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Birhanu MM, Zengin A, Evans RG, Joshi R, Kalyanram K, Kartik K, Danaei G, Barr E, Riddell MA, Suresh O, Srikanth VK, Arabshahi S, Thomas N, Thrift AG. Comparison of the performance of cardiovascular risk prediction tools in rural India: the Rishi Valley Prospective Cohort Study. Eur J Prev Cardiol 2024; 31:723-731. [PMID: 38149975 DOI: 10.1093/eurjpc/zwad404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 12/07/2023] [Accepted: 12/20/2023] [Indexed: 12/28/2023]
Abstract
AIMS We compared the performance of cardiovascular risk prediction tools in rural India. METHODS AND RESULTS We applied the World Health Organization Risk Score (WHO-RS) tools, Australian Risk Score (ARS), and Global risk (Globorisk) prediction tools to participants aged 40-74 years, without prior cardiovascular disease, in the Rishi Valley Prospective Cohort Study, Andhra Pradesh, India. Cardiovascular events during the 5-year follow-up period were identified by verbal autopsy (fatal events) or self-report (non-fatal events). The predictive performance of each tool was assessed by discrimination and calibration. Sensitivity and specificity of each tool for identifying high-risk individuals were assessed using a risk score cut-off of 10% alone or this 10% cut-off plus clinical risk criteria of diabetes in those aged >60 years, high blood pressure, or high cholesterol. Among 2333 participants (10 731 person-years of follow-up), 102 participants developed a cardiovascular event. The 5-year observed risk was 4.4% (95% confidence interval: 3.6-5.3). The WHO-RS tools underestimated cardiovascular risk but the ARS overestimated risk, particularly in men. Both the laboratory-based (C-statistic: 0.68 and χ2: 26.5, P = 0.003) and non-laboratory-based (C-statistic: 0.69 and χ2: 20.29, P = 0.003) Globorisk tools showed relatively good discrimination and agreement. Addition of clinical criteria to a 10% risk score cut-off improved the diagnostic accuracy of all tools. CONCLUSION Cardiovascular risk prediction tools performed disparately in a setting of disadvantage in rural India, with the Globorisk performing best. Addition of clinical criteria to a 10% risk score cut-off aids assessment of risk of a cardiovascular event in rural India. LAY SUMMARY In a cohort of people without prior cardiovascular disease, tools used to predict the risk of cardiovascular events varied widely in their ability to accurately predict who would develop a cardiovascular event.The Globorisk, and to a lesser extent the ARS, tools could be appropriate for this setting in rural India.Adding clinical criteria, such as sustained high blood pressure, to a cut-off of 10% risk of a cardiovascular event within 5 years could improve identification of individuals who should be monitored closely and provided with appropriate preventive medications.
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Affiliation(s)
- Mulugeta Molla Birhanu
- Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Level 5, Block E, Monash Medical Centre, 246 Clayton Road, Melbourne, Victoria 3168, Australia
| | - Ayse Zengin
- Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Level 5, Block E, Monash Medical Centre, 246 Clayton Road, Melbourne, Victoria 3168, Australia
| | - Roger G Evans
- Cardiovascular Disease Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Melbourne, Victoria, Australia
- Pre-clinical Critical Care Unit, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Rohina Joshi
- Faculty of Medicine, School of Population Health, University of New South Wales, Sydney, Australia
- George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia
- George Institute for Global Health, New Delhi, India
| | - Kartik Kalyanram
- Rishi Valley Rural Health Centre, Madanapalle, Chittoor District, Andhra Pradesh, India
| | - Kamakshi Kartik
- Rishi Valley Rural Health Centre, Madanapalle, Chittoor District, Andhra Pradesh, India
| | - Goodarz Danaei
- Department of Global Health and Population and Epidemiology, Harvard University T H Chan School of Public Health, Boston, MA, USA
| | - Elizabeth Barr
- Menzies School of Health Research, Charles Darwin University, Darwin, Northern Territory, Australia
- Clinical Diabetes and Epidemiology, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Michaela A Riddell
- Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Level 5, Block E, Monash Medical Centre, 246 Clayton Road, Melbourne, Victoria 3168, Australia
| | - Oduru Suresh
- Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Level 5, Block E, Monash Medical Centre, 246 Clayton Road, Melbourne, Victoria 3168, Australia
- Rishi Valley Rural Health Centre, Madanapalle, Chittoor District, Andhra Pradesh, India
| | - Velandai K Srikanth
- Peninsula Clinical School, Central Clinical School, Monash University, Frankston, Victoria, Australia
- National Centre for Healthy Ageing, Monash University and Peninsual Health, Melbourne, Victoria, Australia
| | - Simin Arabshahi
- Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Level 5, Block E, Monash Medical Centre, 246 Clayton Road, Melbourne, Victoria 3168, Australia
| | - Nihal Thomas
- Department of Endocrinology, Diabetes and Metabolism, Christian Medical College, Vellore, Tamil Nadu, India
| | - Amanda G Thrift
- Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Level 5, Block E, Monash Medical Centre, 246 Clayton Road, Melbourne, Victoria 3168, Australia
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Morgan T, Ralston A, Davey A, Holliday EG, Nelson M, Fielding A, van Driel M, Tapley A, Moad D, Ball J, Presser J, Spike N, Magin P. Absolute cardiovascular risk assessment by Australian early-career general practitioners: a cross-sectional study. Fam Med Community Health 2023; 11:e002251. [PMID: 37604595 PMCID: PMC10445344 DOI: 10.1136/fmch-2023-002251] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/23/2023] Open
Abstract
OBJECTIVE To determine the prevalence and associations of general practice registrars' performing absolute cardio-vascular risk (ACVR) assessment (ACVRa). DESIGN A cross-sectional study employing data (2017-2018) from the Registrar Clinical Encounters in Training project, an ongoing inception cohort study of Australian GP registrars. The outcome measure was whether an ACVRa was performed. Analyses employed univariable and multivariable regression. Analysis was conducted for all patient problems/diagnoses, then for an 'at-risk' population (specific problems/diagnoses for which ACVRa is indicated). SETTING Three GP regional training organisations (RTOs) across three Australian states. PARTICIPANTS GP registrars training within participating RTOs. RESULTS 1003 registrars (response rate 96.8%) recorded details of 69 105 problems either with Aboriginal and/or Torres Strait patients aged 35 years and older or with non-Indigenous patients aged 45 years and older. Of these problems/diagnoses, 1721 (2.5% (95% CI 2.4% to 2.6%)) involved an ACVRa. An ACVRa was 'plausibly indicated' in 10 384 problems/diagnoses. Of these, 1228 (11.8% (95% CI 11.2% to 12.4%)) involved ACVRa. For 'all problems/diagnoses', on multivariable analysis female gender was associated with reduced odds of ACVRa (OR 0.61 (95% CI 0.54 to 0.68)). There was some evidence for Aboriginal and/or Torres Strait Islander people being more likely to receive ACVRa (OR 1.40 (95% CI 0.94 to 2.08), p=0.10). There were associations with variables related to continuity of care, with reduced odds of ACVRa: if the patient was new to the registrar (OR 0.65 (95% CI 0.57 to 0.75)), new to the practice (OR 0.24 (95% CI 0.15 to 0.38)) or the problem was new (OR 0.68 (95% CI 0.59 to 0.78)); and increased odds if personal follow-up was organised (OR 1.43 (95% CI 1.24 to 1.66)). For 'ACVRa indicated' problems/diagnoses, findings were similar to those for 'all problems/diagnoses'. Association with Aboriginal and/or Torres Strait Islander status, however, was significant at p<0.05 (OR 1.60 (95% CI 1.04 to 2.46)) and association with female gender was attenuated (OR 0.88 (95% CI 0.77 to 1.01)). CONCLUSION Continuity of care is associated with registrars assessing ACVR, reinforcing the importance of care continuity in general practice. Registrars' assessment of an individual patient's ACVR is targeted to patients with individual risk factors, but this may entail ACVRa underutilisation in female patients and younger age groups.
