scholarly journals Association Between Endogenous Testosterone and Cerebrovascular Disease in the ARIC Study (Atherosclerosis Risk in Communities)

Stroke ◽  
2016 ◽  
Vol 47 (11) ◽  
pp. 2682-2688 ◽  
Author(s):  
Reshmi Srinath ◽  
Rebecca F. Gottesman ◽  
Sherita Hill Golden ◽  
Kathryn A. Carson ◽  
Adrian Dobs
Keyword(s):  
Cerebrovascular Disease ◽  
Atherosclerosis Risk In Communities ◽  
Atherosclerosis Risk ◽  
Aric Study

1398-P: Mortality Implications of Comorbid Health Status in Older Adults with Diabetes: The Atherosclerosis Risk in Communities (ARIC) Study

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1398-P
Author(s):  
MARY R. ROONEY ◽  
OLIVE TANG ◽  
B. GWEN WINDHAM ◽  
JUSTIN B. ECHOUFFO TCHEUGUI ◽  
PAMELA LUTSEY ◽  
...  
Keyword(s):  
Older Adults ◽  
Health Status ◽  
Atherosclerosis Risk In Communities ◽  
Atherosclerosis Risk ◽  
Aric Study

scholarly journals Ascertaining Framingham heart failure phenotype from inpatient electronic health record data using natural language processing: a multicentre Atherosclerosis Risk in Communities (ARIC) validation study

BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e047356
Author(s):  
Carlton R Moore ◽  
Saumya Jain ◽  
Stephanie Haas ◽  
Harish Yadav ◽  
Eric Whitsel ◽  
...  
Keyword(s):  
Language Processing ◽  
Validation Dataset ◽  
Free Text ◽  
Electronic Health Record Data ◽  
Atherosclerosis Risk In Communities ◽  
Clinical Notes ◽  
Atherosclerosis Risk ◽  
Record Data ◽  
Sensitivity Specificity ◽  
Aric Study

ObjectivesUsing free-text clinical notes and reports from hospitalised patients, determine the performance of natural language processing (NLP) ascertainment of Framingham heart failure (HF) criteria and phenotype.Study designA retrospective observational study design of patients hospitalised in 2015 from four hospitals participating in the Atherosclerosis Risk in Communities (ARIC) study was used to determine NLP performance in the ascertainment of Framingham HF criteria and phenotype.SettingFour ARIC study hospitals, each representing an ARIC study region in the USA.ParticipantsA stratified random sample of hospitalisations identified using a broad range of International Classification of Disease, ninth revision, diagnostic codes indicative of an HF event and occurring during 2015 was drawn for this study. A randomly selected set of 394 hospitalisations was used as the derivation dataset and 406 hospitalisations was used as the validation dataset.InterventionUse of NLP on free-text clinical notes and reports to ascertain Framingham HF criteria and phenotype.Primary and secondary outcome measuresNLP performance as measured by sensitivity, specificity, positive-predictive value (PPV) and agreement in ascertainment of Framingham HF criteria and phenotype. Manual medical record review by trained ARIC abstractors was used as the reference standard.ResultsOverall, performance of NLP ascertainment of Framingham HF phenotype in the validation dataset was good, with 78.8%, 81.7%, 84.4% and 80.0% for sensitivity, specificity, PPV and agreement, respectively.ConclusionsBy decreasing the need for manual chart review, our results on the use of NLP to ascertain Framingham HF phenotype from free-text electronic health record data suggest that validated NLP technology holds the potential for significantly improving the feasibility and efficiency of conducting large-scale epidemiologic surveillance of HF prevalence and incidence.

scholarly journals Risk factors for lacune subtypes in the Atherosclerosis Risk in Communities (ARIC) Study

Neurology ◽  
2011 ◽  
Vol 78 (2) ◽  
pp. 102-108 ◽  
Author(s):  
D. C. Bezerra ◽  
A. R. Sharrett ◽  
K. Matsushita ◽  
R. F. Gottesman ◽  
D. Shibata ◽  
...  
Keyword(s):  
Risk Factors ◽  
Atherosclerosis Risk In Communities ◽  
Atherosclerosis Risk ◽  
Aric Study
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