心血管病(英文)最新文献

Background: Molecular testing is considered the gold standard for the detection of SARS-CoV-2. This study aimed to compare the performance of the P742H SARS-CoV-2 Nucleic Acid Multiplex Detection Kit in salivary samples, with respect to the 732HF Novel Coronavirus (2019-nCoV) Nucleic Acid Detection Kit and the TaqPath COVID-19 CEIVD RT-PCR Kit, used at University-Hospital of Padova, Italy.

Methods: One hundred twenty-four salivary samples selfcollected by healthcare workers (HCW) during the screening program at University-Hospital of Padova, Italy, from Oct to Nov 2022, were included in the study. RNA extraction was performed by Viral DNA and RNA Extraction Kit (Technogenetics, Lodi, Italy) and amplification by P742H and 732HF (Technogenetics, Lodi, Italy). RNA was extracted using MagNa Pure 96 DNA and Viral NA Small Volume Kit (Roche, Switzerland) for TaqPath analysis (Thermo Fisher Scientific, USA).

Background and objective: A multitude of large cohort studies have collected data on incidence and covariates/risk factors of various chronic diseases. However, approaches for utilization of these large data and translation of the valuable results to inform and guide clinical disease prevention practice are not well developed. In this paper, we proposed, based on large cohort study data, a novel conceptual cost-effective disease prevention design strategy for a target group when it is not affordable to include everyone in the target group for intervention.

Methods and results: Data from American Indian participants (n = 3516; 2056 women) aged 45 - 74 years in the Strong Heart Study, the diabetes risk prediction model from the study, a utility function, and regression models were used. A conceptual cost-effective disease prevention design strategy based on large cohort data was initiated. The application of the proposed strategy for diabetes prevention was illustrated.

Discussion: The strategy may provide reasonable solutions to address cost-effective prevention design issues. These issues include complex associations of a disease with its significant risk factors, cost-effectively selecting individuals at high risk of developing disease to undergo intervention, individual differences in health conditions, choosing intervention risk factors and setting their appropriate, attainable, gradual and adaptive goal levels for different subgroups, and assessing effectiveness of the prevention program.

Conclusions: The strategy and methods shown in the illustrative example can also be analogously adopted and applied to other diseases preventions. The proposed strategy provides a way to translate and apply epidemiological study results to clinical disease prevention practice.

Background and objective: A multitude of large cohort studies have data on incidence rates and predictors of various chronic diseases. However, approaches for utilization of these costly collected data and translation of these valuable results to inform and guide clinical disease prevention practice are not well developed. In this paper we proposed a novel conceptual group/community disease prevention design strategy based on large cohort study data.

Methods and results: The data from participants (n = 3516; 2056 women) aged 45 to 74 years and the diabetes risk prediction model from Strong Heart Study were used. The Strong Heart Study is a population-based cohort study of cardiovascular disease and its risk factors in American Indians. A conceptual group/community disease prevention design strategy based on large cohort data was initiated. The application of the proposed strategy for group diabetes prevention was illustrated.

Discussion: The strategy may provide reasonable solutions to the prevention design issues. These issues include complex associations of a disease with its combined and correlated risk factors, individual differences, choosing intervention risk factors and setting their appropriate, attainable, gradual and adaptive goal levels for different subgroups, and assessing effectiveness of the prevention program.

Conclusions: The strategy and methods shown in the illustration example can be analogously adopted and applied for other diseases preventions. The proposed strategy for a target group/community in a population provides a way to translate and apply epidemiological study results to clinical disease prevention practice.

Background and objective: American Indians have a high prevalence of diabetes and higher incidence of stroke than that of whites and blacks in the U.S. Stroke risk prediction models based on data from American Indians would be of clinical and public health value.