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Affiliation(s)
- Toby Morgan
- School of Population Health, University of New South Wales Faculty of Medicine, Kensington, New South Wales, Australia
| | - Anna Ralston
- NSW & ACT Research and Evaluation Unit, GP Synergy Ltd - Newcastle, Mayfield West, New South Wales, Australia
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Andrew Davey
- NSW & ACT Research and Evaluation Unit, GP Synergy Ltd - Newcastle, Mayfield West, New South Wales, Australia
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Elizabeth G Holliday
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Mark Nelson
- University of Tasmania Menzies Institute for Medical Research, Hobart, Tasmania, Australia
- University of Tasmania School of Medicine, Hobart, Tasmania, Australia
| | - Alison Fielding
- NSW & ACT Research and Evaluation Unit, GP Synergy Ltd - Newcastle, Mayfield West, New South Wales, Australia
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Mieke van Driel
- General Practice Clinical Unit, The University of Queensland Faculty of Medicine, Brisbane, Queensland, Australia
| | - Amanda Tapley
- NSW & ACT Research and Evaluation Unit, GP Synergy Ltd - Newcastle, Mayfield West, New South Wales, Australia
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Dominica Moad
- NSW & ACT Research and Evaluation Unit, GP Synergy Ltd - Newcastle, Mayfield West, New South Wales, Australia
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Jean Ball
- Clinical Research Design and Statistical Support Unit (CReDITSS), The University of Newcastle Hunter Medical Research Institute, New Lambton, New South Wales, Australia
| | - Jennifer Presser
- University of Tasmania School of Medicine, Hobart, Tasmania, Australia
| | - Neil Spike
- Department of General Practice and Primary Health Care, The University of Melbourne, Carlton, Victoria, Australia
- Monash University Faculty of Medicine Nursing and Health Sciences, Clayton, Victoria, Australia
| | - Parker Magin
- NSW & ACT Research and Evaluation Unit, GP Synergy Ltd - Newcastle, Mayfield West, New South Wales, Australia
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
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Predicted cardiovascular disease risk and prescribing of antihypertensive therapy among patients with hypertension in Australia using MedicineInsight. J Hum Hypertens 2022; 37:370-378. [PMID: 35501358 PMCID: PMC10156591 DOI: 10.1038/s41371-022-00691-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 03/30/2022] [Accepted: 04/07/2022] [Indexed: 11/09/2022]
Abstract
Hypertension guidelines recommend that absolute cardiovascular disease (CVD) risk guide the management of hypertensive patients. This study aimed to assess the proportion of patients with diagnosed hypertension with sufficient data to calculate absolute CVD risk and determine whether CVD risk is associated with prescribing of antihypertensive therapies. This was a cross-sectional study using a large national database of electronic medical records of patients attending general practice in 2018 (MedicineInsight). Of 571,492 patients aged 45-74 years without a history of CVD, 251,733 [40.6% (95% CI: 39.8-41.2)] had a recorded hypertension diagnosis. The proportion of patients with sufficient recorded data available to calculate CVD risk was higher for patients diagnosed with hypertension [51.0% (95% CI: 48.0-53.9)] than for patients without a diagnosis of hypertension [38.7% (95% CI: 36.5-41.0)]. Of those patients with sufficient data to calculate CVD risk, 29.3% (95% CI: 28.1-30.6) were at high risk clinically, 6.0% (95% CI: 5.8-6.3) were at high risk based on their CVD risk score, 12.8% (95% CI: 12.5-13.2) at moderate risk and 51.8% (95% CI: 50.8-52.9) at low risk. The overall prevalence of antihypertensive therapy was 60.9% (95% CI: 59.3-62.5). Prescribing was slightly lower in patients at high risk based on their CVD risk score [57.4% (95% CI: 55.4-59.4)] compared with those at low [63.3% (95% CI: 61.9-64.8)] or moderate risk [61.8% (95% CI: 60.2-63.4)] or at high risk clinically [64.1% (95% CI: 61.9-66.3)]. Guideline adherence is suboptimal, and many patients miss out on treatments that may prevent future CVD events.
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Chapman N, McWhirter RE, Schultz MG, Ezzy D, Nelson MR, Sharman JE. General practitioner perceptions of assessment and reporting of absolute cardiovascular disease risk via pathology services: a qualitative study. Fam Pract 2021; 38:173-180. [PMID: 33002138 DOI: 10.1093/fampra/cmaa107] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Guidelines for cardiovascular disease (CVD) prevention recommend assessment of absolute CVD risk to guide clinical management. Despite this, use among general practitioners (GPs) remains limited. OBJECTIVE Pathology services may provide an appropriate setting to assess and report absolute CVD risk in patients attending for cholesterol measurement. This study aimed to explore GPs perceptions of such a service. METHODS A focus group and semi-structured interviews were conducted with GPs (n = 18) in Tasmania, Australia, to identify perceptions of assessment and reporting of absolute CVD risk via pathology services. An example pathology report including absolute CVD risk was provided and discussed. Audio-recordings were transcribed and thematically coded by two researchers. RESULTS Almost all GPs identified that absolute CVD risk assessed and reported via pathology services could address deficits in practice. First, by reducing the number of appointments required to collect risk factors. Second, by providing a systematic (rather than opportunistic) approach for assessment of absolute CVD risk. Third, by reducing misclassification of patient CVD risk caused by overreliance on clinical intuition. All GPs reported they would order absolute CVD risk when issuing a cholesterol referral if such a service was offered. GPs recommended improving the service by providing information on methods used to measure risk factors on the pathology report. CONCLUSIONS Absolute CVD risk assessed and reported via pathology services may address challenges of screening CVD risk experienced by GPs in practice and encourage dedicated follow-up care for CVD prevention.
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Affiliation(s)
- Niamh Chapman
- Menzies Institute for Medical Research, College of Health and Medicine
| | - Rebekah E McWhirter
- Menzies Institute for Medical Research, College of Health and Medicine.,Centre for Law and Genetics, Faculty of Law
| | - Martin G Schultz
- Menzies Institute for Medical Research, College of Health and Medicine
| | - Douglas Ezzy
- School of Social Sciences, University of Tasmania, Hobart, Australia
| | - Mark R Nelson
- Menzies Institute for Medical Research, College of Health and Medicine
| | - James E Sharman
- Menzies Institute for Medical Research, College of Health and Medicine
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5
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Trevena LJ, Bonner C, Okan Y, Peters E, Gaissmaier W, Han PKJ, Ozanne E, Timmermans D, Zikmund-Fisher BJ. Current Challenges When Using Numbers in Patient Decision Aids: Advanced Concepts. Med Decis Making 2021; 41:834-847. [PMID: 33660535 DOI: 10.1177/0272989x21996342] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
BACKGROUND Decision aid developers have to convey complex task-specific numeric information in a way that minimizes bias and promotes understanding of the options available within a particular decision. Whereas our companion paper summarizes fundamental issues, this article focuses on more complex, task-specific aspects of presenting numeric information in patient decision aids. METHODS As part of the International Patient Decision Aids Standards third evidence update, we gathered an expert panel of 9 international experts who revised and expanded the topics covered in the 2013 review working in groups of 2 to 3 to update the evidence, based on their expertise and targeted searches of the literature. The full panel then reviewed and provided additional revisions, reaching consensus on the final version. RESULTS Five of the 10 topics addressed more complex task-specific issues. We found strong evidence for using independent event rates and/or incremental absolute risk differences for the effect size of test and screening outcomes. Simple visual formats can help to reduce common judgment biases and enhance comprehension but can be misleading if not well designed. Graph literacy can moderate the effectiveness of visual formats and hence should be considered in tool design. There is less evidence supporting the inclusion of personalized and interactive risk estimates. DISCUSSION More complex numeric information. such as the size of the benefits and harms for decision options, can be better understood by using incremental absolute risk differences alongside well-designed visual formats that consider the graph literacy of the intended audience. More research is needed into when and how to use personalized and/or interactive risk estimates because their complexity and accessibility may affect their feasibility in clinical practice.
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Affiliation(s)
- Lyndal J Trevena
- Faculty of Medicine and Health, School of Public Health, The University of Sydney, Sydney, NSW, Australia.,Ask Share Know NHMRC Centre for Research Excellence, The University of Sydney, Australia
| | - Carissa Bonner
- Faculty of Medicine and Health, School of Public Health, The University of Sydney, Sydney, NSW, Australia.,Ask Share Know NHMRC Centre for Research Excellence, The University of Sydney, Australia
| | - Yasmina Okan
- Centre for Decision Research, University of Leeds, Leeds, UK
| | | | | | - Paul K J Han
- Center for Outcomes Research and Evaluation, Maine Medical Center Research Institute, Portland, ME, USA.,School of Medicine, Tufts University, Medford, MA, USA
| | | | - Danielle Timmermans
- Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, North Holland, The Netherlands
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Factors predicting statin prescribing for primary prevention: a historical cohort study. Br J Gen Pract 2021; 71:e219-e225. [PMID: 33558331 PMCID: PMC7888748 DOI: 10.3399/bjgp20x714065] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Accepted: 08/17/2020] [Indexed: 11/24/2022] Open
Abstract
Background Initiation of statins for the primary prevention of cardiovascular disease (CVD) should be based on CVD risk estimates, but their use is suboptimal. Aim To investigate the factors influencing statin prescribing when clinicians code and do not code estimated CVD risk (QRISK2). Design and setting A historical cohort of patients who had lipid tests in a database (IQVIA Medical Research Data) of UK primary care records. Method The cohort comprised 686 560 entries (lipid test results) between 2012 and 2016 from 383 416 statin-naive patients without previous CVD. Coded QRISK2 scores were extracted, with variables used in calculating QRISK2 and factors that might influence statin prescribing. If a QRISK2 score was not coded, it was calculated post hoc. The outcome was initiation of a statin within 60 days of the lipid test result. Results Of the entries, 146 693 (21.4%) had a coded QRISK2 score. Statins were initiated in 6.6% (95% confidence interval [CI] = 6.4% to 6.7%) of those with coded and 4.1% (95% CI = 4.0% to 4.1%) of uncoded QRISK2 (P<0.001). Statin initiations were consistent with National Institute for Health and Care Excellence guideline recommendations in 85.0% (95% CI = 84.2% to 85.8%) of coded and 44.2% (95% CI = 43.5% to 44.9%) of uncoded QRISK2 groups (P<0.001). When coded, QRISK2 score was the main predictor of statin initiation, but total cholesterol was the main predictor when a QRISK2 score was not coded. Conclusion When a QRISK2 score is coded, prescribing is more consistent with guidelines. With no QRISK2 score, prescribing is mainly based on total cholesterol. Using QRISK2 is associated with statin prescribing that is more likely to benefit patients. Promoting the routine CVD risk estimation is essential to optimise decision making.
