scholarly journals Cardiovascular disease risk prediction for people with type 2 diabetes in a population-based cohort and in electronic health record data

JAMIA Open ◽  
2020 ◽  
Author(s):  
Jackie Szymonifka ◽  
Sarah Conderino ◽  
Christine Cigolle ◽  
Jinkyung Ha ◽  
Mohammed Kabeto ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Risk Prediction ◽  
Incidence Rates ◽  
Risk Scores ◽  
Cvd Risk ◽  
Clinical Risk ◽  
Demographic Covariates

Abstract Objective Electronic health records (EHRs) have become a common data source for clinical risk prediction, offering large sample sizes and frequently sampled metrics. There may be notable differences between hospital-based EHR and traditional cohort samples: EHR data often are not population-representative random samples, even for particular diseases, as they tend to be sicker with higher healthcare utilization, while cohort studies often sample healthier subjects who typically are more likely to participate. We investigate heterogeneities between EHR- and cohort-based inferences including incidence rates, risk factor identifications/quantifications, and absolute risks. Materials and methods This is a retrospective cohort study of older patients with type 2 diabetes using EHR from New York University Langone Health ambulatory care (NYULH-EHR, years 2009–2017) and from the Health and Retirement Survey (HRS, 1995–2014) to study subsequent cardiovascular disease (CVD) risks. We used the same eligibility criteria, outcome definitions, and demographic covariates/biomarkers in both datasets. We compared subsequent CVD incidence rates, hazard ratios (HRs) of risk factors, and discrimination/calibration performances of CVD risk scores. Results The estimated subsequent total CVD incidence rate was 37.5 and 90.6 per 1000 person-years since T2DM onset in HRS and NYULH-EHR respectively. HR estimates were comparable between the datasets for most demographic covariates/biomarkers. Common CVD risk scores underestimated observed total CVD risks in NYULH-EHR. Discussion and conclusion EHR-estimated HRs of demographic and major clinical risk factors for CVD were mostly consistent with the estimates from a national cohort, despite high incidences and absolute risks of total CVD outcome in the EHR samples.

scholarly journals Epigenetic age acceleration is associated with cardiometabolic risk factors and clinical cardiovascular disease risk scores in African Americans

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Farah Ammous ◽  
Wei Zhao ◽  
Scott M. Ratliff ◽  
Thomas H. Mosley ◽  
Lawrence F. Bielak ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
African Americans ◽  
Risk Prediction ◽  
Risk Scores ◽  
Cvd Risk Factors ◽  
Cvd Risk ◽  
Clinical Risk ◽  
Epigenetic Age ◽  
Epigenetic Age Acceleration

Abstract Background Cardiovascular disease (CVD) is the leading cause of mortality among US adults. African Americans have higher burden of CVD morbidity and mortality compared to any other racial group. Identifying biomarkers for clinical risk prediction of CVD offers an opportunity for precision prevention and earlier intervention. Results Using linear mixed models, we investigated the cross-sectional association between four measures of epigenetic age acceleration (intrinsic (IEAA), extrinsic (EEAA), PhenoAge (PhenoAA), and GrimAge (GrimAA)) and ten cardiometabolic markers of hypertension, insulin resistance, and dyslipidemia in 1,100 primarily hypertensive African Americans from sibships in the Genetic Epidemiology Network of Arteriopathy (GENOA). We then assessed the association between epigenetic age acceleration and time to self-reported incident CVD using frailty hazard models and investigated CVD risk prediction improvement compared to models with clinical risk scores (Framingham risk score (FRS) and the atherosclerotic cardiovascular disease (ASCVD) risk equation). After adjusting for sex and chronological age, increased epigenetic age acceleration was associated with higher systolic blood pressure (IEAA), higher pulse pressure (EEAA and GrimAA), higher fasting glucose (PhenoAA and GrimAA), higher fasting insulin (EEAA), lower low density cholesterol (GrimAA), and higher triglycerides (GrimAA). A five-year increase in GrimAA was associated with CVD incidence with a hazard ratio of 1.54 (95% CI 1.22–2.01) and remained significant after adjusting for CVD risk factors. The addition of GrimAA to risk score models improved model fit using likelihood ratio tests (P = 0.013 for FRS and P = 0.008 for ASCVD), but did not improve C statistics (P > 0.05). Net reclassification index (NRI) showed small but significant improvement in reassignment of risk categories with the addition of GrimAA to FRS (NRI: 0.055, 95% CI 0.040–0.071) and the ASCVD equation (NRI: 0.029, 95% CI 0.006–0.064). Conclusions Epigenetic age acceleration measures are associated with traditional CVD risk factors in an African-American cohort with a high prevalence of hypertension. GrimAA was associated with CVD incidence and slightly improved prediction of CVD events over clinical risk scores.

