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Abstract. Salazar MR, Carbajal HA, Espeche WG, Aizpur ua M,

This study compares the ability of an elevated triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) ratio, using sex-specific cut-points, to identify insulin-resistant individuals within a population without known cardiac disease or diabetes with that obtained using the diagnostic criteria of the metabolic syndrome (MetS). Measurements were made of waist circumference (WC), systolic and diastolic blood pressure, fasting plasma glucose, fasting plasma insulin (FPI), plasma TG and plasma HDL-C concentrations in 1102 women and 464 men. These data were used to classify subjects as being insulin resistant (FPI concentration in the upper quartile) and having the MetS or an elevated TG/HDL-C ratio (>2.5 and >3.5 for women and men, respectively). The sensitivity and specificity with which the two indices identified insulin-resistant subjects were similar (43% and 81% for TG/HDL-C ratio and 45% and 82% for MetS), as the number of individuals was found with either an elevated TG/HDL-C ratio (n = 386) or the MetS (n = 384). Eighty-one per cent of the individuals were identified concordantly. Cardio-metabolic risk profiles in ‘low-risk’ individuals identified by a low TG/HDL-C ratio were comparable to those who did not have the MetS, and this was also the case when comparing ‘high-risk’ groups identified by having the MetS or an elevated TG/HDL-C ratio. These findings suggest that TG/HDL-C concentration ratio is as adequate as MetS diagnosis to identify insulin-resistant subjects.

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The aim of this study is to test the hypotheses that: 1) diagnosing the metabolic syndrome does not effectively identify insulin-resistant (IR) individuals; and 2) waist circumference (WC) is no better than body mass index (BMI) in predicting insulin resistance or the components of the metabolic syndrome (MetS). Measurements of BMI, WC, blood pressure, and fasting plasma glucose, insulin (FPI), triglycerides (TG), and HDL-cholesterol (HDL-C) concentrations were made in 1,300 adults, without known cardiovascular disease (CVD) or drug treatment of hypertension or diabetes. Receiver operating characteristic curves were used to determine the ability of the MetS, and its components, to identify IR individuals. In addition, comparisons were made of CVD risk factors following division of the population into quartiles of FPI concentrations, and univariate and multiple regression analysis used to compare the ability of WC, BMI, and FPI as predictors of MetS components. The MetS was no more effective in identifying IR individuals than several individual components (sensitivity~40%), and IR individuals not identified were at significantly increased CVD risk. FPI concentration was the best predictor of an abnormal glucose, TG, and HDL-C, whereas the adiposity indices were better predictors of abnormal blood pressure. The relationship between BMI and WC with the MetS and its components seemed comparable.

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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.