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Chapman N, Fonseca R, Murfett L, Beazley K, McWhirter RE, Schultz MG, Nelson MR, Sharman JE. Integration of absolute cardiovascular disease risk assessment into routine blood cholesterol testing at pathology services. Fam Pract 2020; 37:675-681. [PMID: 32296818 DOI: 10.1093/fampra/cmaa034] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Absolute cardiovascular disease (CVD) risk assessment is recommended for primary prevention of CVD, yet uptake in general practice is limited. Cholesterol requests at pathology services provide an opportunity to improve uptake by integrating absolute CVD risk assessment with this service. OBJECTIVE This study aimed to assess the feasibility of such an additional service. METHODS Two-hundred and ninety-nine patients (45-74 years) referred to pathology services for blood cholesterol had measurement of all variables required to determine absolute CVD risk according to Framingham calculator (blood pressure, age, sex, smoking and diabetes status via self-report). Data were recorded via computer-based application. The absolute risk score was communicated via the report sent to the referring medical practitioner as per usual practice. Evaluation questionnaires were completed immediately post visit and at 1-, 3- and 6-month follow-up via telephone (n = 262). RESULTS Absolute CVD risk reports were issued for 90% of patients. Most patients (95%) reported that the length of time for the pathology service assessment was acceptable, and 91% that the self-directed computer-based application was easy to use. Seventy-eight per cent reported a preference for pathology services to conduct absolute CVD risk assessment. Only 2% preferred a medical practitioner. Of follow-up patients, 202 (75%) had a consultation with a medical practitioner, during which, aspects of CVD risk prevention were discussed (cholesterol and blood pressure 74% and 69% of the time, respectively). CONCLUSIONS Measurement of absolute CVD risk in pathology services is feasible, highly acceptable among middle-to-older adults and may increase uptake of guideline-directed care in general practice.
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Affiliation(s)
- Niamh Chapman
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
| | - Ricardo Fonseca
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
| | | | | | - Rebekah E McWhirter
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia.,Centre for Law and Genetics, Faculty of Law, University of Tasmania, Hobart, Australia
| | - Martin G Schultz
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
| | - Mark R Nelson
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
| | - James E Sharman
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
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Whelton PK, Carey RM, Aronow WS, Casey DE, Collins KJ, Dennison Himmelfarb C, DePalma SM, Gidding S, Jamerson KA, Jones DW, MacLaughlin EJ, Muntner P, Ovbiagele B, Smith SC, Spencer CC, Stafford RS, Taler SJ, Thomas RJ, Williams KA, Williamson JD, Wright JT. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 2019; 138:e426-e483. [PMID: 30354655 DOI: 10.1161/cir.0000000000000597] [Citation(s) in RCA: 360] [Impact Index Per Article: 72.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Affiliation(s)
- Paul K Whelton
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Robert M Carey
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Wilbert S Aronow
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Donald E Casey
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Karen J Collins
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Cheryl Dennison Himmelfarb
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Sondra M DePalma
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Samuel Gidding
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Kenneth A Jamerson
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Daniel W Jones
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Eric J MacLaughlin
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Paul Muntner
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Bruce Ovbiagele
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Sidney C Smith
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Crystal C Spencer
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Randall S Stafford
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Sandra J Taler
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Randal J Thomas
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Kim A Williams
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Jeff D Williamson
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Jackson T Wright
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
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Whelton PK, Carey RM, Aronow WS, Casey DE, Collins KJ, Dennison Himmelfarb C, DePalma SM, Gidding S, Jamerson KA, Jones DW, MacLaughlin EJ, Muntner P, Ovbiagele B, Smith SC, Spencer CC, Stafford RS, Taler SJ, Thomas RJ, Williams KA, Williamson JD, Wright JT. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 2019; 138:e484-e594. [PMID: 30354654 DOI: 10.1161/cir.0000000000000596] [Citation(s) in RCA: 210] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Paul K Whelton
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Robert M Carey
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Wilbert S Aronow
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Donald E Casey
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Karen J Collins
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Cheryl Dennison Himmelfarb
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Sondra M DePalma
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Samuel Gidding
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Kenneth A Jamerson
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Daniel W Jones
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Eric J MacLaughlin
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Paul Muntner
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Bruce Ovbiagele
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Sidney C Smith
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Crystal C Spencer
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Randall S Stafford
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Sandra J Taler
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Randal J Thomas
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Kim A Williams
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Jeff D Williamson
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
| | - Jackson T Wright
- American Society for Preventive Cardiology Representative. †ACC/AHA Representative. ‡Lay Volunteer/Patient Representative. §Preventive Cardiovascular Nurses Association Representative. ‖American Academy of Physician Assistants Representative. ¶Task Force Liaison. #Association of Black Cardiologists Representative. **American Pharmacists Association Representative. ††ACC/AHA Prevention Subcommittee Liaison. ‡‡American College of Preventive Medicine Representative. §§American Society of Hypertension Representative. ‖‖Task Force on Performance Measures Liaison. ¶¶American Geriatrics Society Representative. ##National Medical Association Representative
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Oshhepkova EV, Aksenova AV, Orlovskij AA, Chazova IE. [Antihypertensive therapy in men and women in real clinical practice according to the National register]. TERAPEVT ARKH 2019; 91:88-100. [PMID: 32598819 DOI: 10.26442/00403660.2019.09.000356] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Indexed: 11/22/2022]
Abstract
Hypertension is one of the most important risk factors for cardiovascular diseases (CVD) in the world, including Russia. Current Guidelines for the management of arterial hypertension do not include different theatment strategies for men and women. Gender and age analysis of antihypertensive treatmen in men and women could reveal unreasonable and non - optimal treatment in each group. The purpose of this study was to identify the gender features of antihypertensive therapy used by primary care physicians in patients with hypertension. Materials and methods. The study is based on the Arterial Hypertension Registry established in 2012. The methodology of it has been described previously [1]. Medical data from outpatient cards were entered by doctors of 53 city primary care medical centers and 5 cardiology clinics from 22 regions of the Russian Federation. The study included the data of 33 564 patients from 18 years and older with diagnosis of arterial hypertension. Gender, age, height, body weight, smoking status, office blood pressure (BP), laboratory and instrumental examination methods, diagnosed cardiovascular and cerebrovascular diseases and comorbidities in accordance with the International Classification of Diseases of the 10th revision [ICD-10], as well as the treatment (antihypertensive and lipid - lowering therapy) were listed. Results and conclusion. Gender differences in the prescription antihypertensive therapy (AHT) in men and women with hypertension were revealed. Apparently, one of the reasons for these differences is the earlier and more frequent development of cardiovascular and cerebrovascular complications of hypertension in men than in women. Beta - blockers (BB) and angiotensin - converting enzyme inhibitors (ACEi) are more often prescribed to men with hypertension and with coronary artery disease (CAD), myocardial infarction (MI) and chronic heart failure (CHF). Women with hypertension are more often prescribed angiotensin receptor blockers (ARB), thiazide and thiazide - like diuretics. The study also showed non - optimal treatment of patients with hypertension. Insufficient prescription of medication which could improve the prognosis of the disease (ACE inhibitors /ARB, BB, mineralocorticoid receptor antagonist) have been identified in patients with hypertension and CAD, MI, CHF. It is noteworthy that in the some outpatient cards of patients with AH there is no record of AHT prescription: at a young age - in 9.6%, at old age in 15.1% of cards. Despite the fact of high and very high cardiovascular risk of the majority of patients, lipid - lowering therapy (statins) was prescribed insufficiently. The most statin administration was observed in hypertensive patients with coronary artery disease (50.1%) and myocardial infarction (62.7%).
