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      General Practitioners’ Decision Making about Primary Prevention of Cardiovascular Disease in Older Adults: A Qualitative Study

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          Abstract

          Background

          Primary cardiovascular disease (CVD) prevention in older people is challenging as they are a diverse group with varying needs, frequent presence of comorbidities, and are more susceptible to treatment harms. Moreover the potential benefits and harms of preventive medication for older people are uncertain. We explored GPs’ decision making about primary CVD prevention in patients aged 75 years and older.

          Method

          25 GPs participated in semi-structured interviews in New South Wales, Australia. Transcribed audio-recordings were thematically coded and Framework Analysis was used.

          Results

          Analysis identified factors that are likely to contribute to variation in the management of CVD risk in older people. Some GPs based CVD prevention on guidelines regardless of patient age. Others tailored management based on factors such as perceptions of prevention in older age, knowledge of limited evidence, comorbidities, polypharmacy, frailty, and life expectancy. GPs were more confident about: 1) medication and lifestyle change for fit/healthy older patients, and 2) stopping or avoiding medication for frail/nursing home patients. Decision making for older patients outside of these categories was less clear.

          Conclusion

          Older patients receive different care depending on their GP’s perceptions of ageing and CVD prevention, and their knowledge of available evidence. GPs consider CVD prevention for older patients challenging and would welcome more guidance in this area.

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          Most cited references31

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          General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

          Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions ("general CVD" algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P<0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non-laboratory-based predictors. A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care.
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            Potential pitfalls of disease-specific guidelines for patients with multiple conditions.

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              Safety and benefit of discontinuing statin therapy in the setting of advanced, life-limiting illness: a randomized clinical trial.

              For patients with limited prognosis, some medication risks may outweigh the benefits, particularly when benefits take years to accrue; statins are one example. Data are lacking regarding the risks and benefits of discontinuing statin therapy for patients with limited life expectancy.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                13 January 2017
                2017
                : 12
                : 1
                : e0170228
                Affiliations
                [1 ]Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
                [2 ]Centre for Medical Psychology and Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, New South Wales, Australia
                [3 ]Faculty of Health Sciences and Medicine, Bond University, Robina, Queensland, Australia
                [4 ]Centre for Education and Research on Ageing (CERA), Ageing and Alzheimer’s Institute, Concord Hospital, The University of Sydney, Sydney, New South Wales, Australia
                Vanderbilt University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: JJ CB LI JD PG KM.

                • Formal analysis: JJ SM.

                • Funding acquisition: JJ LI JD PG KM.

                • Investigation: JJ SM.

                • Methodology: JJ CB LI JD PG KM.

                • Project administration: JJ.

                • Writing – original draft: JJ.

                • Writing – review & editing: JJ SM CB LI JD PG KB VN KM.

                Author information
                http://orcid.org/0000-0001-6384-1745
                Article
                PONE-D-16-30644
                10.1371/journal.pone.0170228
                5234831
                28085944
                a9bb4753-1453-41ea-8079-0181a73e00c6
                © 2017 Jansen et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 1 August 2016
                : 30 December 2016
                Page count
                Figures: 0, Tables: 3, Pages: 13
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award ID: 633003
                Funded by: funder-id http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award ID: 511217
                The study was funded by the National Health and Medical Research Council (NHMRC), through grants awarded to the Screening and Test Evaluation Program (no. 633003) and Bond University (no. 511217). CB was supported by an Australian Postgraduate Award. JJ and KM were supported by NHMRC fellowships. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                People and Places
                Population Groupings
                Age Groups
                Elderly
                Medicine and Health Sciences
                Cardiovascular Medicine
                Cardiovascular Diseases
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognitive Psychology
                Decision Making
                Biology and Life Sciences
                Psychology
                Cognitive Psychology
                Decision Making
                Social Sciences
                Psychology
                Cognitive Psychology
                Decision Making
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognition
                Decision Making
                People and Places
                Demography
                Life Expectancy
                Medicine and Health Sciences
                Public and Occupational Health
                Life Expectancy
                Medicine and Health Sciences
                Geriatrics
                Frailty
                Engineering and Technology
                Management Engineering
                Risk Management
                Medicine and Health Sciences
                Geriatrics
                Medicine and Health Sciences
                Health Care
                Quality of Life
                Custom metadata
                Data underlying our findings cannot be made publicly available for ethical reasons; public availability would compromise our doctors’ privacy. Data requests may be sent to the corresponding author at jesse.jansen@ 123456sydney.edu.au .

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