scholarly journals Cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care setting

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
K D Dziopa ◽  
F W A Asselbergs ◽  
J G Gratton ◽  
N C Chaturvedi ◽  
A F S Schmidt
Keyword(s):  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Cardiovascular Risk ◽  
General Population ◽  
Risk Prediction ◽  
Risk Scores ◽  
Cvd Risk ◽  
C Statistic ◽  
Cardiovascular Risk Prediction

Abstract   People with type 2 diabetes (T2DM) remain at high risk for cardiovascular disease (CVD) CVD treatment initiation and intensification are guided by risk prediction algorithms. The majority of CVD risk prediction tools have not been validated in T2DM. We compared the performance of general and diabetes specific cardiovascular risk prediction scores for cardiovascular disease (CVD ie coronary heart disease and stroke), CVD+ (including atrial fibrillation and heart failure), and their individual components, in type 2 diabetes patients (T2DM). Scores were identified through a systematic review and included irrespective of the type of predicted CVD, or inclusion of T2DM patients. Performance was assessed in a contemporary sample of 203,172 UK T2DM. We identified 22 scores: 11 derived in the general population, 9 in T2DM patients, and 2 excluded T2DM patients. Over 10 years follow-up, 63,000 events occurred. The RECODE score, derived in people with T2DM, performed best for both CVD (c-statistic 0.731 (0.728,0.734), and CVD+ (0.732 (0.729,0.735)). Calibration slopes (1 indicates perfect calibration) ranged from 0.38 (95% CI 0.37; 0.39) to 1.05 (95% CI 1.03; 1.07). A simple, population specific recalibration process considerably improved performance, now ranging between 0.98 and 1.03. Risk scores performed badly in people with pre-existing CVD (c-statistic ∼0.55). CVD risk prediction scores performed worse in T2DM than in the general population, irrespective of derivation population, and of original predicted outcome. Scores performed especially poorly in patients with established CVD. A simple population specific recalibration markedly improved score performance and is recommended for future use. FUNDunding Acknowledgement Type of funding sources: Public grant(s) – EU funding. Main funding source(s): NPIF programme

Determining the Cardiovascular Disease Risk Factor Knowledge and Related Factors Among Adults With Type 2 Diabetes Mellitus

2021 ◽  
pp. 105477382110464
Author(s):  
Emine Karaman ◽  
Aslı Kalkım ◽  
Banu Pınar Şarer Yürekli
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Cvd Risk Factors ◽  
Cvd Risk ◽  
Related Factors

In this study was to determine knowledge of cardiovascular disease (CVD) risk factors and to explore related factors among adults with type 2 diabetes mellitus (DM) who have not been diagnosed with CVD. This descriptive study was conducted with 175 adults. Data were collected individual identification form and Cardiovascular Disease Risk Factors Knowledge Level (CARRF-KL) scale. A negative correlation was found between age and CARRF-KL score. A significant difference was found between educational status and CARRF-KL score. The individuals described their health status as good, managed their condition with diet and exercise, received information from nurses, adults with DM in their family and those with no DM complications had significantly higher scores in CARRF-KL. The knowledge of an individual with DM about CVD risk factors should be assessed, CVD risks should be identified at an early stage, and individuals at risk should be subjected to screening.

Physical activity less than the recommended amount may prevent the onset of major biological risk factors for cardiovascular disease: a cohort study of 198 919 adults

2018 ◽  
Vol 54 (4) ◽  
pp. 238-244 ◽  
Author(s):  
David Martinez-Gomez ◽  
Irene Esteban-Cornejo ◽  
Esther Lopez-Garcia ◽  
Esther García-Esquinas ◽  
Kabir P Sadarangani ◽  
...  
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Cvd Risk Factors ◽  
Cvd Risk ◽  
Highly Active ◽  
Atherogenic Dyslipidaemia