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Affiliation(s)
- E V Oshhepkova
- Myasnikov Institute of Clinical Cardiology, National Medical Research Center of Cardiology
| | - A V Aksenova
- Myasnikov Institute of Clinical Cardiology, National Medical Research Center of Cardiology
| | - A A Orlovskij
- Myasnikov Institute of Clinical Cardiology, National Medical Research Center of Cardiology
| | - I E Chazova
- Myasnikov Institute of Clinical Cardiology, National Medical Research Center of Cardiology
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Bonner C, Fajardo MA, Doust J, McCaffery K, Trevena L. Implementing cardiovascular disease prevention guidelines to translate evidence-based medicine and shared decision making into general practice: theory-based intervention development, qualitative piloting and quantitative feasibility. Implement Sci 2019; 14:86. [PMID: 31466526 PMCID: PMC6716813 DOI: 10.1186/s13012-019-0927-x] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 07/18/2019] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND The use of cardiovascular disease (CVD) prevention guidelines based on absolute risk assessment is poor around the world, including Australia. Behavioural barriers amongst GPs and patients include capability (e.g. difficulty communicating/understanding risk) and motivation (e.g. attitudes towards guidelines/medication). This paper outlines the theory-based development of a website for GP guidelines, and piloting of a new risk calculator/decision aid. METHODS Stage 1 involved identifying evidence-based solutions using the Behaviour Change Wheel (BCW) framework, informed by previous research involving 400 GPs and 600 patients/consumers. Stage 2 co-developed website content with GPs. Stage 3 piloted a prototype website at a national GP conference. Stage 4 iteratively improved the website based on "think aloud" interviews with GPs and patients. Stage 5 was a feasibility study to evaluate potential efficacy (guidelines-based recommendations for each risk category), acceptability (intended use) and demand (actual use over 1 month) amongst GPs (n = 98). RESULTS Stage 1 identified GPs as the target for behaviour change; the need for a new risk calculator/decision aid linked to existing audit and feedback training; and online guidelines as a delivery format. Stage 2-4 iteratively improved content and format based on qualitative feedback from GP and patient user testing over three rounds of website development. Stage 5 suggested potential efficacy with improved identification of hypothetical high risk patients (from 26 to 76%) and recommended medication (from 57 to 86%) after viewing the website (n = 42), but prescribing to low risk patients remained similar (from 19 to 22%; n = 37). Most GPs (89%) indicated they would use the website in the next month, and 72% reported using it again after one month (n = 98). Open feedback identified implementation barriers including a need for integration with medical software, low health literacy resources and pre-consultation assessment. CONCLUSIONS Following a theory-based development process and user co-design, the resulting intervention was acceptable to GPs with high intentions for use, improved identification of patient risk categories and more guidelines-based prescribing intentions for high risk but not low risk patients. The effectiveness of linking the intervention to clinical practice more closely to address implementation barriers will be evaluated in future research.
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Affiliation(s)
- Carissa Bonner
- The University of Sydney, Sydney School of Public Health, ASK-GP Centre of Research Excellence, Rm 128 Edward Ford Building (A27), Sydney, NSW Australia
| | - Michael Anthony Fajardo
- The University of Sydney, Sydney School of Public Health, ASK-GP Centre of Research Excellence, Rm 128 Edward Ford Building (A27), Sydney, NSW Australia
| | - Jenny Doust
- Bond University, Faculty of Health Sciences & Medicine, ASK-GP Centre of Research Excellence, Robina, QLD Australia
| | - Kirsten McCaffery
- The University of Sydney, Sydney School of Public Health, ASK-GP Centre of Research Excellence, Rm 128 Edward Ford Building (A27), Sydney, NSW Australia
| | - Lyndal Trevena
- The University of Sydney, Sydney School of Public Health, ASK-GP Centre of Research Excellence, Rm 128 Edward Ford Building (A27), Sydney, NSW Australia
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Herrett E, Gadd S, Jackson R, Bhaskaran K, Williamson E, van Staa T, Sofat R, Timmis A, Smeeth L. Eligibility and subsequent burden of cardiovascular disease of four strategies for blood pressure-lowering treatment: a retrospective cohort study. Lancet 2019; 394:663-671. [PMID: 31353050 PMCID: PMC6717081 DOI: 10.1016/s0140-6736(19)31359-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Revised: 05/24/2019] [Accepted: 06/04/2019] [Indexed: 01/17/2023]
Abstract
BACKGROUND Worldwide treatment recommendations for lowering blood pressure continue to be guided predominantly by blood pressure thresholds, despite strong evidence that the benefits of blood pressure reduction are observed in patients across the blood pressure spectrum. In this study, we aimed to investigate the implications of alternative strategies for offering blood pressure treatment, using the UK as an illustrative example. METHODS We did a retrospective cohort study in primary care patients aged 30-79 years without cardiovascular disease, using data from the UK's Clinical Practice Research Datalink linked to Hospital Episode Statistics and Office for National Statistics mortality. We assessed and compared four different strategies to determine eligibility for treatment: using 2011 UK National Institute for Health and Care Excellence (NICE) guideline, or proposed 2019 NICE guideline, or blood pressure alone (threshold ≥140/90 mm Hg), or predicted 10-year cardiovascular risk alone (QRISK2 score ≥10%). Patients were followed up until the earliest occurrence of a cardiovascular disease diagnosis, death, or end of follow-up period (March 31, 2016). For each strategy, we estimated the proportion of patients eligible for treatment and number of cardiovascular events that could be prevented with treatment. We then estimated eligibility and number of events that would occur during 10 years in the UK general population. FINDINGS Between Jan 1, 2011, and March 31, 2016, 1 222 670 patients in the cohort were followed up for a median of 4·3 years (IQR 2·5-5·2). 271 963 (22·2%) patients were eligible for treatment under the 2011 NICE guideline, 327 429 (26·8%) under the proposed 2019 NICE guideline, 481 859 (39·4%) on the basis of a blood pressure threshold of 140/90 mm Hg or higher, and 357 840 (29·3%) on the basis of a QRISK2 threshold of 10% or higher. During follow-up, 32 183 patients were diagnosed with cardiovascular disease (overall rate 7·1 per 1000 person-years, 95% CI 7·0-7·2). Cardiovascular event rates in patients eligible for each strategy were 15·2 per 1000 person-years (95% CI 15·0-15·5) under the 2011 NICE guideline, 14·9 (14·7-15·1) under the proposed 2019 NICE guideline, 11·4 (11·3-11·6) with blood pressure threshold alone, and 16·9 (16·7-17·1) with QRISK2 threshold alone. Scaled to the UK population, we estimated that 233 152 events would be avoided under the 2011 NICE guideline (28 patients needed to treat for 10 years to avoid one event), 270 233 under the 2019 NICE guideline (29 patients), 301 523 using a blood pressure threshold (38 patients), and 322 921 using QRISK2 threshold (27 patients). INTERPRETATION A cardiovascular risk-based strategy (QRISK2 ≥10%) could prevent over a third more cardiovascular disease events than the 2011 NICE guideline and a fifth more than the 2019 NICE guideline, with similar efficiency regarding number treated per event avoided. FUNDING National Institute for Health Research.
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Affiliation(s)
- Emily Herrett
- Department of Non-Communicable Diseases Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
| | - Sarah Gadd
- Department of Non-Communicable Diseases Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Rod Jackson
- Section of Epidemiology and Biostatistics, School of Population Health, University of Auckland, Auckland, New Zealand
| | - Krishnan Bhaskaran
- Department of Non-Communicable Diseases Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Elizabeth Williamson
- Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, UK; Health Data Research UK, London, UK
| | - Tjeerd van Staa
- Centre for Health Informatics, Division of Informatics, Imaging and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute of Pharmaceutical Sciences, Utrecht, Netherlands
| | - Reecha Sofat
- Institute of Health Informatics University College London, London, UK
| | - Adam Timmis
- Barts Heart Centre, Queen Mary University London, London, UK
| | - Liam Smeeth
- Department of Non-Communicable Diseases Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; Health Data Research UK, London, UK
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Welsh J, Korda RJ, Joshy G, Banks E. Primary Absolute Cardiovascular Disease Risk and Prevention in Relation to Psychological Distress in the Australian Population: A Nationally Representative Cross-Sectional Study. Front Public Health 2019; 7:126. [PMID: 31214558 PMCID: PMC6554659 DOI: 10.3389/fpubh.2019.00126] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 05/07/2019] [Indexed: 01/14/2023] Open
Abstract
People who experience psychological distress have an elevated risk of incident cardiovascular disease (CVD). However, the extent to which traditional CVD prevention strategies could be used to reduce the CVD burden in this group is unclear because population-level data on CVD risk profiles and appropriate management of risk in relation to distress are currently not available. The aim of this study was to use nationally representative data to quantify variation in CVD risk and appropriate management of risk according to level of psychological distress in the Australian population. Data were from 2,618 participants aged 45-74 years without prior CVD who participated in the 2011-12 Australian Health Survey, a cross-sectional and nationally representative study of Australian adults. Age-and sex-adjusted prevalence of 5-year absolute risk of primary CVD (low <10%, moderate 10-15%, or high >15%), CVD risk factors, blood-pressure, and cholesterol assessments, and appropriate treatment (combined blood pressure- and lipid-lowering medication) if at high primary risk, were estimated. Prevalence ratios (PR) quantified variation in these outcomes in relation to low (Kessler-10 score: 10-<12), mild (12-<16), moderate (16-<22) and high (22-50) psychological distress, after adjusting for sociodemographic characteristics. The prevalence of high absolute risk of primary CVD for low, mild, moderate and high distress was 10.9, 12.3, 11.4, and 18.6%, respectively, and was significantly higher among participants with high compared to low distress (adjusted PR:1.62, 95%CI:1.04-2.52). The prevalence of CVD risk factors was generally higher in those with higher psychological distress. Blood pressure and cholesterol assessments were reported by the majority of participants (>85%) but treatment of high absolute risk was low (<30%), and neither were related to psychological distress. Our findings confirm the importance of recognizing people who experience psychological distress as a high risk group and suggest that at least part of the excess burden of primary CVD events among people with high psychological distress could be reduced with an absolute risk approach to assessment and improved management of high primary CVD risk.
