4 results on '"Chiang, Michael F."'
Search Results
2. Aggressive posterior retinopathy of prematurity in two cohorts of patients in South India: implications for primary, secondary, and tertiary prevention.
- Author
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Shah, Parag K., Subramanian, Prema, Venkatapathy, Narendran, Chan, Robison Vernon Paul, Chiang, Michael F., and Campbell, John Peter
- Subjects
RETROLENTAL fibroplasia ,ENDOTHELIAL growth factors ,RETINAL detachment ,MIDDLE-income countries ,LASER photocoagulation ,RETINAL artery - Abstract
Aggressive posterior retinopathy of prematurity (APROP), which has a poor visual prognosis, is common in low- and middle-income countries (LMICs) as a result of suboptimal oxygen monitoring (primary prevention). The purpose of this study was to compare outcomes in APROP eyes treated with laser to eyes treated with antivascular endothelial growth factor (anti-VEGF) therapy. The medical records of a cohort of APROP eyes treated with anti-VEGF (2010-2018) and another of eyes treated with laser photocoagulation (2002-2010) at the same institution in South India were reviewed retrospectively and compared. The main outcome was the proportion of eyes developing retinal detachment during resolution of acute ROP. A total of 398 eyes of 199 preterm babies with APROP were included: 168 eyes were treated with photocoagulation; 230, with anti-VEGF. From 2002 to 2010, compared to the more recent cohort, babies diagnosed with APROP tended to be heavier (P < 0.001), older (P < 0.001), and exposed to fewer days of oxygen (P = 0.02). In the laser-treated cohort, 17 of 168 eyes (10%) developed retinal detachment (7, stage 5; 12, stage 4), compared with 3 of 230 (1%) in the anti-VEGF cohort (all stage 4 [ P = 0.002]). The incidence of retinal detachment was significantly lower in eyes treated with anti-VEGF compared with laser-.treated eyes In the absence of a randomized trial, these data suggest that anti-VEGF may lead to better anatomic outcomes, although questions remain concerning dosage, timing, and risks. [ABSTRACT FROM AUTHOR]
- Published
- 2019
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3. Epidemiologic Evaluation of Retinopathy of Prematurity Severity in a Large Telemedicine Program in India Using Artificial Intelligence.
- Author
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deCampos-Stairiker, Mallory A., Coyner, Aaron S., Gupta, Aditi, Oh, Minn, Shah, Parag K., Subramanian, Prema, Venkatapathy, Narendran, Singh, Praveer, Kalpathy-Cramer, Jayashree, Chiang, Michael F., Chan, R. V. Paul, and Campbell, J. Peter
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RETROLENTAL fibroplasia , *DIABETIC retinopathy , *ARTIFICIAL intelligence , *TELEMEDICINE , *NEONATAL mortality , *EYE care - Abstract
Epidemiological changes in retinopathy of prematurity (ROP) depend on neonatal care, neonatal mortality, and the ability to carefully titrate and monitor oxygen. We evaluate whether an artificial intelligence (AI) algorithm for assessing ROP severity in babies can be used to evaluate changes in disease epidemiology in babies from South India over a 5-year period. Retrospective cohort study. Babies (3093) screened for ROP at neonatal care units (NCUs) across the Aravind Eye Care System (AECS) in South India. Images and clinical data were collected as part of routine tele-ROP screening at the AECS in India over 2 time periods: August 2015 to October 2017 and March 2019 to December 2020. All babies in the original cohort were matched 1:3 by birthweight (BW) and gestational age (GA) with babies in the later cohort. We compared the proportion of eyes with moderate (type 2) or treatment-requiring (TR) ROP, and an AI-derived ROP vascular severity score (from retinal fundus images) at the initial tele-retinal screening exam for all babies in a district, VSS), in the 2 time periods. Differences in the proportions of type 2 or worse and TR-ROP cases, and VSS between time periods. Among BW and GA matched babies, the proportion [95% confidence interval {CI}] of babies with type 2 or worse and TR-ROP decreased from 60.9% [53.8%–67.7%] to 17.1% [14.0%–20.5%] (P < 0.001) and 16.8% [11.9%–22.7%] to 5.1% [3.4%–7.3%] (P < 0.001), over the 2 time periods. Similarly, the median [interquartile range] VSS in the population decreased from 2.9 [1.2] to 2.4 [1.8] (P < 0.001). In South India, over a 5-year period, the proportion of babies developing moderate to severe ROP has dropped significantly for babies at similar demographic risk, strongly suggesting improvements in primary prevention of ROP. These results suggest that AI-based assessment of ROP severity may be a useful epidemiologic tool to evaluate temporal changes in ROP epidemiology. Proprietary or commercial disclosure may be found after the references. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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4. Applications of Artificial Intelligence for Retinopathy of Prematurity Screening.
- Author
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Campbell JP, Singh P, Redd TK, Brown JM, Shah PK, Subramanian P, Rajan R, Valikodath N, Cole E, Ostmo S, Chan RVP, Venkatapathy N, Chiang MF, and Kalpathy-Cramer J
- Subjects
- Female, Gestational Age, Hospital Units, Humans, India, Infant, Newborn, Linear Models, Male, Oxygen analysis, ROC Curve, Retrospective Studies, Sensitivity and Specificity, Artificial Intelligence, Retinopathy of Prematurity diagnosis, Severity of Illness Index, Telemedicine
- Abstract
Objectives: Childhood blindness from retinopathy of prematurity (ROP) is increasing as a result of improvements in neonatal care worldwide. We evaluate the effectiveness of artificial intelligence (AI)-based screening in an Indian ROP telemedicine program and whether differences in ROP severity between neonatal care units (NCUs) identified by using AI are related to differences in oxygen-titrating capability., Methods: External validation study of an existing AI-based quantitative severity scale for ROP on a data set of images from the Retinopathy of Prematurity Eradication Save Our Sight ROP telemedicine program in India. All images were assigned an ROP severity score (1-9) by using the Imaging and Informatics in Retinopathy of Prematurity Deep Learning system. We calculated the area under the receiver operating characteristic curve and sensitivity and specificity for treatment-requiring retinopathy of prematurity. Using multivariable linear regression, we evaluated the mean and median ROP severity in each NCU as a function of mean birth weight, gestational age, and the presence of oxygen blenders and pulse oxygenation monitors., Results: The area under the receiver operating characteristic curve for detection of treatment-requiring retinopathy of prematurity was 0.98, with 100% sensitivity and 78% specificity. We found higher median (interquartile range) ROP severity in NCUs without oxygen blenders and pulse oxygenation monitors, most apparent in bigger infants (>1500 g and 31 weeks' gestation: 2.7 [2.5-3.0] vs 3.1 [2.4-3.8]; P = .007, with adjustment for birth weight and gestational age)., Conclusions: Integration of AI into ROP screening programs may lead to improved access to care for secondary prevention of ROP and may facilitate assessment of disease epidemiology and NCU resources., Competing Interests: POTENTIAL CONFLICT OF INTEREST: The artificial intelligence technology evaluated in this article was invented by Drs Chan, Campbell, Chiang, Brown, and Kalpathy-Cramer and is owned by Oregon Health & Science University, Massachusetts General Hospital, University of Illinois at Chicago, and Northeastern University. Related technology has been licensed for commercial development, which may result in royalties to Massachusetts General Hospital, Oregon Health & Science University, and Dr Kalpathy-Cramer. This potential conflict of interest has been reviewed and managed by Massachusetts General Hospital and Oregon Health & Science University., (Copyright © 2021 by the American Academy of Pediatrics.)
- Published
- 2021
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