Risk of incident diabetes after COVID-19 infection: A systematic review and meta-analysis.

BACKGROUND: COVID-19 might be a risk factor for various chronic diseases. However, the association between COVID-19 and the risk of incident diabetes remains unclear. We aimed to meta-analyze evidence on the relative risk of incident diabetes in patients with COVID-19. METHODS: In this systematic review and meta-analysis, the Embase, PubMed, CENTRAL, and Web of Science databases were searched from December 2019 to June 8, 2022. We included cohort studies that provided data on the number, proportion, or relative risk of diabetes after confirming the COVID-19 diagnosis. Two reviewers independently screened studies for eligibility, extracted data, and assessed risk of bias. We used a random-effects meta-analysis to pool the relative risk with corresponding 95 % confidence intervals. Prespecified subgroup and meta-regression analyses were conducted to explore the potential influencing factors. We converted the relative risk to the absolute risk difference to present the evidence. This study was registered in advance (PROSPERO CRD42022337841). MAIN FINDINGS: Ten articles involving 11 retrospective cohorts with a total of 47.1 million participants proved eligible. We found a 64 % greater risk (RR = 1.64, 95%CI: 1.51 to 1.79) of diabetes in patients with COVID-19 compared with non-COVID-19 controls, which could increase the number of diabetes events by 701 (558 more to 865 more) per 10,000 persons. We detected significant subgroup effects for type of diabetes and sex. Type 2 diabetes has a higher relative risk than type 1. Moreover, men may be at a higher risk of overall diabetes than women. Sensitivity analysis confirmed the robustness of the results. No evidence was found for publication bias. CONCLUSIONS: COVID-19 is strongly associated with the risk of incident diabetes, including both type 1 and type 2 diabetes. We should be aware of the risk of developing diabetes after COVID-19 and prepare for the associated health problems, given the large and growing number of people infected with COVID-19. However, the body of evidence still needs to be strengthened.

The distribution of SARS-CoV-2 contamination on the environmental surfaces during incubation period of COVID-19 patients.

Roles of environmental factors in transmission of COVID-19 have been highlighted. In this study, we sampled the high-touch environmental surfaces in the quarantine room, aiming to detect the distribution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on the environmental surfaces during the incubation period of coronavirus disease 2019 (COVID-19) patients. Fifteen sites were sampled from the quarantine room, distributing in the functional areas such as bedroom, bathroom and living room. All environmental surface samples were collected with sterile polyester-tipped applicator pre-moistened in viral transport medium and tested for SARS-CoV-2. Overall, 34.1% of samples were detected positively for SARS-CoV-2. The positive rates of Patient A, B and C, were 46.2%, 0% and 61.5%, respectively. SARS-CoV-2 was detected positively in bedroom and bathroom, with the positive rate of 50.0% and 46.7%, respectively. In contrast, living room had no positive sample detected. Environmental contamination of SARS-CoV-2 distributes widely during the incubation period of COVID-19, and the positive rates of SARS-CoV-2 on environmental surfaces are relatively high in bathroom and bedroom.

Coronavirus disease (COVID 2019): protocol for a living overview of systematic reviews.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic continues to grow worldwide, and systematic reviews (SRs)/meta-analyses (MAs) on COVID-19 can efficiently guide evidence-based clinical practice. However, SRs/MAs with weaknesses can mislead clinical practice and pose harm to patients, and too many useless SRs/MAs could pose confusion and waste sources. A "living" overview of SRs/MAs aims to provide an open, accessible and frequently updated resource summarizing the highest-level evidence of COVID-19, that can help evidence-users to quickly identify trusted evidence to guide the practice. This study aims to systematically give an overview SRs/MAs of COVID-19, assess their quality, and identify the best synthesis of evidence. METHODS: Databases including Medline, EMBASE, Web of Science, China National Knowledge Infrastructure (CNKI), China Biology Medicine (CBM) and WanFang were systematically searched on May 1, 2020 using relevant terms for identify SRs/MAs related to COVID-19. The study selection, data extraction and quality assessment will be performed by independent reviewers, and results will be crosschecked. The authoritative tools (AMSTAR-2, PRISMA and its extensions) will be used to assess the methodological quality and reporting quality of included SRs/MAs, and potential influence factors will be explored. The consistency of conclusions will be compared among reviews and the best evidence will be summarized. In addition, we will conduct exploratory meta-analyses (MAs) of individual studies when applicable. Data will be reported as number with (or) percentage, risk ratio (RR) or odds ratio (OR), mean difference (MD) or standardized mean difference (SMD) with 95% confidence interval (CI) according to the specific results. R3.6.1 and Microsoft Excel 2016 will be used to analyze and manage data. RESULTS: The results of this overview will be submitted to a peer-reviewed journal for publication. DISCUSSION: In this study, we will present for the first time, an overview of SRs/MAs, which provides a comprehensive, dynamic evidence landscape on prevalence, prevention, diagnosis, treatment, and prognosis of COVID-19.