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Affiliation(s)
- Jennifer Welsh
- National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, ACT, Australia
| | - Rosemary J Korda
- National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, ACT, Australia
| | - Grace Joshy
- National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, ACT, Australia
| | - Emily Banks
- National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, ACT, Australia.,The Sax Institute, Ultimo, NSW, Australia
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Mc Namara KP, Krass I, Peterson GM, Alzubaidi H, Grenfell R, Freedman B, Dunbar JA. Implementing screening interventions in community pharmacy to promote interprofessional coordination of primary care - A mixed methods evaluation. Res Social Adm Pharm 2019; 16:160-167. [PMID: 31088777 DOI: 10.1016/j.sapharm.2019.04.011] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Revised: 04/04/2019] [Accepted: 04/15/2019] [Indexed: 10/26/2022]
Abstract
BACKGROUND Screening is a critical component of efforts to reduce the population burden of cardiovascular disease (CVD), by facilitating early use of cost-effective prevention and treatment strategies. While international evidence suggests that screening in community pharmacies improves screening access and identifies at-risk individuals, concerns from medical organisations about the absence of interdisciplinary coordination and related lack of continuity of care with general practice have significantly contributed to reluctance from some stakeholders to endorse, and engage with, pharmacy-based screening initiatives. The Cardiovascular Absolute Risk Screening (CARS) study was designed to address these challenges and promote an interprofessional approach to screening for cardiovascular disease risk by pharmacists. This study describes the impact of the CARS implementation model on interdisciplinary coordination and continuity of care. METHODS In addition to clinical training, pharmacists at eleven participating pharmacies were provided with implementation training, resources and support to promote interprofessional coordination. Completion of training and pharmacy implementation plans, both of which highlighted GP engagement strategies, were pre-requisites for screening commencement. Using mixed methods approaches, data were analyzed from screening records (n = 388), researcher interviews with patients at 6-10 weeks post-screening (n = 248, 64%), and pharmacist interviews (n = 10). RESULTS Screening records suggested that 94% of screened individuals were advised to seek formal GP assessment, and 98% consented to sharing of results. Among interviewed participants, 81% recalled direct pharmacist action to facilitate GP engagement. Among interviewees who had seen their GP already (n = 70), 79% reported that their GP was aware of the results (another 16% were uncertain). Pharmacists reported positive GP feedback stemming from efforts at early engagement, but an absence of ongoing collaboration. CONCLUSIONS Use of implementation planning by pharmacists, alongside clinical training, can effectively promote an interdisciplinary coordination focus by pharmacists.
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Affiliation(s)
- Kevin P Mc Namara
- School of Medicine, Deakin University, Geelong, Victoria, Australia; Centre for Population Health Research, Deakin University, Geelong, Victoria, Australia; Centre for Medicine Use and Safety, Monash University, Parkville, Victoria, Australia.
| | - Ines Krass
- School of Pharmacy, The University of Sydney, Camperdown, New South Wales, Australia
| | - Gregory M Peterson
- School of Medicine, Faculty of Health, University of Tasmania, Hobart, Tasmania, Australia
| | - Hamzah Alzubaidi
- University of Sharjah, Sharjah Institute for Medical Research and College of Pharmacy, Sharjah, United Arab Emirates
| | - Rob Grenfell
- CSIRO Health and Biosecurity, Parkville, Victoria, Australia
| | - Ben Freedman
- Heart Research Institute/Charles Perkins Centre, University of Sydney, Camperdown, New South Wales, Australia; Sydney Medical School, University of Sydney, Camperdown, New South Wales, Australia
| | - James A Dunbar
- Centre for Population Health Research, Deakin University, Geelong, Victoria, Australia
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Ju I, Banks E, Calabria B, Ju A, Agostino J, Korda RJ, Usherwood T, Manera K, Hanson CS, Craig JC, Tong A. General practitioners' perspectives on the prevention of cardiovascular disease: systematic review and thematic synthesis of qualitative studies. BMJ Open 2018; 8:e021137. [PMID: 30389756 PMCID: PMC6224770 DOI: 10.1136/bmjopen-2017-021137] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2018] [Revised: 09/27/2018] [Accepted: 10/03/2018] [Indexed: 12/12/2022] Open
Abstract
OBJECTIVE Cardiovascular disease (CVD) is a leading cause of morbidity and mortality globally, and prevention of CVD is a public health priority. This paper aims to describe the perspectives of general practitioners (GPs) on the prevention of CVD across different contexts. DESIGN Systematic review and thematic synthesis of qualitative studies using the Enhancing Transparency of Reporting the Synthesis of Qualitative research (ENTREQ) framework. DATA SOURCES MEDLINE, Embase, PsycINFO and CINAHL from database inception to April 2018. ELIGIBILITY CRITERIA FOR SELECTING STUDIES We included qualitative studies on the perspectives of GPs on CVD prevention. DATA EXTRACTION AND SYNTHESIS We used HyperRESEARCH to code the primary papers and identified themes. RESULTS We selected 34 studies involving 1223 participants across nine countries. We identified six themes: defining own primary role (duty to prescribe medication, refraining from risking patients' lives, mediating between patients and specialists, delegating responsibility to patients, providing holistic care); trusting external expertise (depending on credible evidence and opinion, entrusting care to other health professionals, integrating into patient context); motivating behavioural change for prevention (highlighting tangible improvements, negotiating patient acceptance, enabling autonomy and empowerment, harnessing the power of fear, disappointment with futility of advice); recognising and accepting patient capacities (ascertaining patient's drive for lifestyle change, conceding to ingrained habits, prioritising urgent comorbidities, tailoring to patient environment and literacy); avoiding overmedicalisation (averting long-term dependence on medications, preventing a false sense of security, minimising stress of sickness) and minimising economic burdens (avoiding unjustified costs to patients, delivering practice within budget, alleviating healthcare expenses). CONCLUSIONS GPs sought to empower patients to prevent CVD, but consideration of patients' individual factors was challenging. Community-based strategies for assessing CVD risk involving other health professionals, and decision aids that address the individuality of the patient's health and environment, may support GPs in their decisions regarding CVD prevention.
