Using clinical data, hypothesis generation tools and PubMed trends to discover the association between diabetic retinopathy and antihypertensive drugs

Katherine Senter, Sreenivas R. Sukumar, Robert M. Patton, Edward Chaum

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Diabetic retinopathy (DR) is a leading cause of blindness and common complication of diabetes. Many diabetic patients take antihypertensive drugs to prevent cardiovascular problems, but these drugs may have unintended consequences on eyesight. Six common classes of antihypertensive drug are angiotensin converting enzyme (ACE) inhibitors, alpha blockers, angiotensin receptor blockers (ARBs), β-blockers, calcium channel blockers, and diuretics. Analysis of medical history data might indicate which of these drugs provide safe blood pressure control, and a literature review is often used to guide such analyses. Beyond manual reading of relevant publications, we sought to identify quantitative trends in literature from the biomedical database PubMed to compare with quantitative trends in the clinical data. By recording and analyzing PubMed search results, we found wide variation in the prevalence of each antihypertensive drug in DR literature. Drug classes developed more recently such as ACE inhibitors and ARBs were most prevalent. We also identified instances of change-over-time in publication patterns. We then compared these literature trends to a dataset of 500 diabetic patients from the UT Hamilton Eye Institute. Data for each patient included class of antihypertensive drug, presence and severity of DR. Graphical comparison revealed that older drug classes such as diuretics, calcium channel blockers, and β-blockers were much more prevalent in the clinical data than in the DR and antihypertensive literature. Finally, quantitative analysis of the dataset revealed that patients taking β-blockers were statistically more likely to have DR than patients taking other medications, controlling for presence of hypertension and year of diabetes onset. This finding was concerning given the prevalence of β-blockers in the clinical data. We determined that clinical use of β-blockers should be minimized in diabetic patients to prevent retinal damage.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2578-2582
Number of pages5
ISBN (Electronic)9781479999255
DOIs
StatePublished - Dec 22 2015
Event3rd IEEE International Conference on Big Data, IEEE Big Data 2015 - Santa Clara, United States
Duration: Oct 29 2015Nov 1 2015

Other

Other3rd IEEE International Conference on Big Data, IEEE Big Data 2015
CountryUnited States
CitySanta Clara
Period10/29/1511/1/15

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Medical problems
Calcium
Enzymes
Association reactions
Pressure control
Blood pressure
Chemical analysis

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Software

Cite this

Senter, K., Sukumar, S. R., Patton, R. M., & Chaum, E. (2015). Using clinical data, hypothesis generation tools and PubMed trends to discover the association between diabetic retinopathy and antihypertensive drugs. In Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015 (pp. 2578-2582). [7364055] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2015.7364055

Using clinical data, hypothesis generation tools and PubMed trends to discover the association between diabetic retinopathy and antihypertensive drugs. / Senter, Katherine; Sukumar, Sreenivas R.; Patton, Robert M.; Chaum, Edward.

Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 2578-2582 7364055.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Senter, K, Sukumar, SR, Patton, RM & Chaum, E 2015, Using clinical data, hypothesis generation tools and PubMed trends to discover the association between diabetic retinopathy and antihypertensive drugs. in Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015., 7364055, Institute of Electrical and Electronics Engineers Inc., pp. 2578-2582, 3rd IEEE International Conference on Big Data, IEEE Big Data 2015, Santa Clara, United States, 10/29/15. https://doi.org/10.1109/BigData.2015.7364055
Senter K, Sukumar SR, Patton RM, Chaum E. Using clinical data, hypothesis generation tools and PubMed trends to discover the association between diabetic retinopathy and antihypertensive drugs. In Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 2578-2582. 7364055 https://doi.org/10.1109/BigData.2015.7364055
Senter, Katherine ; Sukumar, Sreenivas R. ; Patton, Robert M. ; Chaum, Edward. / Using clinical data, hypothesis generation tools and PubMed trends to discover the association between diabetic retinopathy and antihypertensive drugs. Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 2578-2582
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