95% CI 4.11-32.26, p = .001) or glaucoma (OR 8.33, 95% CI 4.43- 15.81, p < .001). African American (OR 2.39, 95% CI 1.39-4.09, p = .002) and Hispanic or Latino (OR 1.80, 95% CI 1.01-3.15, p = .04) participants were disproportionately affected. CONCLUSIONS: Racial and ethnic disparities exist among those with loss of an eye from underlying conditions. Addressing health inequities may mitigate the risk of this morbid outcome.
Entities:
Keywords:
Big data; enucleation; health inequities; loss of eye; social determinants of health
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