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Affiliation(s)
- Irene Ju
- Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Kidney Research, The Children’s Hospital at Westmead, Westmead, New South Wales, Australia
| | - Emily Banks
- National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, Australian Capital Territory, Australia
- Sax Institute, Haymarket, New South Wales, Australia
| | - Bianca Calabria
- National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, Australian Capital Territory, Australia
- National Drug and Alcohol Research Centre, University of New South Wales, Sydney, New South Wales, Australia
| | - Angela Ju
- Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Kidney Research, The Children’s Hospital at Westmead, Westmead, New South Wales, Australia
| | - Jason Agostino
- Academic Unit of General Practice, School of Medicine, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Rosemary J Korda
- National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Tim Usherwood
- Department of General Practice, Sydney Medical School Westmead, University of Sydney, Sydney, New South Wales, Australia
| | - Karine Manera
- Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Kidney Research, The Children’s Hospital at Westmead, Westmead, New South Wales, Australia
| | - Camilla S Hanson
- Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Kidney Research, The Children’s Hospital at Westmead, Westmead, New South Wales, Australia
| | - Jonathan C Craig
- Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Kidney Research, The Children’s Hospital at Westmead, Westmead, New South Wales, Australia
| | - Allison Tong
- Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Kidney Research, The Children’s Hospital at Westmead, Westmead, New South Wales, Australia
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Whelton PK, Carey RM, Aronow WS, Casey DE, Collins KJ, Dennison Himmelfarb C, DePalma SM, Gidding S, Jamerson KA, Jones DW, MacLaughlin EJ, Muntner P, Ovbiagele B, Smith SC, Spencer CC, Stafford RS, Taler SJ, Thomas RJ, Williams KA, Williamson JD, Wright JT. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: Executive Summary. ACTA ACUST UNITED AC 2018; 12:579.e1-579.e73. [DOI: 10.1016/j.jash.2018.06.010] [Citation(s) in RCA: 92] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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17
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Whelton PK, Carey RM, Aronow WS, Casey DE, Collins KJ, Dennison Himmelfarb C, DePalma SM, Gidding S, Jamerson KA, Jones DW, MacLaughlin EJ, Muntner P, Ovbiagele B, Smith SC, Spencer CC, Stafford RS, Taler SJ, Thomas RJ, Williams KA, Williamson JD, Wright JT. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension 2018. [DOI: 10.1161/hyp.0000000000000065 10.1016/j.jacc.2017.11.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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18
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Whelton PK, Carey RM, Aronow WS, Casey DE, Collins KJ, Dennison Himmelfarb C, DePalma SM, Gidding S, Jamerson KA, Jones DW, MacLaughlin EJ, Muntner P, Ovbiagele B, Smith SC, Spencer CC, Stafford RS, Taler SJ, Thomas RJ, Williams KA, Williamson JD, Wright JT. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension 2017; 71:e13-e115. [PMID: 29133356 DOI: 10.1161/hyp.0000000000000065] [Citation(s) in RCA: 1552] [Impact Index Per Article: 221.7] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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Whelton PK, Carey RM, Aronow WS, Casey DE, Collins KJ, Dennison Himmelfarb C, DePalma SM, Gidding S, Jamerson KA, Jones DW, MacLaughlin EJ, Muntner P, Ovbiagele B, Smith SC, Spencer CC, Stafford RS, Taler SJ, Thomas RJ, Williams KA, Williamson JD, Wright JT. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension 2017; 71:1269-1324. [PMID: 29133354 DOI: 10.1161/hyp.0000000000000066] [Citation(s) in RCA: 2113] [Impact Index Per Article: 301.9] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Whelton PK, Carey RM, Aronow WS, Casey DE, Collins KJ, Dennison Himmelfarb C, DePalma SM, Gidding S, Jamerson KA, Jones DW, MacLaughlin EJ, Muntner P, Ovbiagele B, Smith SC, Spencer CC, Stafford RS, Taler SJ, Thomas RJ, Williams KA, Williamson JD, Wright JT. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol 2017; 71:2199-2269. [PMID: 29146533 DOI: 10.1016/j.jacc.2017.11.005] [Citation(s) in RCA: 618] [Impact Index Per Article: 88.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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21
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Whelton PK, Carey RM, Aronow WS, Casey DE, Collins KJ, Dennison Himmelfarb C, DePalma SM, Gidding S, Jamerson KA, Jones DW, MacLaughlin EJ, Muntner P, Ovbiagele B, Smith SC, Spencer CC, Stafford RS, Taler SJ, Thomas RJ, Williams KA, Williamson JD, Wright JT. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol 2017; 71:e127-e248. [PMID: 29146535 DOI: 10.1016/j.jacc.2017.11.006] [Citation(s) in RCA: 3016] [Impact Index Per Article: 430.9] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Matthews V, Burgess CP, Connors C, Moore E, Peiris D, Scrimgeour D, Thompson SC, Larkins S, Bailie R. Integrated Clinical Decision Support Systems Promote Absolute Cardiovascular Risk Assessment: An Important Primary Prevention Measure in Aboriginal and Torres Strait Islander Primary Health Care. Front Public Health 2017; 5:233. [PMID: 28929097 PMCID: PMC5591433 DOI: 10.3389/fpubh.2017.00233] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2017] [Accepted: 08/18/2017] [Indexed: 11/13/2022] Open
Abstract
Background Aboriginal and Torres Strait Islander Australians experience a greater burden of disease compared to non-Indigenous Australians. Around one-fifth of the health disparity is caused by cardiovascular disease (CVD). Despite the importance of absolute cardiovascular risk assessment (CVRA) as a screening and early intervention tool, few studies have reported its use within the Australian Indigenous primary health care (PHC) sector. This study utilizes data from a large-scale quality improvement program to examine variation in documented CVRA as a primary prevention strategy for individuals without prior CVD across four Australian jurisdictions. We also examine the proportion with elevated risk and follow-up actions recorded. Methods We undertook cross-sectional analysis of 2,052 client records from 97 PHC centers to assess CVRA in Indigenous adults aged ≥20 years with no recorded chronic disease diagnosis (2012–2014). Multilevel regression was used to quantify the variation in CVRA attributable to health center and client level factors. The main outcome measure was the proportion of eligible adults who had CVRA recorded. Secondary outcomes were the proportion of clients with elevated risk that had follow-up actions recorded. Results Approximately 23% (n = 478) of eligible clients had documented CVRA. Almost all assessments (99%) were conducted in the Northern Territory. Within this jurisdiction, there was wide variation between centers in the proportion of clients with documented CVRA (median 38%; range 0–86%). Regression analysis showed health center factors accounted for 48% of the variation. Centers with integrated clinical decision support systems were more likely to document CVRA (OR 21.1; 95% CI 5.4–82.4; p < 0.001). Eleven percent (n = 53) of clients were found with moderate/high CVD risk, of whom almost one-third were under 35 years (n = 16). Documentation of follow-up varied with respect to the targeted risk factor. Fewer than 30% with abnormal blood lipid or glucose levels had follow-up management plans recorded. Conclusion There was wide variation in CVRA between jurisdictions and between PHC centers. Learnings from successful interventions to educate and support centers in CVRA provision should be shared with stakeholders more widely. Where risk has been identified, further improvement in follow-up management is required to prevent CVD onset and reduce future burden in Australia’s Indigenous population.
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Affiliation(s)
- Veronica Matthews
- The University of Sydney, University Centre for Rural Health - North Coast, Lismore, NSW, Australia
| | | | - Christine Connors
- Top End Health Service, Northern Territory Government, Darwin, NT, Australia
| | - Elizabeth Moore
- Aboriginal Medical Services Alliance Northern Territory, Alice Springs, NT, Australia
| | - David Peiris
- The George Institute for Global Health, Sydney, NSW, Australia
| | | | - Sandra C Thompson
- Western Australian Centre for Rural Health, University of Western Australia, Geraldton, WA, Australia
| | - Sarah Larkins
- College of Medicine and Dentistry, James Cook University, Townsville, QLD, Australia
| | - Ross Bailie
- The University of Sydney, University Centre for Rural Health - North Coast, Lismore, NSW, Australia
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Ho CLB, Sanders S, Doust J, Breslin M, Reid CM, Nelson MR. Legacy Effect of Delayed Blood Pressure-Lowering Pharmacotherapy in Middle-Aged Individuals Stratified by Absolute Cardiovascular Disease Risk: Protocol for a Systematic Review. JMIR Res Protoc 2017; 6:e177. [PMID: 28864428 PMCID: PMC5600968 DOI: 10.2196/resprot.8362] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2017] [Revised: 07/20/2017] [Accepted: 07/21/2017] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Many national and international guidelines recommend that the initiation of blood pressure (BP)-lowering drug treatment for the primary prevention of cardiovascular disease (CVD) should no longer be based on BP level alone, but on absolute cardiovascular risk. While BP-lowering drug treatment is beneficial in high-risk individuals at any level of elevated BP, clinicians are concerned about legacy effects on patients with low-to-moderate risk and mildly elevated BP who remain "untreated". OBJECTIVE We aim to investigate the legacy effect of delayed BP-lowering pharmacotherapy in middle-aged individuals (45-65 years) with mildly elevated BP (systolic BP 140-159 mmHg and/or diastolic BP 90-99 mmHg) stratified by absolute risk for primary prevention of CVD, but particularly in the low-risk (<10% five-year absolute risk) group. METHODS Randomized trials of BP-lowering therapy versus placebo or pretreated subjects in active comparator studies with posttrial follow-up will be identified using a 2-step process. First, randomized trials of BP-lowering therapy will be identified by (1) retrieving the references of trials included in published systematic reviews of BP-lowering therapy, (2) retrieving studies published by the Blood Pressure Lowering Treatment Trialists' Collaboration (BPLTTC), and (3) checking studies referenced in the 1993 World Health Organization/International Society of Hypertension meeting memorandum on BP management. Posttrial follow-up studies will then be identified by forward citation searching the randomized trials identified in step 1 through Web of Science. The search will include randomized controlled trials with at least 1-year in-trial period and a posttrial follow-up phase. Age is the major determinant of absolute cardiovascular risk, so the participants in our review will be restricted to middle-aged adults who are more likely to have a lower cardiovascular risk profile. The primary outcome will be all-cause mortality. Secondary outcomes will include cardiovascular mortality, fatal stroke, fatal myocardial infarction, and death due to heart failure. RESULTS The searches for existing systematic reviews and BPLTTC studies were piloted and modified. The study is expected to be completed before June 2018. CONCLUSIONS The findings of this study will contribute to the body of knowledge concerning the beneficial, neutral, or harmful effects of delayed BP-lowering drug treatment on the primary prevention of CVD in patients with mildly elevated BP and low-to-moderate CVD risk. TRIAL REGISTRATION PROSPERO International Prospective Register of Systematic Reviews: CRD42017058414; https://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42017058414 (Archived by WebCite® at http://www.webcitation.org/6t6sa8O2Q).