ObjectivesWe examined the dose–response relationship between physical activity (PA) and incidence of cardiovascular disease (CVD) risk factors in adults in Taiwan.MethodsThis study included 1 98 919 participants, aged 18–97 years, free of CVD, cancer and diabetes at baseline (1997–2013), who were followed until 2016. At baseline, participants were classified into five PA levels: inactive’ (0 metabolic equivalent of task (MET)-h/week), ‘lower insufficiently active’ (0.1–3.75 MET-h/week), ‘upper insufficiently active’ (3.75–7.49 MET-h/week), ‘active’ (7.5–14.99 MET-h/week) and ‘highly active’ (≥15 MET-h/week]. CVD risk factors were assessed at baseline and at follow-up by physical examination and laboratory tests. Analyses were performed with Cox regression and adjusted for the main confounders.ResultsDuring a mean follow-up of 6.0±4.5 years (range 0.5–19 years), 20 447 individuals developed obesity, 19 619 hypertension, 21 592 hypercholesterolaemia, 14 164 atherogenic dyslipidaemia, 24 275 metabolic syndrome and 8548 type 2 diabetes. Compared with inactive participants, those in the upper insufficiently active (but not active) category had a lower risk of obesity (HR 0.92; 95% CI 0.88 to 0.95), atherogenic dyslipidaemia (0.96; 0.90 to 0.99), metabolic syndrome (0.95; 0.92 to 0.99) and type 2 diabetes (0.91; 0.86 to 0.97). Only highly active individuals showed a lower incidence of CVD risk factors than their upper insufficiently active counterparts.ConclusionCompared with being inactive, doing half the recommended amount of PA is associated with a lower incidence of several common biological CVD risk factors. Given these benefits, half the recommended amount of PA is an evidence based target for inactive adults.

Abstract 013: High Prevalence and Rapid Increase of Cardiovascular Disease Risk Factors in Youth with Type 2 Diabetes: The TODAY Study Group

Circulation ◽  
2013 ◽  
Vol 127 (suppl_12) ◽  
Author(s):  
Fida Bacha ◽  
Samuel S Gidding ◽  
Sonia Caprio ◽  
Ruth Weinstock ◽  
Jane Lynch ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Glycemic Control ◽  
Hemoglobin A1c ◽  
Male Gender ◽  
High Risk Population ◽  
Cvd Risk Factors ◽  
Cvd Risk

Background The natural history of type 2 diabetes (T2D) in youth appears to differ from that in adults in that almost half of T2D youth in the “Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY)” study had a rapid decline in beta cell function. The rate of change in risk for cardiovascular disease (CVD) in youth with T2D is not known. We tested the hypothesis that CVD risk factors are highly prevalent and rapidly progress over time in youth with T2D using longitudinal assessments of hypertension (HT), microalbuminuria (MA) and dyslipidemia obtained during the TODAY clinical trial of adolescents with recent onset T2D. Methods A cohort of 699 adolescents, aged 10-17 years, <2 years duration of T2D, body mass index (BMI) ≥85th percentile, Hemoglobin A1c (A1c) ≤8% on metformin therapy were randomized to metformin alone, metformin plus rosiglitazone, or metformin plus an intensive lifestyle intervention and followed over an average of 3.9 years. (range 2-6.5 years). Primary outcome was loss of glycemic control. Quarterly BP and annual MA were monitored with initiation and titration of therapy (ACE inhibitor) to maintain BP <130/80 or <95th percentile for age, gender, and height and MA <30 mcg/mg. Statin drugs were begun for LDL cholesterol (LDLC) ≥130 mg/dL or triglycerides ≥300 mg/dL. Change in the prevalence of CVD risk factors was examined accounting for the effect of treatment group, time, glycemic control, gender, and race-ethnicity. Results In this cohort, 319 (45•6%) reached primary glycemic outcome. HTN was observed in 11•6% of subjects at baseline and 33•8% by end of study (average follow-up 3•9 years). MA was found in 6•3% at baseline and rose to 16•6% at study end. Participants with LDLC ≥130 mg/dL or statin use increased from 4.5% to 10.7%. Male gender and higher BMI significantly increased the risk for HTN. Higher levels of hemoglobin A1c correlated with the risk of developing MA and dyslipidemia. Conclusion The prevalence of CVD risk factors increased rapidly among adolescents with T2D regardless of diabetes treatment. The greatest risk for HTN was male gender and higher BMI. The risk for microalbuminuria and worsening of dyslipidemia was related to glycemic control. Measures to address CVD risk are needed early in the disease course in this high risk population.

scholarly journals Genetic risk score for risk prediction of diabetic nephropathy in Han Chinese type 2 diabetes patients

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Li-Na Liao ◽  
Tsai-Chung Li ◽  
Chia-Ing Li ◽  
Chiu-Shong Liu ◽  
Wen-Yuan Lin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Prediction Model ◽  
Risk Prediction ◽  
Genetic Risk Score ◽  
Clinical Risk Factors ◽  
Clinical Risk ◽  
Conventional Risk Factors ◽  
Diabetes Patients

