scholarly journals Shared Decision Making Regarding Aspirin in Primary Prevention of Cardiovascular Disease

JAMA ◽  
2016 ◽  
Vol 316 (21) ◽  
pp. 2276
Author(s):  
Steven D. Stovitz ◽  
David J. Satin ◽  
Ian Shrier
Keyword(s):  
Cardiovascular Disease ◽  
Decision Making ◽  
Primary Prevention ◽  
Shared Decision Making ◽  
Shared Decision ◽  
Prevention Of Cardiovascular Disease

scholarly journals Clinical Prediction Models for Primary Prevention of Cardiovascular Disease: Validity in Independent Cohorts

2021 ◽  
Author(s):  
Gaurav Gulati ◽  
Riley J Brazil ◽  
Jason Nelson ◽  
David van Klaveren ◽  
Christine M. Lundquist ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Decision Making ◽  
Primary Prevention ◽  
Prediction Models ◽  
Model Updating ◽  
Clinical Prediction ◽  
Net Benefit ◽  
Clinical Prediction Models ◽  
C Statistic ◽  
Prevention Of Cardiovascular Disease

AbstractBackgroundClinical prediction models (CPMs) are used to inform treatment decisions for the primary prevention of cardiovascular disease. We aimed to assess the performance of such CPMs in fully independent cohorts.Methods and Results63 models predicting outcomes for patients at risk of cardiovascular disease from the Tufts PACE CPM Registry were selected for external validation on publicly available data from up to 4 broadly inclusive primary prevention clinical trials. For each CPM-trial pair, we assessed model discrimination, calibration, and net benefit. Results were stratified based on the relatedness of derivation and validation cohorts, and net benefit was reassessed after updating model intercept, slope, or complete re-estimation. The median c statistic of the CPMs decreased from 0.77 (IQR 0.72-0.78) in the derivation cohorts to 0.63 (IQR 0.58-0.66) when externally validated. The validation c-statistic was higher when derivation and validation cohorts were considered related than when they were distantly related (0.67 vs 0.60, p < 0.001). The calibration slope was also higher in related cohorts than distantly related cohorts (0.69 vs 0.58, p < 0.001). Net benefit analysis suggested substantial likelihood of harm when models were externally applied, but this likelihood decreased after model updating.ConclusionsDiscrimination and calibration decrease significantly when CPMs for primary prevention of cardiovascular disease are tested in external populations, particularly when the population is only distantly related to the derivation population. Poorly calibrated predictions lead to poor decision making. Model updating can reduce the likelihood of harmful decision making, and is needed to realize the full potential of risk-based decision making in new settings.

Statins for primary prevention: what is the regulator’s role?

2020 ◽  
pp. bmjebm-2019-111321 ◽  
Author(s):  
Tom Jefferson ◽  
Maryanne Demasi ◽  
Peter Doshi
Keyword(s):  
Cardiovascular Disease ◽  
Decision Making ◽  
Primary Prevention ◽  
General Public ◽  
Trial Data ◽  
Central Location ◽  
Decision Making Processes ◽  
Drug Approvals ◽  
Prevention Of Cardiovascular Disease

Globally, drug regulators have approved statins for the prevention of cardiovascular disease (CVD), although their use in primary prevention has been controversial. A highly publicised debate has ensued over whether the benefits outweigh the harms. Drug regulators, which are legally required to make independent judgements on drug approvals, have remained silent during the debate. Our aim was to navigate the decision-making processes of European drug regulators and ultimately request the data upon which statins were approved. Our findings revealed a system of fragmented regulation in which many countries licensed statins but did not analyse the data themselves. There is no easily accessible archive containing information about the licensing approval of statins or a central location for holding the trial data. This is an unsustainable model and serves neither the general public, nor researchers.

scholarly journals Shared Decision Making for Athletes with Cardiovascular Disease

2019 ◽  
Vol 18 (3) ◽  
pp. 76-81 ◽  
Author(s):  
Aaron L. Baggish ◽  
Michael J. Ackerman ◽  
Margot Putukian ◽  
Rachel Lampert
Keyword(s):  
Cardiovascular Disease ◽  
Decision Making ◽  
Shared Decision Making ◽  
Shared Decision

scholarly journals Online decision aids for primary cardiovascular disease prevention: systematic search, evaluation of quality and suitability for low health literacy patients

BMJ Open ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. e025173 ◽  
Author(s):  
Carissa Bonner ◽  
Pinika Patel ◽  
Michael Anthony Fajardo ◽  
Ruixuan Zhuang ◽  
Lyndal Trevena
Keyword(s):  
Cardiovascular Disease ◽  
Decision Making ◽  
Health Literacy ◽  
Shared Decision Making ◽  
Decision Aids ◽  
Shared Decision ◽  
Low Health Literacy ◽  
Lower Health ◽  
Cvd Prevention ◽  
Lower Health Literacy

ObjectivesRecent guideline changes for cardiovascular disease (CVD) prevention medication have resulted in calls to implement shared decision-making rather than arbitrary treatment thresholds. Less attention has been paid to existing tools that could facilitate this. Decision aids are well-established tools that enable shared decision-making and have been shown to improve CVD prevention adherence. However, it is unknown how many CVD decision aids are publicly available for patients online, what their quality is like and whether they are suitable for patients with lower health literacy, for whom the burden of CVD is greatest. This study aimed to identify and evaluate all English language, publicly available online CVD prevention decision aids.DesignSystematic review of public websites in August to November 2016 using an environmental scan methodology, with updated evaluation in April 2018. The decision aids were evaluated based on: (1) suitability for low health literacy populations (understandability, actionability and readability); and (2) International Patient Decision Aids Standards (IPDAS).Primary outcome measuresUnderstandability and actionability using the validated Patient Education Materials Assessment Tool for Printed Materials (PEMAT-P scale), readability using Gunning–Fog and Flesch–Kincaid indices and quality using IPDAS V.3 and V.4.ResultsA total of 25 unique decision aids were identified. On the PEMAT-P scale, the decision aids scored well on understandability (mean 87%) but not on actionability (mean 61%). Readability was also higher than recommended levels (mean Gunning–Fog index=10.1; suitable for grade 10 students). Four decision aids met criteria to be considered a decision aid (ie, met IPDAS qualifying criteria) and one sufficiently minimised major bias (ie, met IPDAS certification criteria).ConclusionsPublicly available CVD prevention decision aids are not suitable for low literacy populations and only one met international standards for certification. Given that patients with lower health literacy are at increased risk of CVD, this urgently needs to be addressed.

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