Periodontal disease is associated with renal insufficiency in the Atherosclerosis Risk In Communities (ARIC) study

2005 ◽  
Vol 45 (4) ◽  
pp. 650-657 ◽  
Author(s):  
Abhijit V. Kshirsagar ◽  
Kevin L. Moss ◽  
John R. Elter ◽  
James D. Beck ◽  
Steve Offenbacher ◽  
...  
Keyword(s):  
Renal Insufficiency ◽  
Periodontal Disease ◽  
Atherosclerosis Risk In Communities ◽  
Atherosclerosis Risk ◽  
Aric Study

Periodontitis and Risk of Diabetes in the Atherosclerosis Risk In Communities (ARIC) Study: A BMI-modified Association

2021 ◽  
Author(s):  
Shaoping Zhang ◽  
Kamaira H Philips ◽  
Kevin Moss ◽  
Di Wu ◽  
Hamdi S Adam ◽  
...  
Keyword(s):  
Periodontal Disease ◽  
Risk Model ◽  
Continuous Variable ◽  
Competing Risk ◽  
Incident Diabetes ◽  
Disease Stage ◽  
Atherosclerosis Risk In Communities ◽  
Biological Variables ◽  
Atherosclerosis Risk ◽  
Aric Study

Abstract Purpose To determine whether periodontal disease is positively associated with incident diabetes across the continuum of body mass levels (BMI) and test the hypothesis that the periodontal risk for incident diabetes is modified by BMI. Methods We included 5569 diabetes-free participants from Visit 4 (1996-1998) of the Atherosclerosis Risk in Communities (ARIC) Study and followed them until 2018. Periodontal disease status was classified by periodontal profile class (PPC)-Stages and incident diabetes was based on participant report of physician diagnosis. We estimated the hazard ratios (HR) for diabetes using a competing risk model for each PPC-Stage. We assessed multiplicative interactions between periodontal disease and BMI (as a continuous variable) on risk of diabetes. Results During a median time of 19.4 years of follow-up, 1,348 incident diabetes cases and 1,529 deaths occurred. Compared to “healthy/incidental disease” Stage , participants with PPC-“severe periodontal disease” or “severe tooth loss” Stage and lower BMI had elevated risk for diabetes adjusting for demographic, smoking, education and biological variables when accounting for death as a competing risk with HRs 1.76 (95%CI 1.10-2.80) and 2.11 (95% CI 1.46-3.04), respectively. The interaction between PPC-stages and BMI was significant (p= 0.01). No significant associations of PPC-Stages with incident diabetes were present when BMI was above 31 kg/m 2. Conclusion Periodontal disease was associated with incident diabetes, especially in non-obese participants. Dentists should be aware that periodontal disease is associated with incident diabetes but the association may be modified for patient’s at higher BMI levels.

scholarly journals Tooth loss, periodontal disease, and cognitive decline in the Atherosclerosis Risk in Communities (ARIC) study

2014 ◽  
Vol 43 (1) ◽  
pp. 47-57 ◽  
Author(s):  
Supawadee Naorungroj ◽  
Victor J. Schoenbach ◽  
Lisa Wruck ◽  
Thomas H. Mosley ◽  
Rebecca F. Gottesman ◽  
...  
Keyword(s):  
Periodontal Disease ◽  
Cognitive Decline ◽  
Tooth Loss ◽  
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.

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