Survey of physicians' practices in the control of cardiovascular risk factors: the EURIKA study.
ABSTRACT To assess the practices of physicians in 12 European countries in the primary prevention of cardiovascular disease (CVD).
In 2009, 806 physicians from 12 European countries answered a questionnaire, delivered electronically or by post, regarding their assessment of patients with cardiovascular risk factors, and their use of risk calculation tools and clinical practice guidelines (ClinicalTrials.gov number: NCT00882336). Approximately 60 physicians per country were selected (participation rate varied between 3.1% in Sweden and 22.8% in Turkey).
Among participating physicians, 85.2% reported using at least one clinical guideline for CVD prevention. The most popular were the ESC guidelines (55.1%). Reasons for not using guidelines included: the wide choice available (47.1%), time constraints (33.3%), lack of awareness of guidelines (27.5%), and perception that guidelines are unrealistic (23.5%). Among all physicians, 68.5% reported using global risk calculation tools. Written charts were the preferred method (69.4%) and the most commonly used was the SCORE equation (35.4%). Reasons for not using equations included time constraints (59.8%), not being convinced of their usefulness (21.7%) and lack of awareness (19.7%). Most physicians (70.8%) believed that global risk-equations have limitations; 89.8% that equations overlook important risk factors, and 66.5% that they could not be used in elderly patients. Only 46.4% of physicians stated that their local healthcare framework was sufficient for primary prevention of CVD, while 67.2% stated that it was sufficient for secondary prevention of CVD.
A high proportion of physicians reported using clinical guidelines for primary CVD prevention. However, time constraints, lack of perceived usefulness and inadequate knowledge were common reasons for not using CVD prevention guidelines or global CVD risk assessment tools.
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ABSTRACT: Little is known on the prevalence of multimorbidity (MM) in the general population. We aimed to assess the prevalence of MM using measured or self-reported data in the Swiss population. Cross-sectional, population-based study conducted between 2003 and 2006 in the city of Lausanne, Switzerland, and including 3714 participants (1967 women) aged 35 to 75 years. Clinical evaluation was conducted by thoroughly trained nurses or medical assistants and the psychiatric evaluation by psychologists or psychiatrists. For psychiatric conditions, two definitions were used: either based on the participant's statements, or on psychiatric evaluation. MM was defined as presenting ≥2 morbidities out of a list of 27 (self-reported - definition A, or measured - definition B) or as the Functional Comorbidity Index (FCI) using measured data - definition C. The overall prevalence and (95% confidence interval) of MM was 34.8% (33.3%-36.4%), 56.3% (54.6%-57.9%) and 22.7% (21.4%-24.1%) for definitions A, B and C, respectively. Prevalence of MM was higher in women (40.2%, 61.7% and 27.1% for definitions A, B and C, respectively, vs. 28.7%, 50.1% and 17.9% in men, p < 0.001); Swiss nationals (37.1%, 58.8% and 24.8% for definitions A, B and C, respectively, vs. 31.4%, 52.3% and 19.7% in foreigners, all p < 0.001); elderly (>65 years: 67.0%, 70.0% and 36.7% for definitions A, B and C, respectively, vs. 23.6%, 50.2% and 13.8% for participants <45 years, p < 0.001); participants with lower educational level; former smokers and obese participants. Multivariate analysis confirmed most of these associations: odds ratio (95% Confidence interval) 0.55 (0.47-0.64), 0.61 (0.53-0.71) and 0.51 (0.42-0.61) for men relative to women for definitions A, B and C, respectively; 1.27 (1.09-1.49), 1.29 (1.11-1.49) and 1.41 (1.17-1.71) for Swiss nationals relative to foreigners, for definitions A, B and C, respectively. Conversely, no difference was found for educational level for definitions A and B and abdominally obese participants for all definitions. Prevalence of MM is high in the Lausanne population, and varies according to the definition or the data collection method.BMC Public Health 12/2015; 15(1). DOI:10.1186/s12889-015-1515-x · 2.32 Impact Factor
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ABSTRACT: Lifestyle interventions have proven effective for lowering a cardiovascular risk profile by improving lifestyle behaviors, blood glucose and blood cholesterol levels. However, implementation of lifestyle interventions is often met with barriers. This qualitative study sought to determine anticipated barriers and facilitators to the nationwide implementation of an effective lifestyle intervention in the construction industry in the Netherlands. Prior to implementation, focus groups were held with 8 lifestyle counselors and semi-structured interviews with 20 employees of the construction industry, 4 occupational physicians, 4 medical assistants, and 1 manager of an occupational health service. The transcripts were coded by two coders and analyzed by constant comparison. Hypothetical employee willingness to sign up for the intervention was facilitated by a high level of perceived risk, perceived added value of the intervention, and perceived social support. It was hampered by a preference for independence and perceived interference with their work. All professionals named a lack of time as an anticipated barrier to implementation. Lifestyle counselors suggested several strategies to improve the proficiency of their counseling technique, such as training in small groups and a continuous stream of employee referrals. Occupational physicians thought they would be hampered in screening employees and referring them to a lifestyle counselor by the perception that addressing employee lifestyles was not their task, and by a counter-productive relationship with other stakeholders. The manager addressed financial incentives and a good intervention fit with the current approach of the OHS. The findings suggest that employees can be motivated to sign up for a lifestyle intervention by tailoring the implementation strategy to various subgroups within the target group. Occupational physicians can be motivated to refer employees for the intervention by making a referral personally and professionally rewarding.BMC Public Health 12/2014; 14(1):1317. DOI:10.1186/1471-2458-14-1317 · 2.32 Impact Factor
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ABSTRACT: To analyse the treatment and control of dyslipidaemia in patients at high and very high cardiovascular risk being treated for the primary prevention of cardiovascular disease (CVD) in Europe. Data were assessed from the European Study on Cardiovascular Risk Prevention and Management in Usual Daily Practice (EURIKA, ClinicalTrials.gov identifier: NCT00882336), which included a randomly sampled population of primary CVD prevention patients from 12 European countries (n = 7641). Patients' 10-year risk of CVD-related mortality was calculated using the Systematic Coronary Risk Evaluation (SCORE) algorithm, identifying 5019 patients at high cardiovascular risk (SCORE ≥5% and/or receiving lipid-lowering therapy), and 2970 patients at very high cardiovascular risk (SCORE ≥10% or with diabetes mellitus). Among high-risk individuals, 65.3% were receiving lipid-lowering therapy, and 61.3% of treated patients had uncontrolled low-density lipoprotein cholesterol (LDL-C) levels (≥2.5 mmol/L). For very-high-risk patients (uncontrolled LDL-C levels defined as ≥1.8 mmol/L) these figures were 49.5% and 82.9%, respectively. Excess 10-year risk of CVD-related mortality (according to SCORE) attributable to lack of control of dyslipidaemia was estimated to be 0.72% and 1.61% among high-risk and very-high-risk patients, respectively. Among high-risk individuals with uncontrolled LDL-C levels, only 8.7% were receiving a high-intensity statin (atorvastatin ≥40 mg/day or rosuvastatin ≥20 mg/day). Among very-high-risk patients, this figure was 8.4%. There is a considerable opportunity for improvement in rates of lipid-lowering therapy use and achievement of lipid-level targets in high-risk and very-high-risk patients being treated for primary CVD prevention in Europe.PLoS ONE 02/2015; 10(2):e0115270. DOI:10.1371/journal.pone.0115270 · 3.53 Impact Factor