ArticleCirculation. Cardiovascular quality and outcomes2015
Interpreting Hemoglobin A1C in Combination With Conventional Risk Factors for Prediction of Cardiovascular Risk.
Article in Circulation. Cardiovascular quality and outcomes, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
10 citing papers in PubMed, 20 citations in OpenAlex.
- Assessing Glycosylated Hemoglobin Thresholds for Development of Cardiovascular Disease by Racial and Ethnic Groups.Journal of the American Heart Association · 2024Article
- Fasting Plasma Glucose and Glycated Hemoglobin Levels as Risk Factors for the Development of Hypertension: A Retrospective Cohort Study.Diabetes, metabolic syndrome and obesity : targets and therapy · 2023Article
- Article
- Association of glycated hemoglobin ACardiovascular diabetology · 2021Article
- Developing an Internally Validated Veterans Affairs Women Cardiovascular Disease Risk Score Using Veterans Affairs National Electronic Health Records.Journal of the American Heart Association · 2021Article
- Incidence of cardiovascular disease and its associated risk factors in at-risk men and women in the United Arab Emirates: a 9-year retrospective cohort study.BMC cardiovascular disorders · 2019Article
- The association between fasting plasma glucose and glycated hemoglobin in the prediabetes range and future development of hypertension.Cardiovascular diabetology · 2019Article
- Appropriateness of Using Tests for Blood Glucose and Diabetic Complications in Clinical Practice: Experiences in a Hospital in Thailand.Medical science monitor : international medical journal of experimental and clinical research · 2018Article
- Synergy of circulating miR-212 with markers for cardiovascular risks to enhance estimation of atherosclerosis presence.PloS one · 2017Article
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3 authors at 1 institution in 1 country.
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Abstract
backgroundHemoglobin A1C (HbA1C) is associated with increased risk of cardiovascular events, but its use for prediction of cardiovascular disease (CVD) events in combination with conventional risk factors has not been well defined. METHODS AND
resultsTo understand the effect of HbA1C on CVD risk in the context of other CVD risk factors, we analyzed HbA1C and other CVD risk factor measurements in 2000 individuals aged 40 to 79 years without pre-existing diabetes mellitus or CVD from the 2011 to 2012 National Health and Nutrition Examination Surveys survey. The resulting regression model was used to predict the HbA1C distribution based on individual patient characteristics. We then calculated post-test 10-year atherosclerotic CVD risk incorporating the actual versus predicted HbA1C, according to established methods, for a set of example scenarios. Age, sex, race/ethnicity, and traditional cardiovascular risk factors were significant predictors of HbA1C in our model, with the expected HbA1C distribution being significantly higher in non-Hispanic black, non-Hispanic Asian, and Hispanic individuals than that in non-Hispanic white/other individuals. Incorporating the expected HbA1C distribution into pretest atherosclerotic CVD risk has a modest effect on post-test atherosclerotic CVD risk. In the patient examples, we assessed that having an HbA1C of <5.7% reduced post-test risk by 0.4% to 2.0% points, whereas having an HbA1C of ≥6.5% increased post-test risk by 1.0% to 2.5% points, depending on the scenario. The post-test risk increase from having an HbA1C of ≥6.5% tends to approximate the risk increase from being 5 years older.
conclusionsHbA1C has modest effects on predicted atherosclerotic CVD risk when considered in the context of conventional risk factors.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.