AbstractWe evaluated whether genetic information could offer improvement on risk prediction of diabetic nephropathy (DN) while adding susceptibility variants into a risk prediction model with conventional risk factors in Han Chinese type 2 diabetes patients. A total of 995 (including 246 DN cases) and 519 (including 179 DN cases) type 2 diabetes patients were included in derivation and validation sets, respectively. A genetic risk score (GRS) was constructed with DN susceptibility variants based on findings of our previous genome-wide association study. In derivation set, areas under the receiver operating characteristics (AUROC) curve (95% CI) for model with clinical risk factors only, model with GRS only, and model with clinical risk factors and GRS were 0.75 (0.72–0.78), 0.64 (0.60–0.68), and 0.78 (0.75–0.81), respectively. In external validation sample, AUROC for model combining conventional risk factors and GRS was 0.70 (0.65–0.74). Additionally, the net reclassification improvement was 9.98% (P = 0.001) when the GRS was added to the prediction model of a set of clinical risk factors. This prediction model enabled us to confirm the importance of GRS combined with clinical factors in predicting the risk of DN and enhanced identification of high-risk individuals for appropriate management of DN for intervention.

scholarly journals Knowledge and Perceptions towards Cardiovascular Disease Prevention among Patients with Type 2 Diabetes Mellitus: A Review of Current Assessments and Recommendations

2020 ◽  
Vol 16 ◽  
Author(s):  
Mohamed Hassan Elnaem ◽  
Mahmoud E Elrggal ◽  
Nabeel Syed ◽  
Atta Abbas Naqvi ◽  
Muhammad Abdul Hadi
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Type 2 Diabetes Mellitus ◽  
Original Research ◽  
Knowledge Gaps ◽  
Cvd Risk ◽  
Cvd Prevention

Introduction: Patients with type 2 diabetes mellitus (T2DM) are at significantly higher risk of developing cardiovascular disease (CVD). There is scarcity of literature reviews that describes and summarises T2DM patients' knowledge and perception about CVD prevention. Objectives: To describe and summarise the assessment of knowledge and perceptions about CVD risk and preventive approaches among patients with T2DM. Methods: A scoping review methodology was adopted, and three scientific databases, Google Scholar, Science Direct and PubMed were searched using predefined search terms. A multistage screening process that considered relevancy, publication year (2009-2019), English language, and article type (original research) was followed. We formulated research questions focused on the assessment of levels of knowledge and perceptions of the illness relevant to CVD prevention and the identification of associated patients' characteristics. Results: A total of 16 studies were included. Patients were not confident to identify CVD risk and other clinical consequences that may occur in the prognostic pathway of T2DM. Furthermore, patients were less likely to identify all CV risk factors indicating a lack of understanding of the multi-factorial contribution of CVD risk. Patients' beliefs about medications were correlated with their level of adherence to medications for CVD prevention. Many knowledge gaps were identified, including the basic disease expectations at the time of diagnosis, identification of individuals' CVD risk factors and management aspects. Knowledge and perceptions were affected by patients' demographic characteristics, e.g., educational level, race, age, and area of residence. Conclusion: There are knowledge gaps concerning the understanding of CVD risk among patients with T2DM. The findings necessitate educational initiatives to boost CVD prevention among patients with T2DM. Furthermore, these should be individualised based on patients' characteristics and knowledge gaps, disease duration and estimated CVD risk.

scholarly journals Cardiovascular Disease Related Proteomic Biomarkers of Alcohol Consumption

2020 ◽  
Author(s):  
Xianbang Sun ◽  
Jennifer E. Ho ◽  
He Gao ◽  
Evangelos Evangelou ◽  
Chen Yao ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Alcohol Consumption ◽  
Lower Risk ◽  
Cvd Risk Factors ◽  
Cvd Risk ◽  
Associated Proteins ◽  
Triangular Relationships

