Cardiovascular Risk Prediction using JBS3 Tool: A Kerala based Study

Background: The accuracy of Joint British Society calculator3 (JBS3) cardiovascular risk prediction may vary within Indian population, and is not yet studied using south Indian Kerala based population data. Objectives: To evaluate the cardiovascular disease (CV) risk estimation using the traditional CVD risk factors (TRF) in Kerala based population. Methods: This cross sectional study has 977 subjects aged between 30 and 80 years. The traditional CVD risk markers are recorded from the medical archives of clinical locations at Ernakulum district, in Kerala The 10 year risk categories used are low (<7.5%), intermediate (≥7.5% and <20%), and high (≥20%). The lifetime classifications low lifetime (≤39%) and high lifetime (≥40%) are used. The study was evaluated using statistical analysis. Chi-square test was done for dependent and categorical CVD risk variable comparison. Multivariate ordinal logistic regression for 10-year risk model and odds logistic regression analysis for lifetime model was used to identify significant risk variables. Results: The mean age of the study population is 52.56±11.43 years. The risk predictions has 39.1% in low, 25.0% in intermediate, and 35.9% had high 10-year risk. The low lifetime risk had 41.1% and 58.9% is high lifetime risk. Reclassifications to high lifetime are higher from intermediate 10-year risk category. The Hosmer-Lemeshow goodness-of-fit statistics indicates a good model fit. Conclusion: The risk prediction and timely intervention with appropriate therapeutic and lifestyle modification is useful in primary prevention. Avoiding short-term incidences and reclassifications to high lifetime can reduce the CVD mortality rates.

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

10.1101/2020.10.08.20209015 ◽

2020 ◽

Author(s):

K Dziopa ◽

F W Asselbergs ◽

J Gratton ◽

N Chaturvedi ◽

A F Schmidt

Keyword(s):

Type 2 Diabetes ◽

Cardiovascular Risk ◽

Risk Prediction ◽

Risk Scores ◽

Routine Practice ◽

Cvd Risk ◽

C Statistic ◽

Cardiovascular Risk Prediction ◽

Multiple Variables

AbstractObjectiveTo compare performance of general and diabetes specific cardiovascular risk prediction scores in type 2 diabetes patients (T2DM).DesignCohort study.SettingScores were identified through a systematic review and included irrespective of predicted outcome, or inclusion of T2DM patients. Performance was assessed using data from routine practice.ParticipantsA contemporary representative sample of 203,172 UK T2DM patients (age ≥ 18 years).Main outcome measuresCardiovascular disease (CVD i.e., coronary heart disease and stroke) and CVD+ (including atrial fibrillation and heart failure).ResultsWe identified 22 scores: 11 derived in the general population, 9 in only T2DM patients, and 2 that 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)). Overall, neither derivation population, nor original predicted outcome influenced performance. 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, ranging between 0.98 and 1.03. Risk scores performed badly in people with pre-existing CVD (c-statistic ∼0.55). Scores with more predictors did not perform scores better: for CVD+ QRISK3 (19 variables) c-statistic 0.69 (95%CI 0.68;0.69), compared to CHD Basic (8 variables) 0.71 (95%CI 0.70; 0.71).ConclusionsCVD risk prediction scores performed well in T2DM, irrespective of derivation population and of original predicted outcome. Scores performed poorly in patients with established CVD. Complex scores with multiple variables did not outperform simple scores. A simple population specific recalibration markedly improved score performance and is recommended for future use.

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Abstract P195: The Relative Contribution of Systolic Blood Pressure in Cardiovascular Risk Prediction Declines

Circulation ◽

10.1161/circ.135.suppl_1.p195 ◽

2017 ◽

Vol 135 (suppl_1) ◽

Author(s):

Susanne Rospleszcz ◽

Barbara Thorand ◽

Tonia de las Heras Gala ◽

Christa Meisinger ◽

Rolf Holle ◽

...

Keyword(s):

Risk Factors ◽

Blood Pressure ◽

Cardiovascular Risk ◽

Risk Prediction ◽

Performance Measures ◽

Population Attributable Risk ◽

Attributable Risk ◽

Cvd Risk ◽

Relative Contribution ◽

Cardiovascular Risk Prediction

Background: The Framingham Risk Score (FRS) is an established tool for the prediction of cardiovascular disease (CVD) risk. The established CVD risk factors age, HDL cholesterol, total cholesterol, systolic blood pressure (SBP), antihypertensive treatment, diabetes mellitus and smoking are used in the calculation of the FRS. The prevalence and distribution of these risk factors in the population have changed within the last decades and especially average levels of SBP have declined. However, the impact of this change on the risk prediction performance of the FRS has not been investigated. Hypothesis: We assessed the hypothesis that the relative contribution of SBP to CVD risk prediction within the FRS framework has changed from 1985 to 2000. Methods: We used N = 11 760 participants aged 30 - 65 years from four prospective population-based cohort studies enrolled in Southern Germany in 1985, 1990, 1995, and 2000. CVD risk was calculated by recalibrated equations of the original FRS. Predicted CVD risks using the actual SBP values were compared to predicted CVD risks using optimal (SBP < 120 mmHg) values for each participant. We assessed the relative contribution of SBP with three performance measures: First, the median difference in predicted risks with actual and optimal SBP, second, the relative positive predictive value of the FRS using actual compared to optimal SBP values and third, the population attributable risk fraction of SBP using Levin’s formula. Results: CVD events occurred in 6.3% of male participants in 1985 and 6.2% in 2000; in women, event rates were 2.4% and 2.3%, respectively. Mean SBP levels decreased from 134 mmHg (Standard Deviation: 17 mmHg) to 132 (SD: 17) mmHg in men and from 127 (SD: 19) mmHg to 121 (SD: 18) mmHg in women. The difference in median predicted risk declined from 1.21 [Interquartile range 0.52, 3.38] in 1985 to 0.93 [0.35, 2.44] in 2000 in men and from 0.26 [-0.05, 1.45] to -0.07 [-0.19, 0.89] in women. The relative positive predictive value dropped from 0.88 to 0.73 in men and from 0.61 to 0.53 in women. The population attributable risk fraction of SBP decreased from 70.2% (95% CI: 42.1, 89.6) to 29.71% (-6.4, 64.7) in men and from 85.7% (62.9, 93.1) to 57.9% (28.0, 82.0) in women. Given the results from 1990 and 1995, the declining trend was nonlinear for all three performance measures. Conclusion: In conclusion, the relative contribution of blood pressure to cardiovascular risk prediction has decreased within the last decades. This affects the future development of CVD risk prediction methods which will have to consider the changing relative importance of SBP. Furthermore, this might also influence public health policies focusing on the management of SBP and hypertension in order to effectively prevent CVD.

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Improvement of cardiovascular risk prediction using coronary imaging: subclinical atherosclerosis: the memory of lifetime risk factor exposure

European Heart Journal ◽

10.1093/eurheartj/ehs076 ◽

2012 ◽

Vol 33 (10) ◽

pp. 1201-1213 ◽

Cited By ~ 70

Author(s):

R. Erbel ◽

M. Budoff

Keyword(s):

Risk Factor ◽

Cardiovascular Risk ◽

Risk Prediction ◽

Subclinical Atherosclerosis ◽

Lifetime Risk ◽

Coronary Imaging ◽

Cardiovascular Risk Prediction

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

European Heart Journal ◽

10.1093/eurheartj/ehab724.2458 ◽

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

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