METHODS: A cross-sectional study was conducted between November 2020 and January 2021. A self-administered questionnaire was distributed to 350 physicians (GPs, residents, specialists, and consultants). Two trained pharmacists distributed the questionnaires in 5 major tertiary governmental hospitals and more than ten private hospitals. Also, private clinics were targeted so that we get a representative sample of physicians at different workplaces.
RESULTS: A total of 270 physicians filled the questionnaire out of 350 physicians approached, with 14 being excluded due to high missing data, giving a final response rate of 73%. Participants had suboptimal knowledge and practices with a high positive attitude toward atherosclerotic cardiovascular diseases risk assessment. The knowledge and practices were higher among consultants, participants from the cardiology department, those with experience years of more than nine years, and those who reported following a specific guideline for cholesterol management or using a risk calculator in their practice. Notably, the risk assessment and counseling practices were lower among physicians who reported seeing more patients per day.
CONCLUSION: Physicians had overall low knowledge, suboptimal practices, and a high positive attitude toward cardiovascular risk assessment. Therefore, physicians' training and continuing medical education regarding cholesterol management and primary prevention clinical practice guidelines are recommended. Also, the importance of adherence to clinical practice guidelines and their impact on clinical outcomes should be emphasized.
OBJECTIVE: This systematic review and meta-analysis aimed to determine the effectiveness of mobile applications on medication adherence, functional outcomes, cardiovascular risk factors, quality of life and knowledge on stroke in stroke survivors.
METHODS: A review of the literature was conducted using key search terms in PubMed, EMBASE, Cochrane and Web of Science databases until 16 March 2023 to identify eligible randomized controlled trials (RCTs) or controlled clinical trial (CCTs) of mobile application interventions among stroke survivors. Two reviewers independently screened the literature in accordance with the eligibility criteria and collected data from the articles included. Outcomes included medication adherence,functional outcomes,cardiovascular risk factors, quality of life,and knowledge of stroke.
RESULTS: Twenty-three studies involving 2983 participants across nine countries were included in this review. Sixteen trials involved health care professionals in app use, and seven trials reported measures to ensure app-based intervention adherence. Mobile applications targeting stroke survivors primarily encompassed three areas: rehabilitation, education and self-care. The participants in the studies primarily included young and middle-aged stroke survivors. Meta-analysis results demonstrated that mobile application intervention significantly improved trunk control ability (mean differences [MD] 3.00, 95% CI [1.80 to 4.20]; P cholesterol (MD - 0.33, 95% CI [- 0.54 to - 0.11]; P = 0.003) and glycosylated haemoglobin A1c (HbA1c)<7 levels (MD 1.95, 95% CI [1.17 to 3.25]; P = 0.01). However, the mobile application intervention did not differ significantly in medication adherence, 10-min walk test (10 MWT), Barthel index, systolic blood pressure, diastolic blood pressure, high-density lipoprotein cholesterol, body mass index, smoking, health-related quality of life and knowledge of stroke.
CONCLUSION: Our study suggested that mobile application interventions may have a potential benefit to stroke survivors, but clinical effectiveness should be established. More studies using rigorous designs are warranted to understand their usefulness. Future research should also involve more older adult stroke survivors.
Methods: This case-control study was carried out on 113 patients with PV and 100 healthy controls. Total cholesterol, high-density lipoprotein (HDL) and triglycerides (TG) levels were measured and low-density lipoprotein (LDL), non-HDL cholesterol (non-HDL-C) and atherogenic index of plasma (AIP) were calculated. Chi-squared test and independent Student t-test (or their alternatives) were used for group comparison.
Results: The mean age and BMI of patients and controls were 47.7 ± 14.5 and 28 ± 6.2 and, 44.5 ± 18.5 and 25.5 ± 5.1, respectively. Total cholesterol, LDL, HDL, non-HDL-C and TG were statistically different between the two groups (P values < 0.001; < 0.001; < 0.001; < 0.001 and 0.021, respectively). However, AIP was not significantly different (P-value = 0.752).
Conclusion: The serum lipid profile was significantly higher in PV patients compared to healthy controls. Therefore, PV patients may be more prone to develop atherosclerosis and this finding can be important in the overall management of these patients.
METHODS: This was a cross-sectional population based study with data on occupational social class, educational level obtained using a detailed health and lifestyle questionnaire. A total of 10,147 men and 12,304 women aged 45-80 years living in Norfolk, United Kingdom, were recruited using general practice age-sex registers as part of the European Prospective Investigation into Cancer (EPIC-Norfolk). Plasma levels of cholesterol and triglycerides were measured in baseline samples. Social class was classified according to three classifications: occupation, educational level, and area deprivation score according to Townsend deprivation index. Differences in lipid levels by socio-economic status indices were quantified by analysis of variance (ANOVA) and multiple linear regression after adjusting for body mass index and alcohol consumption.
RESULTS: Total cholesterol levels were associated with occupational level among men, and with educational level among women. Triglyceride levels were associated with educational level and occupational level among women, but the latter association was lost after adjustment for age and body mass index. HDL-cholesterol levels were associated with both educational level and educational level among men and women. The relationships with educational level were substantially attenuated by adjustment for age, body mass index and alcohol use, whereas the association with educational class was retained upon adjustment. LDL-cholesterol levels were not associated with social class indices among men, but a positive association was observed with educational class among women. This association was not affected by adjustment for age, body mass index and alcohol use.
CONCLUSIONS: The findings of this study suggest that there are sex differences in the association between socio-economic status and serum lipid levels. The variations in lipid profile with socio-economic status may be largely attributed to potentially modifiable factors such as obesity, physical activity and dietary intake.