Quinlanglud4957

Sex differences in the antihypertensive medications used to control blood pressure and risk factor control in hypertensive patients is poorly understood.

We conducted a retrospective review of the patients newly diagnosed with hypertension registered for treatment in 52 outpatient settings across Abu Dhabi province between 1 January and 31 December 2017. We explored sex differences in risk factors and treatment management over 6 months of the follow-up period of each patient. Multiple logistic regression models were used to identify factors associated with poor BP control.

A total of 5308 patients (2559 men and 2849 women) were identified. We observed an increase in SBP and DBP levels in men (1.72/1.13 mmHg) and only SBP in women (0.87/-0.021 mmHg) with increased incidence of comorbidities overtime. learn more The overall BP control was suboptimal (65%) (<140/90 mmHg) with no significant difference between women (65.3%) and men (64.2%). In men with dyslipidemia, use of angiotensin-converting enzyme inhibitor or angiotensin receptor blocker with diuretics and in women, only calcium channel blockers showed higher for BP control. Factors significantly associated with poor BP control in men are being overweight and obese, and dyslipidemia in men. After the age of 50, women in contrast to men, with dyslipidemia and heart rate >80 beats per minute are less likely to maintain hypertension control.

Sex-specific analysis indicated that BP control among United Arab Emirates men and women was suboptimal (65%). Interventions aiming to achieve better control of BP in hypertensive patients with metabolic syndrome should be emphasized.

Sex-specific analysis indicated that BP control among United Arab Emirates men and women was suboptimal (65%). Interventions aiming to achieve better control of BP in hypertensive patients with metabolic syndrome should be emphasized.

Blood pressure (BP) abstracted from electronic medical records (EMR) is moderately correlated to BP in nonpregnant adults with limited agreement. Little is known about the agreement of research versus EMR BP measured during pregnancy or associations of EMR BP with hypertensive disorder of pregnancy (HDP) diagnoses.

BP was measured according to guidelines at in-person research study visits in 214 women with prepregnancy overweight or obesity (44.4% African American, mean age = 29.8 ± 4.8 years) at weeks 16 and 32 of pregnancy. Clinic BP readings that occurred within 1 week of the study visits were abstracted from the EMR. We assessed correlations between sources using Pearson's coefficients; the agreement was evaluated with Bland-Altman plots. We compared differences in the proportion of women with an HDP diagnosis in the EMR between women with versus without a hypertensive EMR BP measurement.

SBP and DBP from study visits and the EMR were modestly moderately correlated at both time points; 0.20 < r < 0.44; P < 0.05 for all. The average mean difference was 10.5 mmHg for SBP and <1 mmHg for DBP in early and 7.3 mmHg for SBP and -1.7 mmHg for DBP in late pregnancy. Women with at least one hypertensive BP reading in the EMR were more likely to have an HDP diagnosis recorded in the EMR; 43.5 versus 3.3%; P < 0.01.

EMR SBP was higher but moderately correlated with research quality BP in early and late pregnancy. Women with a hypertensive EMR BP measurement were more likely to have an HDP diagnosis in the EMR.

EMR SBP was higher but moderately correlated with research quality BP in early and late pregnancy. Women with a hypertensive EMR BP measurement were more likely to have an HDP diagnosis in the EMR.

Accurate measurement of blood pressure (BP) is crucial to hypertension control and prevention of future stroke and heart attack. All BP measuring devices must be validated independently in the clinical setting.

To validate the accuracy of three automatic upper arm devices (Omron HEM-7120, Yuwell YE680A and Cofoe KF-65B) for self-measurement of BP in Chinese adults with arm size of 22-32 cm.

The validation was conducted independently for each of the three devices according to the European Society of Hypertension International Protocol revision 2010 (ESH-IP revision 2010), with the facilitation of a designated smartphone application. Subjects were recruited from those attending Beijing Anzhen Hospital for routine physical examination and clinic visits. For each device, BP was measured sequentially in 33 adults using a mercury sphygmomanometer (two observers) and the test device (one supervisor) with seven measurements alternating between observers and the device, which generated a total of 99 before/afterYuwell YE680A and Cofoe KF-65B failed (part 3).To limit the spread of the novel coronavirus, governments across the world implemented extraordinary physical distancing policies, such as stay-at-home orders. Numerous studies aim to estimate the effects of these policies. Many statistical and econometric methods, such as difference-in-differences, leverage repeated measurements, and variation in timing to estimate policy effects, including in the COVID-19 context. Although these methods are less common in epidemiology, epidemiologic researchers are well accustomed to handling similar complexities in studies of individual-level interventions. Target trial emulation emphasizes the need to carefully design a nonexperimental study in terms of inclusion and exclusion criteria, covariates, exposure definition, and outcome measurement-and the timing of those variables. We argue that policy evaluations using group-level longitudinal ("panel") data need to take a similar careful approach to study design that we refer to as policy trial emulation. This approach is especially important when intervention timing varies across jurisdictions; the main idea is to construct target trials separately for each treatment cohort (states that implement the policy at the same time) and then aggregate. We present a stylized analysis of the impact of state-level stay-at-home orders on total coronavirus cases. We argue that estimates from panel methods-with the right data and careful modeling and diagnostics-can help add to our understanding of many policies, though doing so is often challenging.