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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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Background A first-dose of various vaccines provides acceptable protection against infections by SARS-CoV-2 and evolution to the most severe forms of COVID-19. The recombinant adenovirus (rAd)-based vaccine, Gam-COVID-Vac (Sputnik V), was proven efficacious but information about effectiveness in the real-world setting is lacking. The aim of our study was to investigate the association between the rollout of the first component (rAd26) of Gam-COVID-Vac and PCR-positive tests, hospitalisations and deaths. Methods We conducted a retrospective cohort study which analyzed individuals aged 60-79 who self-registered in the online vaccination system of the Province of Buenos Aires, Argentina, from December 29, 2020 to March 21, 2021. Exclusion criteria were having a previous positive RT-PCR or antigen tests for SARS-CoV-2, having received other vaccines, or two doses of any vaccine. Proportions of new laboratory-confirmed SARS-CoV-2 infections, hospitalisations and deaths until 83 days of vaccination were compared between vaccinated and unvaccinated subjects. Vaccine effectiveness for the three outcomes was calculated as (1–OR) × 100. Kaplan-Meier cumulative incidence curves were constructed. Findings During the study period 415995 registered subjects received the first component of Gam-COVID-Vac; 40387 belonged to the 60-79 age group, and were compared to 38978 unvaccinated. Vaccine effectiveness for preventing laboratory-confirmed infections was 78•6% [CI 95% 74·8 - 81·7]; and for reducing hospitalizations and deaths was, respectively, 87·6% [CI 95% 80·3 - 92·2] and 84·8% [CI 95% 75·0 - 90·7]. Effectiveness was high across all subgroups. Interpretation Similarly to other vaccines, the administration of one dose of Gam-COVID-Vac was effective for a wide range of COVID-19–related outcomes. Funding This study did not receive any funding.

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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