AbstractThe relationship between alcohol consumption, circulating proteins, and cardiovascular disease (CVD) risk has not been well studied. We performed association analyses of alcohol consumption with three CVD risk factors and 71 CVD-related circulating proteins measured in 6,745 Framingham Heart Study participants (mean age, 49 years; 53% women). We found that an increase in alcohol consumption was associated with a higher risk of incident hypertension (P=7.2E-3) but a lower risk of incident obesity (P=5.7E-4) and type 2 diabetes (P=1.4E-5) in a 14-year of follow-up. Using independent discovery (n=4,348) and validation (n=2,397) samples, we identified 20 alcohol-associated proteins (FDR<0.05 in discovery and P<0.05/n in validation), with majority (18 of 20 proteins) inversely associated with alcohol consumption. The alcohol-protein associations remained similar after removing heavy drinkers. Four proteins demonstrated consistent triangular relationships, as expected, with alcohol consumption and CVD risk factors. For example, a greater level of APOA1, which was associated with a higher alcohol consumption (P=1.2E-65), was associated with a lower risk of type 2 diabetes (P=3.1E-5). However, several others showed inconsistent triangular relationships, e.g., a greater level of GDF15, which was associated with a lower alcohol consumption (P=1.0E-13), was associated with an increased risk of hypertension (P=2.4E-4). In conclusion, we identified 20 alcohol-associated proteins and demonstrated complex relationships between alcohol consumption, circulating proteins and CVD risk factors. Future studies with integration of more proteomic markers and larger sample size are warranted to unravel the complex relationship between alcohol consumption and CVD risk.

scholarly journals Comparisons of Polyexposure, Polygenic, and Clinical Risk Scores in Risk Prediction of Type 2 Diabetes

Diabetes Care ◽  
2021 ◽  
pp. dc202049
Author(s):  
Yixuan He ◽  
Chirag M. Lakhani ◽  
Danielle Rasooly ◽  
Arjun K. Manrai ◽  
Ioanna Tzoulaki ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Risk Prediction ◽  
Risk Scores ◽  
Clinical Risk

scholarly journals Incidence and risk factors for end-stage kidney disease in patients with clinically manifest vascular disease; results from the UCC-SMART cohort study

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
H.B Oestergaard ◽  
M.C Verhaar ◽  
M.L Bots ◽  
F.W Asselbergs ◽  
G.J De Borst ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Kidney Disease ◽  
Vascular Disease ◽  
Hdl Cholesterol ◽  
Incidence Rates ◽  
Increased Risk ◽  
Kidney Length

Abstract Background Patients with cardiovascular disease are at increased risk of developing chronic kidney disease, potentially leading to end-stage kidney disease (ESKD). On the other hand, kidney disease is associated with an increased risk of adverse cardiovascular outcomes and mortality. Previous studies have identified several risk factors for ESKD in the general population. However, little is known about the impact of these risk factors for ESKD in patients with clinically manifest cardiovascular disease. Purpose The aim of this study was to determine the incidence rates of ESKD in patients with clinically manifest cardiovascular disease and to assess the relation between risk of ESKD and risk factors, including systolic blood pressure (SBP), type 2 diabetes mellitus, estimated glomerular filtration rate (eGFR) and albuminuria (urinary albumin/creatinine ratio (uACR)), body mass index (BMI), dyslipidemia (non-HDL cholesterol), smoking, kidney length and exercise, in this high-risk population. Methods Patients (n=8402) from the ongoing UCC-SMART cohort (1996–2018) with clinically manifest cardiovascular disease were included. Occurrence of ESKD during follow up was defined as kidney transplantation, chronic dialysis or chronic kidney disease stage 5 (persistent eGFR &lt;15 mL/min/1.73m2). Incidence rates for ESKD were determined and stratified according to vascular disease location. Cox proportional hazard models were used to assess the risk of ESKD for every determinant adjusted for potential confounders. Results A total of 65 events of ESKD were observed in 75,282 person-years (median follow-up time 8.6 years, IQR 4.7–12.8 years). The overall incidence rate for ESKD was 0.9 per 1000 person-years and was lower in patients with only cerebrovascular (0.6 per 1000 person-years) or cardiovascular disease (0.6 per 1000 person-years). A higher incidence rate was observed in patients with polyvascular disease (1.8 per 1000 person-years) (Figure 1A). Presence of type 2 diabetes (HR 1.83; 95% CI 1.06–3.16) and higher SBP (HR 1.37; 95% CI 1.24–1.52 per 10 mmHg) were associated with an elevated risk of ESKD. Lower eGFR and higher uACR were associated with a higher risk of ESKD (Figure 1B). Kidney length was inversely associated with risk of ESKD. Smoking, physical exercise, BMI and non-HDL cholesterol were not related to ESKD. Conclusions The incidence of ESKD is higher in patients with polyvascular disease compared to patients with cerebrovascular or cardiovascular disease. Type 2 diabetes, SBP, eGFR, uACR and kidney length are associated with a higher risk of ESKD. In patients with symptomatic vascular disease, secondary cardiovascular prevention focused at these risk factors may also reduce the risk of ESKD. Figure 1 Funding Acknowledgement Type of funding source: Public hospital(s). Main funding source(s): University Medical Center Utrecht

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