Incidence, demographics, types and risk factors of dry eye disease in India: Electronic medical records driven big data analytics report I

Donthineni, Pragnya Rao; Kammari, Priyanka; Shanbhag, Swapna S; Singh, Vivek; Das, Anthony Vipin; Basu, Sayan

doi:10.1016/j.jtos.2019.02.007

Cited by 118 publications

(95 citation statements)

References 23 publications

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“…The indigenously created and customized EMR allowed for a standardized data entry and data collection free of any transcription errors. [9][10][11] The study included multiple centers of our eye care network across a wide geographic reach. This sort of a multitier network analysis allowed for the inclusion of both rural and urban populations, thus covering all the different demographic groups in the study.…”

Section: Discussionmentioning

confidence: 99%

<p>Demography and Clinical Features of Chalazion Among Patients Seen at a Multi-Tier Eye Care Network in India: An Electronic Medical Records Driven Big Data Analysis Report</p>

Das¹,

Dave²

2020

OPTH

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Purpose: To describe the prevalence, demographics and clinical presentations of chalazion in patients presenting to a multi-tier ophthalmology network in India. Materials and Methods: This was a cross-sectional observational multi-centric hospitalbased study of 1,982,058 new patients presenting between 2010 and 2019. Patients with both symptoms and signs of chalazion were considered as subjects. The data were retrieved using an electronic medical record system. Results: Overall, 11,270 (0.57%) new patients were diagnosed with chalazion. Of these, 1,085 (10%) patients had recurrent chalazia. The prevalence rates were 0.95% in children and 0.51% in adults. Males accounted for 51% of the cases, and 79% had unilateral affliction. The commonest age group affected was the third decade of life (31%). Of the 13,691 affected eyes with chalazion, 39% were located in the upper eyelid, 6% were lateral in position and 3% have multiple swellings at presentation. Conservative treatment was the preferred treatment modality in 85%. Incision and curettage were performed in 15% eyes and intralesional steroid in 0.55% eyes. Of the 15% patients that were advised surgery, 9% underwent the procedure with a conversion rate of 58%. Conclusion: Only a miniscule percentage of patients seeking eye care in India are affected by chalazion. It is slightly more common in males and is usually unilateral and largely affects the upper eyelids. It is recurrent in a tenth of the cases. Conservative management is the preferred modality.

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Section: Discussionmentioning

confidence: 99%

<p>Demography and Clinical Features of Chalazion Among Patients Seen at a Multi-Tier Eye Care Network in India: An Electronic Medical Records Driven Big Data Analysis Report</p>

Das¹,

Dave²

2020

OPTH

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“…Of the 1,458,830 new patients recruited 21,290 (1.46%) had recent-onset DED with age, gender, residence, occupation, socio-economic status having a signi cant impact of development of the disease (19), while of the 259,969 new patients (≤21years) 10.1% had AED. Boys with atopy during middle childhood and from middle to higher income families were commonly affected AED which was self-limiting by adolescence.…”

Section: Discussionmentioning

confidence: 99%

OphthatomeTM: An integrated knowledgebase of ophthalmic diseases for translating vision research into the clinic

