Objectives:
To estimate the prevalence of isolated nocturnal hypertension (INH) and its relationships with office blood pressure (BP) categories defined by 2018 ESC/ESH guidelines.
Methods:
We conducted a prospective cohort study in consecutive patients referred to perform an ambulatory blood pressure monitoring (ABPM) for diagnosis or therapeutic purposes. Office BP measurements and ABPM were performed in the same visit. The cohort was divided according to office BP in optimal, normal, high-normal and hypertension. The prevalence and adjusted risk for combined daytime and nocturnal hypertension and INH were estimated for each category.
Results:
We evaluated 1344 individuals, 59.3% women (51 ± 14 years old) and 40.7% men (52 ± 15 years old). 61.5% of the individuals had nocturnal hypertension, 12.9% INH and 48.7% combined daytime and nocturnal hypertension. Prevalence of combined daytime and nocturnal hypertension increased through office BP categories (P < 0.001). Conversely, prevalence of INH was lower in individuals with hypertension than in normotensives (7.4 vs. 17.2%, P < 0.001) and similar between nonhypertensive office BP categories, 16.6, 15 and 19.4% for optimal, normal and high-normal BP, respectively (P < 0.399). In individuals with office BP values less than 140/90 mmHg, the prevalence of masked hypertension phenotypes were 8.6, 17.2 and 30.2% for daytime, INH and combined daytime and nocturnal hypertension, respectively. Adjusted risk for combined daytime and nocturnal hypertension increased significantly through office BP categories; conversely, the risk for INH was similar in all nonhypertensive office BP categories.
Conclusion:
Nocturnal hypertension was the more prevalent phenotype of masked hypertension and more than one-third of the individuals with nocturnal hypertension had INH. The risk for INH was not related to nonhypertensive office BP categories.
Masked and nocturnal hypertension are frequent findings in normotensive women coursing a high-risk pregnancy, and their presence implies an increased risk to develop PEEC.
The aim of this study was to test the hypothesis that cardiovascular disease occurs to the greatest extent in persons with prediabetes mellitus who are also insulin resistant. In 2003, 664 non-diabetic women (n = 457) and men (n = 207), aged 52 ± 16 and 53 ± 15 years, were surveyed during a programme for cardiovascular disease prevention. Fasting plasma glucose concentrations defined participants as having normal fasting plasma glucose (fasting plasma glucose <5.6 mmol/L) or prediabetes mellitus (fasting plasma glucose ⩾ 5.6 and <7.0 mmol/L). The tertile of prediabetes mellitus subjects with the highest fasting plasma insulin concentration was classified as insulin resistant. Baseline cardiovascular disease risk factors were accentuated in prediabetes mellitus versus normal fasting glucose, particularly in prediabetes mellitus/insulin resistant. In 2012, 86% of the sample were surveyed again, and the crude incidence for cardiovascular disease was higher in subjects with prediabetes mellitus versus normal fasting glucose (13.7 vs 6.0/100 persons/10 years; age- and sex-adjusted hazard ratio = 1.88, p = 0.052). In prediabetes mellitus, the crude incidences were 22.9 versus 9.6/100 persons/10 years in insulin resistant versus non-insulin resistant persons (age- and sex-adjusted hazard ratio = 2.36, p = 0.040). In conclusion, cardiovascular disease risk was accentuated in prediabetes mellitus/insulin resistant individuals, with a relative risk approximately twice as high compared to prediabetes mellitus/non-insulin resistant subjects.
We evaluated the consequences of excluding the first of three blood pressure (BP) readings in different settings: a random population sample (POS, n=1525), a general practice office (GPO, n=942) and a specialized hypertension center (SHC, n=462). Differences between systolic and diastolic BP (SBP and DBP) estimates obtained including and excluding the first reading were compared and their correlation with ambulatory BP monitoring (ABPM) was estimated. The samples were divided into quartiles according to the difference between the third and the first SBP (3-1ΔSBP). SBP decreased through sequential readings, 3-1ΔSBP was -5.5 ± 9.7 mm Hg (P<0.001), -5.1 ± 10.4 mm Hg (P<0.001) and -6.1 ± 9.3 mm Hg (P<0.001) for POS, GPO and SHC, respectively. However, individuals included in the top quartile of 3-1ΔSBP showed their highest values on the third reading. The mean SBP estimate was significantly higher excluding the first reading (P<0.001), but the differences among both approaches were small (1.5-1.6 mm g). Moreover, the correlation between SBP values including and excluding the first reading and daytime ABPM were comparable (r = 0.69 and 0.68, respectively). Similar results were observed for DBP. In conclusion, our study does not support the notion of discarding the first BP measurement and suggests that it should be measured repeatedly, regardless the first value.
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