BackgroundNationally representative estimates of diabetes mellitus (DM) prevalence among HIV-infected adults in the USA are lacking, and whether HIV-infected adults are at increased risk of DM compared with the general adult population remains controversial.MethodsWe used nationally representative survey (2009–2010) data from the Medical Monitoring Project (n=8610 HIV-infected adults) and the National Health and Nutrition Examination Survey (n=5604 general population adults) and fit logistic regression models to determine and compare weighted prevalences of DM between the two populations, and examine factors associated with DM among HIV-infected adults.ResultsDM prevalence among HIV-infected adults was 10.3% (95% CI 9.2% to 11.5%). DM prevalence was 3.8% (CI 1.8% to 5.8%) higher in HIV-infected adults compared with general population adults. HIV-infected subgroups, including women (prevalence difference 5.0%, CI 2.3% to 7.7%), individuals aged 20–44 (4.1%, CI 2.7% to 5.5%), and non-obese individuals (3.5%, CI 1.4% to 5.6%), had increased DM prevalence compared with general population adults. Factors associated with DM among HIV-infected adults included age, duration of HIV infection, geometric mean CD4 cell count, and obesity.Conclusions1 in 10 HIV-infected adults receiving medical care had DM. Although obesity contributes to DM risk among HIV-infected adults, comparisons to the general adult population suggest that DM among HIV-infected persons may develop at earlier ages and in the absence of obesity.

On May 21, 2021, this report was posted as an MMWR Early Release on the MMWR website (https://www.cdc.gov/mmwr).To meet the educational, physical, social, and emotional needs of children, many U.S. schools opened for in-person learning during fall 2020 by implementing strategies to prevent transmission of SARS-CoV-2, the virus that causes COVID-19 (1,2). To date, there have been no U.S. studies comparing COVID-19 incidence in schools that varied in implementing recommended prevention strategies, including mask requirements and ventilation improvements* (2). Using data from Georgia kindergarten through grade 5 (K-5) schools that opened for in-person learning during fall 2020, CDC and the Georgia Department of Public Health (GDPH) assessed the impact of school-level prevention strategies on incidence of COVID-19 among students and staff members before the availability of COVID-19 vaccines. † Among 169 K-5 schools that participated in a survey on prevention strategies and reported COVID-19 cases during November 16-December 11, 2020, COVID-19 incidence was 3.08 cases among students and staff members per 500 enrolled students. § Adjusting for county-level incidence, COVID-19 incidence was 37% lower in schools that required teachers and staff members to use masks, and 39% lower in schools that improved ventilation, compared with schools that did not use these prevention strategies. Ventilation strategies associated with lower school incidence included methods to dilute airborne particles alone by opening windows, opening doors, or using fans (35% lower incidence), or in combination with methods to filter airborne particles with high-efficiency particulate absorbing (HEPA) filtration with or without purification with ultraviolet germicidal irradiation (UVGI) (48% lower incidence). Multiple strategies should be implemented * Ventilation strategies include dilution methods (opening doors, opening windows, and using fans to improve circulation from open windows); filtration methods (installation of high-efficiency particulate absorbing [HEPA] filters); and purification methods (installation of ultraviolet germicidal irradiation [UVGI] units, installed in upper room areas and shielded from persons or installed in the heating, ventilation, and air conditioning [HVAC] system).

Background Cardiovascular disease (CVD) risk prediction tools are often applied to populations beyond those in which they were designed when validated tools for specific subpopulations are unavailable. Methods Using data from 2283 human immunodeficiency virus (HIV)–infected adults aged ≥18 years, who were active in the HIV Outpatient Study (HOPS), we assessed performance of 3 commonly used CVD prediction models developed for general populations: Framingham general cardiovascular Risk Score (FRS), American College of Cardiology/American Heart Association Pooled Cohort equations (PCEs), and Systematic COronary Risk Evaluation (SCORE) high-risk equation, and 1 model developed in HIV-infected persons: the Data Collection on Adverse Effects of Anti-HIV Drugs (D:A:D) study equation. C-statistics assessed model discrimination and the ratio of expected to observed events (E/O) and Hosmer-Lemeshow χ2 P value assessed calibration. Results From January 2002 through September 2013, 195 (8.5%) HOPS participants experienced an incident CVD event in 15 056 person-years. The FRS demonstrated moderate discrimination and was well calibrated (C-statistic: 0.66, E/O: 1.01, P = .89). The PCE and D:A:D risk equations demonstrated good discrimination but were less well calibrated (C-statistics: 0.71 and 0.72 and E/O: 0.88 and 0.80, respectively; P < .001 for both), whereas SCORE performed poorly (C-statistic: 0.59, E/O: 1.72; P = .48). Conclusions Only the FRS accurately estimated risk of CVD events, while PCE and D:A:D underestimated risk. Although these models could potentially be used to rank US HIV-infected individuals at higher or lower risk for CVD, the models may fail to identify substantial numbers of HIV-infected persons with elevated CVD risk who could potentially benefit from additional medical treatment.

Pooled analyses of available randomized controlled trials suggest that CoQ₁₀ may improve the EF in patients with CHF. Additional well-designed studies that include more diverse populations are needed.

These members of the evidence review committee are listed alphabetically, and all participated equally in the process. †The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. ‡Former Task Force member; current member during the writing effort. Copies: This document is available on the websites of the American College of Cardiology (www.acc.org) and the American Heart Association (professional.heart.org). A copy of the document is available at http://professional.heart.org/statements by using either "Search for Guidelines & Statements" or the "Browse by Topic" area. To purchase additional reprints, call 843-216-2533 or e-mail kelle.ramsay@wolterskluwer.com.Expert peer review of AHA Scientific Statements is conducted by the AHA Office of Science Operations. For more on AHA statements and guidelines development, visit http://professional.heart.org/statements. Select the "Guidelines & Statements" drop-down menu, then click "Publication Development."Permissions: Multiple copies, modification, alteration, enhancement, and/or distribution of this document are not permitted without the express permission of the American Heart Association. Instructions for obtaining permission are located at http://www.heart.org/HEARTORG/General/Copyright-Permission-Guidelines_UCM_300404_Article.jsp. A link to the "Copyright Permissions Request Form" appears on the right side of the page. With Hypertension .................................................................................................................................. 7 Introduction: Part 1 ............................................................................................................................ 1 ................................................................................................................................. 1 ....................................................................................................................... 1 .................................................................................................................................... ........................................................................................................................ 2 ................................................................................................................................ 2 ................................................................................................................................... ............................................................................................................................. ...................................................................................................................... 33 References ........................................................................................................................................ AbstractObjective: To review the literature systematically and perform meta-analyses to ...