Raj

Tejwani

Sudha

et al. 2020

Preprint

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Background: Medical big data analytics has revolutionized the human healthcare system by introducing processes that facilitate rationale clinical decision making, predictive or prognostic modelling of the disease progression and management, disease surveillance, overall impact on public health and research. Although, the electronic medical records (EMR) system is the digital storehouse of rich medical data of a large patient cohort collected over many years, the data lack sufficient structure to be of clinical value for applying deep learning methods and advanced analytics to improve disease management at an individual patient level or for the discipline in general. Ophthatome TM captures data contained in retrospective electronic medical records between September 2012 and January 2018 to facilitate translational vision research through a knowledgebase of ophthalmic diseases. Methods: The electronic medical records data from Narayana Nethralaya ophthalmic hospital recorded in the MS-SQL database was mapped and programmatically transferred to MySQL. The captured data was manually curated to preserve data integrity and accuracy. The data was stored in MySQL database management system for ease of visualization, advanced search functions and other knowledgebase applications. Results: Ophthatome TM is a comprehensive and accurate knowledgebase of ophthalmic diseases containing curated clinical, treatment and imaging data of 581,466 ophthalmic subjects from the Indian population, recorded between September 2012 and January 2018. Ophthatome TM provides filters and Boolean searches with operators and modifiers that allow selection of specific cohorts covering 524 distinct ophthalmic disease types and 1800 disease sub-types across 35 different anatomical regions of the eye. The availability of longitudinal data for about 300,000 subjects provides additional opportunity to perform clinical research on disease progression and management including drug responses and management outcomes. The knowledgebase captures ophthalmic diseases in a genetically diverse population providing opportunity to study genetic and environmental factors contributing to or influencing ophthalmic diseases. Conclusion: Ophthatome TM will accelerate clinical, genomic, pharmacogenomic and advanced translational research in ophthalmology and vision sciences. Key words: Ophthatome, knowledge base, electronic medical records, curated clinical data, defined cohort, vision sciences

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“…Studies done in larger cohorts in India have reported an increased incidence of DED with age, which is also the pattern seen with cataract (8,9). It is hence not uncommon to encounter situations where we need to either simultaneously or sequentially manage both dry eye and cataract.…”

Section: Introductionmentioning

confidence: 95%

Cataract Surgery in Dry Eye Disease: Visual Outcomes and Complications

et al. 2020

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Purpose: To describe the visual outcomes and complications following cataract surgery in dry eye disease (DED). Methods: This retrospective study included 668 eyes of 399 patients with DED, who underwent cataract surgery between 2011 and 2019 at our multi-tier ophthalmology hospital network. Based on etiology, they were divided into three groups: cicatrizing conjunctivitis (CC), meibomian gland dysfunction (MGD), and Sjogren's syndrome (SS). The data on demographics, visual impairment, surgical technique, visual outcomes, and complications were collected using an electronic medical record system. Median LogMAR best corrected visual acuity (BCVA) with interquartile range (IQR) was compared using Wilcoxon's rank sum test. Results: The median age at which cataract surgery was performed was 58 (IQR: 47-65) years. Etiology of DED was CC in 279, MGD in 255, and SS in 134 eyes. Most (471) eyes underwent phacoemulsification, under peribulbar anesthesia (548) through a temporal clear corneal incision (209) with foldable intraocular lens implantation (417). The overall median LogMAR BCVA improved from 1.1 (IQR: 0.6-2.1) at baseline to 0.3 (IQR: 0.1-0.7) and 0.1 (IQR: 0-0.65) at 1 and 6 weeks (p < 0.0001) post-operatively. The median 6 weeks post-operative BCVA was 0.3, 0.1, and 0.1 in CC, MGD, and SS, respectively, and significantly better than at baseline (p < 0.0001). The leading cause of sub-optimal vision was corneal scarring (44; 9%), and the most common complication was posterior capsular rupture with vitreous loss (23; 3%). Conclusion: Cataract surgery has good visual outcomes in patients with DED, without any disconcerting rate of complications. Pre-existing keratopathy is the main determinant of the extent of post-operative visual recovery.

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Incidence, demographics, types and risk factors of dry eye disease in India: Electronic medical records driven big data analytics report I

Cited by 118 publications

References 23 publications

<p>Demography and Clinical Features of Chalazion Among Patients Seen at a Multi-Tier Eye Care Network in India: An Electronic Medical Records Driven Big Data Analysis Report</p>

<p>Demography and Clinical Features of Chalazion Among Patients Seen at a Multi-Tier Eye Care Network in India: An Electronic Medical Records Driven Big Data Analysis Report</p>

OphthatomeTM: An integrated knowledgebase of ophthalmic diseases for translating vision research into the clinic

Cataract Surgery in Dry Eye Disease: Visual Outcomes and Complications

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