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Affiliation(s)
- Chau Le Bao Ho
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | - Sharon Sanders
- Centre for Research in Evidence-Based Practice, Bond University, Gold Coast, QLD, Australia
| | - Jenny Doust
- Centre for Research in Evidence-Based Practice, Bond University, Gold Coast, QLD, Australia
| | - Monique Breslin
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | - Christopher M Reid
- School of Public Health, Curtin University, Perth, WA, Australia
- Centre of Cardiovascular Research & Education in Therapeutics, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Mark Raymond Nelson
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
- Centre of Cardiovascular Research & Education in Therapeutics, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
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Finnikin S, Ryan R, Marshall T. Cohort study investigating the relationship between cholesterol, cardiovascular risk score and the prescribing of statins in UK primary care: study protocol. BMJ Open 2016; 6:e013120. [PMID: 27856481 PMCID: PMC5128938 DOI: 10.1136/bmjopen-2016-013120] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
INTRODUCTION Risk scoring is an integral part of the prevention of cardiovascular disease (CVD) and should form the basis for the decision to offer medication to reduce cholesterol (statins). However, there is a suggestion in the literature that many patients are still initiated on statins based on raised cholesterol rather than a raised CVD risk. It is important, therefore, to investigate the role that lipid levels and CVD risks have in the decision to prescribe. This research will establish how cholesterol levels and CVD risk independently influence the prescribing of statins for the primary prevention of CVD in primary care. METHODS AND ANALYSIS The Health Improvement Network (THIN) is a database of coded primary care electronic patient records from over 500 UK general practices. From this resource, a historical cohort will be created of patients without a diagnosis of CVD, not currently receiving a prescription for statins and who had a lipid profile measured. A post hoc QRISK2 score will be calculated for these patients and they will be followed up for 60 days to establish whether they were subsequently prescribed a statin. Primary analysis will consist of predictive modelling using multivariate logistic regression with potential predictors including cholesterol level, calculated QRISK2 score, sociodemographic characteristic and comorbidities. Descriptive statistics will be used to identify trends in prescribing and further secondary analysis will explore what other factors may have influenced the prescribing of statins and the degree of interprescriber variability. ETHICS AND DISSEMINATION The THIN Data Collection Scheme was approved by the South-East Multicentre Research Ethics Committee in 2003. Individual studies using THIN require Scientific Review Committee approval. The original protocol for this study and a subsequent amendment have been approved (16THIN009A1). The results will be published in a peer review journal and presented at national and international conferences.
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Affiliation(s)
- Samuel Finnikin
- Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Ronan Ryan
- Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Tom Marshall
- Institute of Applied Health Research, University of Birmingham, Birmingham, UK
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Feigin VL, Norrving B, George MG, Foltz JL, Roth GA, Mensah GA. Prevention of stroke: a strategic global imperative. Nat Rev Neurol 2016; 12:501-12. [PMID: 27448185 PMCID: PMC8114177 DOI: 10.1038/nrneurol.2016.107] [Citation(s) in RCA: 140] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
The increasing global stroke burden strongly suggests that currently implemented primary stroke prevention strategies are not sufficiently effective, and new primary prevention strategies with larger effect sizes are needed. Here, we review the latest stroke epidemiology literature, with an emphasis on the recently published Global Burden of Disease 2013 Study estimates; highlight the problems with current primary stroke and cardiovascular disease (CVD) prevention strategies; and outline new developments in primary stroke and CVD prevention. We also suggest key priorities for the future, including comprehensive prevention strategies that target people at all levels of CVD risk; implementation of an integrated approach to promote healthy behaviours and reduce health disparities; capitalizing on information technology to advance prevention approaches and techniques; and incorporation of culturally appropriate education about healthy lifestyles into standard education curricula early in life. Given the already immense and fast-increasing burden of stroke and other major noncommunicable diseases (NCDs), which threatens worldwide sustainability, governments of all countries should develop and implement an emergency action plan addressing the primary prevention of NCDs, possibly including taxation strategies to tackle unhealthy behaviours that increase the risk of stroke and other NCDs.
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Affiliation(s)
- Valery L Feigin
- National Institute for Stroke and Applied Neurosciences, School of Rehabilitation and Occupation Studies, School of Public Health and Psychosocial Studies, Faculty of Health and Environmental Studies, Auckland University of Technology, North Shore Campus, AA254, 90 Akoranga Drive, Northcote 0627, Private Bag 92006, Auckland 1142, New Zealand
| | - Bo Norrving
- Department of Clinical Sciences, Neurology, Lund University, Paradisgatan 2, Lund, Sweden
| | - Mary G George
- Division for Heart Disease &Stroke Prevention, Centers for Disease Control and Prevention, 600 Clifton Road, Atlanta, Georgia 30333, USA
| | - Jennifer L Foltz
- Division for Heart Disease &Stroke Prevention, Centers for Disease Control and Prevention, 600 Clifton Road, Atlanta, Georgia 30333, USA
| | - Gregory A Roth
- Institute for Health Metrics and Evaluation and the Division of Cardiology, School of Medicine, University of Washington, 2301 5th Avenue Suite 600, Seattle, Washington 98121, USA
| | - George A Mensah
- Center for Translation Research and Implementation Science (CTRIS) and Division of Cardiovascular Sciences; National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Bethesda, Maryland 20892, USA
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McKinn S, Bonner C, Jansen J, Teixeira-Pinto A, So M, Irwig L, Doust J, Glasziou P, McCaffery K. Factors influencing general practitioners' decisions about cardiovascular disease risk reassessment: findings from experimental and interview studies. BMC FAMILY PRACTICE 2016; 17:107. [PMID: 27495325 PMCID: PMC4974805 DOI: 10.1186/s12875-016-0499-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/06/2015] [Accepted: 07/21/2016] [Indexed: 11/25/2022]
Abstract
Background Guidelines on cardiovascular disease (CVD) risk reassessment intervals are unclear, potentially leading to detrimental practice variation: too frequent can result in overtreatment and greater strain on the healthcare system; too infrequent could result in the neglect of high risk patients who require medication. This study aimed to understand the different factors that general practitioners (GPs) consider when deciding on the reassessment interval for patients previously assessed for primary CVD risk. Methods This paper combines quantitative and qualitative data regarding reassessment intervals from two separate studies of CVD risk management. Experimental study: 144 Australian GPs viewed a random selection of hypothetical cases via a paper-based questionnaire, in which blood pressure, cholesterol and 5-year absolute risk (AR) were systematically varied to appear lower or higher. GPs were asked how they would manage each case, including an open-ended response for when they would reassess the patient. Interview study: Semi-structured interviews were conducted with a purposive sample of 25 Australian GPs, recruited separately from the GPs in the experimental study. Transcribed audio-recordings were thematically coded, using the Framework Analysis method. Results Experiment: GPs stated that they would reassess the majority of patients across all absolute risk categories in 6 months or less (low AR = 52 % [CI95% = 47–57 %], moderate AR = 82 % [CI95% = 76–86 %], high AR = 87 % [CI95% = 82–90 %], total = 71 % [CI95% = 67–75 %]), with 48 % (CI95% = 43–53 %) of patients reassessed in under 3 months. The majority (75 % [CI95% = 70–79 %]) of patients with low-moderate AR (≤15 %) and an elevated risk factor would be reassessed in under 6 months. Interviews: GPs identified different functions for reassessment and risk factor monitoring, which affected recommended intervals. These included perceived psychosocial benefits to patients, preparing the patient for medication, and identifying barriers to lifestyle change and medication adherence. Reassessment and monitoring intervals were driven by patient motivation to change lifestyle, patient demand, individual risk factors, and GP attitudes. Conclusions There is substantial variation in reassessment intervals for patients with the same risk profile. This suggests that GPs are not following reassessment recommendations in the Australian guidelines. The use of shorter intervals for low-moderate AR contradicts research on optimal monitoring intervals, and may result in unnecessary costs and over-treatment. Electronic supplementary material The online version of this article (doi:10.1186/s12875-016-0499-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Shannon McKinn
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.,Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia
| | - Carissa Bonner
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.,Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia
| | - Jesse Jansen
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.,Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia
| | - Armando Teixeira-Pinto
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia
| | - Matthew So
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.,Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia
| | - Les Irwig
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia
| | - Jenny Doust
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.,Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, Australia
| | - Paul Glasziou
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.,Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, Australia
| | - Kirsten McCaffery
- Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia. .,Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), The University of Sydney, Sydney, NSW, Australia.