Methods and results: A total of 3483 (2043 women) Strong Heart Study participants free of stroke at baseline were followed from 1989 to 2010 for incident stroke. Overall, 297 stroke cases (179 women) were identified. Cox models with stroke-free time and risk factors recorded at baseline were used to develop stroke risk prediction models. Assessment of the developed stroke risk prediction models regarding discrimination and calibration was performed by an analogous C-statistic (C) and a version of the Hosmer-Lemeshow statistic (HL), respectively, and validated internally through use of Bootstrapping methods.

Results: Age, smoking status, alcohol consumption, waist circumference, hypertension status, an-tihypertensive therapy, fasting plasma glucose, diabetes medications, high/low density lipoproteins, urinary albumin/creatinine ratio, history of coronary heart disease/heart failure, atrial fibrillation, or Left ventricular hypertrophy, and parental history of stroke were identified as the significant optimal risk factors for incident stroke.

Discussion: The models produced a C = 0.761 and HL = 4.668 (p = 0.792) for women, and a C = 0.765 and HL = 9.171 (p = 0.328) for men, showing good discrimination and calibration.

Conclusions: Our stroke risk prediction models provide a mechanism for stroke risk assessment designed for American Indians. The models may be also useful to other populations with high prevalence of obesity and/or diabetes for screening individuals for risk of incident stroke and designing prevention programs.

Background: Resting ischemic electrocardiographic abnormalities have been associated with cardiovascular mortality. Simple markers of abnormal autonomic tone have also been associated with diabetes, obesity, and the metabolic syndrome in some populations. Data on these electrocardiographic abnormalities and correlations with coronary risk factors are lacking among Mexican Americans wherein these conditions are prevalent.

Objective: This study aimed to evaluate the prevalent resting electrocardiographic abnormalities among community-dwelling Mexican Americans, and correlate these findings with coronary risk factors, particularly diabetes, obesity, and the metabolic syndrome.

Methods: Study subjects (n=1280) were drawn from the Cameron County Hispanic Cohort comprised of community-dwelling Mexican Americans living in Brownsville, Texas at the United States-Mexico border. Ischemic electrocardiographic abnormalities were defined as presence of ST/T wave abnormalities suggestive of ischemia, abnormal Q waves, and left bundle branch block. Parameters that reflect autonomic tone, such as heart rate-corrected QT interval and resting heart rate, were also measured.

Results: Ischemic electrocardiographic abnormalities were more prevalent among older persons and those with hypertension, diabetes, obesity, and the metabolic syndrome. Subjects in the highest quartiles of QTc interval and resting heart rate were also more likely to be diabetic, hypertensive, obese, or have the metabolic syndrome.

Conclusions: Among Mexican Americans, persons with diabetes, obesity, and the metabolic syndrome were more likely to have ischemic electrocardiographic abnormalities, longer QTc intervals, and higher resting heart rates. A resting electrocardiogram can play a complementary role in the comprehensive evaluation of cardiovascular risk in this minority population.

OBJECTIVE: In a recent study, we showed that the combination of aspirin plus the omega-3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) synergistically inhibited platelet function. As aspirin, EPA, and DHA have demonstrated anti-inflammatory properties, we hypothesized that the ingestion of EPA and DHA, with and without aspirin, would reduce plasma levels of inflammatory cytokines and angiogenesis factors more than aspirin alone and before aspirin was ingested. METHODS: Using multiplex technology, we investigated the effects of aspirin (single-dose 650 mg on day 1), EPA+DHA (3.4 g/d for days 2-29), and aspirin with EPA+DHA (day 30) on plasma levels of inflammatory cytokines and angiogenesis factors in healthy adults. RESULTS: Aspirin alone had no effect on any factor versus baseline, but EPA+DHA, with and without aspirin, significantly reduced concentrations of 8 of 9 factors. Although EPA+DHA plus aspirin reduced concentrations of a subset of the factors compared to baseline, neither aspirin alone nor the combination significantly reduced the level of any analyte more robustly than EPA+DHA alone. CONCLUSIONS: These data suggest that EPA+DHA has more pronounced down-regulatory effects on inflammation and angiogenesis than aspirin. The implications of these findings for the use of combined therapy for cardiovascular disease remain to be clarified.