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Karmali KN, Lee JY, Brown T, Persell SD. Predictors of cholesterol treatment discussions and statin prescribing for primary cardiovascular disease prevention in community health centers. Prev Med 2016; 88:176-81. [PMID: 27090436 PMCID: PMC5040465 DOI: 10.1016/j.ypmed.2016.04.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2015] [Revised: 04/05/2016] [Accepted: 04/12/2016] [Indexed: 11/25/2022]
Abstract
BACKGROUND Although cholesterol guidelines emphasize cardiovascular disease (CVD) risk to guide primary prevention, predictors of statin use in practice are unknown. We aimed to identify factors associated with a cholesterol treatment discussion and statin prescribing in a high-risk population. METHODS We used data from a trial conducted among participants in community health centers without CVD or diabetes and a 10-year coronary heart disease (CHD) risk≥10%. Cholesterol treatment discussion was assessed at 6months and statin prescription at 1year. We used logistic regressions to identify factors associated with each outcome. RESULTS We analyzed 646 participants (89% male, mean age 60±9.5years). Cholesterol treatment discussion occurred in 19% and statin prescription in 12% of participants. Ten-year CHD risk was not associated with treatment discussion (OR 1.11 per 1 SD increase, 95% CI 0.91-1.33) but was associated with statin prescription (OR 1.41 per 1 SD increase, 95% CI 1.13-1.75) in unadjusted models. After adjusting for traditional CVD risk factors that contribute to CHD risk, low-density lipoprotein cholesterol (LDL-C) was independently associated with statin prescription (OR 1.82 per 1 SD increase, 95% CI 1.66-1.99). Antihypertensive medication use was independently associated with both cholesterol treatment discussion (OR 3.68, 95% CI 2.35-5.75) and statin prescription (OR 3.98, 95% CI 3.30-4.81). Other drivers of CVD risk (age, smoking, and systolic blood pressure) were not associated with statin use. CONCLUSIONS Single risk factor management strongly influences cholesterol treatment discussions and statin prescribing patterns. Interventions that promote risk-based statin utilization are needed. TRIAL REGISTRATION Clinicaltrials.gov.: NCT01610609.
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Affiliation(s)
- Kunal N Karmali
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States; Division of Cardiology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Ji-Young Lee
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Tiffany Brown
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Stephen D Persell
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States; Center for Primary Care Innovation, Institute for Public Health and Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.
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Schilling C, Mortimer D, Dalziel K, Heeley E, Chalmers J, Clarke P. Using Classification and Regression Trees (CART) to Identify Prescribing Thresholds for Cardiovascular Disease. PHARMACOECONOMICS 2016; 34:195-205. [PMID: 26578402 DOI: 10.1007/s40273-015-0342-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
BACKGROUND AND OBJECTIVE Many guidelines for clinical decisions are hierarchical and nonlinear. Evaluating if these guidelines are used in practice requires methods that can identify such structures and thresholds. Classification and regression trees (CART) were used to analyse prescribing patterns of Australian general practitioners (GPs) for the primary prevention of cardiovascular disease (CVD). Our aim was to identify if GPs use absolute risk (AR) guidelines in favour of individual risk factors to inform their prescribing decisions of lipid-lowering medications. METHODS We employed administrative prescribing information that is linked to patient-level data from a clinical assessment and patient survey (the AusHeart Study), and assessed prescribing of lipid-lowering medications over a 12-month period for patients (n = 1903) who were not using such medications prior to recruitment. CART models were developed to explain prescribing practice. Out-of-sample performance was evaluated using receiver operating characteristic (ROC) curves, and optimised via pruning. RESULTS We found that individual risk factors (low-density lipoprotein, diabetes, triglycerides and a history of CVD), GP-estimated rather than Framingham AR, and sociodemographic factors (household income, education) were the predominant drivers of GP prescribing. However, sociodemographic factors and some individual risk factors (triglycerides and CVD history) only become relevant for patients with a particular profile of other risk factors. The ROC area under the curve was 0.63 (95% confidence interval [CI] 0.60-0.64). CONCLUSIONS There is little evidence that AR guidelines recommended by the National Heart Foundation and National Vascular Disease Prevention Alliance, or conditional individual risk eligibility guidelines from the Pharmaceutical Benefits Scheme, are adopted in prescribing practice. The hierarchy of conditional relationships between risk factors and socioeconomic factors identified by CART provides new insights into prescribing decisions. Overall, CART is a useful addition to the analyst's toolkit when investigating healthcare decisions.
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Affiliation(s)
- Chris Schilling
- Centre for Health Policy, School of Population and Global Health, University of Melbourne, Melbourne, VIC, 3051, Australia.
| | - Duncan Mortimer
- Centre for Health Economics, Monash Business School, Monash University, Melbourne, VIC, 3800, Australia
| | - Kim Dalziel
- Centre for Health Policy, School of Population and Global Health, University of Melbourne, Melbourne, VIC, 3051, Australia
| | - Emma Heeley
- The George Institute for Global Health, The University of Sydney and the Royal Prince Alfred Hospital, Sydney, NSW, 2050, Australia
| | - John Chalmers
- The George Institute for Global Health, The University of Sydney and the Royal Prince Alfred Hospital, Sydney, NSW, 2050, Australia
| | - Philip Clarke
- Centre for Health Policy, School of Population and Global Health, University of Melbourne, Melbourne, VIC, 3051, Australia
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Kulenovic I, Mortensen MB, Bertelsen J, May O, Dodt KK, Kanstrup H, Falk E. Statin use prior to first myocardial infarction in contemporary patients: Inefficient and not gender equitable. Prev Med 2016; 83:63-9. [PMID: 26687101 DOI: 10.1016/j.ypmed.2015.12.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2015] [Revised: 10/28/2015] [Accepted: 12/06/2015] [Indexed: 11/27/2022]
Abstract
OBJECTIVES Guidelines recommend initiating primary prevention with statins to those at highest cardiovascular risk. We assessed the gender-specific implementation and effectiveness of this risk-guided approach. METHODS We identified 1399 consecutive patients without known cardiovascular disease or diabetes hospitalized with a first myocardial infarction (MI) in Denmark. Statin use before MI was assessed, and cardiovascular risk was calculated using SCORE (Systematic COronary Risk Evaluation). RESULTS Among patients with first MI, 36% were women. Compared with men, they were older (mean 72 vs. 65years) but had a lower estimated risk (median 3.4% vs. 6.7%, SCORE high-risk model in the statin-naïve patients). Statin therapy had been initiated in 12% of women and 10% of men prior to MI. After adding 1.5mmol/L to the total cholesterol concentration of those already on statins, the estimated pre-treatment risk was much lower in women than men (median 3.8% vs. 9.2%, SCORE high-risk model), and only 29% of women would have passed the risk-based treatment threshold defined by the European guidelines (SCORE ≥5%). Estimated risk and statin use correlated directly in men but not in women. Only ~5% of first MI are prevented by the current use of statins in people without diabetes. CONCLUSION In people destined for a first MI, statin therapy is uncommon and prevents few events. Lower-risk women receive as much statins as higher risk men. This gender disparity and inefficient targeting of statins to those at highest risk indicate that risk scoring is not widely used in routine clinical practice in Denmark.
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Affiliation(s)
- Imra Kulenovic
- Department of Cardiology, Aarhus University Hospital, Denmark
| | | | | | - Ole May
- Department of Medicine, Regional Hospital Herning, Denmark
| | - Karen Kaae Dodt
- Department of Cardiology, Regional Hospital Horsens, Denmark
| | - Helle Kanstrup
- Department of Cardiology, Aarhus University Hospital, Denmark
| | - Erling Falk
- Department of Cardiology, Aarhus University Hospital, Denmark
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Kim J, Thrift AG, Nelson MR, Bladin CF, Cadilhac DA. Personalized medicine and stroke prevention: where are we? Vasc Health Risk Manag 2015; 11:601-11. [PMID: 26664130 PMCID: PMC4671759 DOI: 10.2147/vhrm.s77571] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
There are many recommended pharmacological and non-pharmacological therapies for the prevention of stroke, and an ongoing challenge is to improve their uptake. Personalized medicine is seen as a possible solution to this challenge. Although the use of genetic information to guide health care could be considered as the apex of personalized medicine, genetics is not yet routinely used to guide prevention of stroke. Currently personalized aspects of prevention of stroke include tailoring interventions based on global risk, the utilization of individualized management plans within a model of organized care, and patient education. In this review we discuss the progress made in these aspects of prevention of stroke and present a case study to illustrate the issues faced by health care providers and patients with stroke that could be overcome with a personalized approach to the prevention of stroke.
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Affiliation(s)
- Joosup Kim
- Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia ; Public Health, Stroke Division, Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia
| | - Amanda G Thrift
- Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia
| | - Mark R Nelson
- Discipline of General Practice, School of Medicine, Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | - Christopher F Bladin
- Public Health, Stroke Division, Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia ; Eastern Health Clinical School, Monash University, Clayton, VIC, Australia
| | - Dominique A Cadilhac
- Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia ; Public Health, Stroke Division, Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia
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31
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New Strategy to Reduce the Global Burden of Stroke. Stroke 2015; 46:1740-7. [DOI: 10.1161/strokeaha.115.008222] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2015] [Accepted: 03/27/2015] [Indexed: 11/16/2022]
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