Prevalence, Clinical Characteristics, and Clinical Outcomes of New-onset Diabetes Mellitus among COVID-19 Patients in Developing and Developed Countries: A Systematic Review.

Diabetes mellitus (DM) is linked to poor clinical outcomes and high mortality in Coronavirus patients. The primary objective of this systematic review was to determine the prevalence, clinical features, glycemic parameters, and outcomes of newly diagnosed diabetes in individuals with COVID-19 in developing and developed countries. By searching PubMed, Medline, Scopus, Embase, Google Scholar, and PakMediNet databases, an online literature search was conducted from March 2020 to November 2021. Guidelines for reporting systematic reviews and meta-analyses (PRISMA) were used. There were 660 publications found, of which 27 were original studies involving 3241 COVID-19 patients were selected. In the COVID-19 patients with new-onset diabetes, mean age was 43.21±21.00 years. Fever, cough, polyuria, and polydipsia were the most frequently reported symptoms, followed by shortness of breath, arthralgia, and myalgia. The developed world reported (109/1119) new diabetes cases (9.74%), while the developing world reported (415/2122) (19.5%). COVID-19 new-onset diabetic mortality rate was 470/3241 (14.5%). Key Words: COVID-19, New onset diabetes mellitus, SARS-CoV-2, Prevalence, Clinical outcomes, Developing countries, Developed countries.

Household COVID-19 secondary attack rate and associated determinants in Pakistan; A retrospective cohort study.

BACKGROUND: COVID-19 household transmissibility remains unclear in Pakistan. To understand the dynamics of Severe Acute Respiratory Syndrome Coronavirus disease epidemiology, this study estimated Secondary Attack Rate (SAR) among household and close contacts of index cases in Pakistan using a statistical transmission model. METHODOLOGY: A retrospective cohort study was conducted using an inclusive contact tracing dataset from the provinces of Punjab and Khyber-Pakhtunkhwa to estimate SAR. We considered the probability of an infected person transmitting the infection to close contacts regardless of residential addresses. This means that close contacts were identified irrespective of their relationship with the index case. We assessed demographic determinants of COVID-19 infectivity and transmissibility. For this purpose based on evolving evidence, and as CDC recommends fully vaccinated people get tested 5-7 days after close contact with a person with suspected or confirmed COVID-19. Therefore we followed the same procedure in the close contacts for secondary infection. FINDINGS: During the study period from 15th May 2020 to 15th Jan 2021, a total of 339 (33.9%) index cases were studied from 1000 cases initially notified. Among close contact groups (n = 739), households were identified with an assumed mean incubation period of 8.2+4.3 days and a maximum incubation period of 15 days. SAR estimated here is among the household contacts. 117 secondary cases from 739 household contacts, with SAR 11.1% (95% CI 9.0-13.6). All together (240) SAR achieved was 32.48% (95% CI; 29.12-37.87) for symptomatic and confirmed cases. The potential risk factors for SAR identified here included; old age group (>45 years of age), male (gender), household members >5, and residency in urban areas and for index cases high age group. Overall local reproductive number (R) based on the observed household contact frequencies for index/primary cases was 0.9 (95% CI 0.47-1.21) in Khyber Pakhtunkhwa and 1.3 (95% CI 0.73-1.56) in Punjab. CONCLUSIONS: SAR estimated here was high especially in the second phase of the COVID-19 pandemic in Pakistan. The results highlight the need to adopt rigorous preventive measures to cut the chain of viral transmission and prevent another wave of COVID-19.

Infodemics: Use of Peer Reviewed and Non-Peer Reviewed Information by Post Graduate Trainee Doctors for COVID-19 Pandemic in Pakistan

Background: Reliable and peer reviewed information is of immense importance for preventive, diagnostic and curative solutions and efforts should be done to minimize inaccurate infodemics among post graduate trainee doctors. Objective: The aim of the study was to access the use of Peer Reviewed and Non-Peer Reviewed Information by post graduate trainee doctors for COVID-19 Pandemic in Pakistan. Methods: The study was analytical cross sectional in design and was conducted in 3193 post graduate trainee doctors employing Electronic Logbook (elog) system of College of Physicians and Surgeons, Pakistan. An online survey included demographic characteristics, year of training, specialty and sources of information used for COVID-19 pandemic. Results: Total 3193 study participants from all provinces of Pakistan were included with mean age of 28.68 years. Majority of participants (58.66%) used both peer reviewed and non-peer reviewed information source for getting updated guidelines and information about COVID-19. According to bivariate analysis results, significant differences were revealed between the source of information and the age (p < 0.001), province (p < 0.001) and gender (p < 0.002). Multivariate logistic regression results showed that the age less than 30 years (AOR = 1.311, 95% (CI: 0.800, 2.146), working in Khyber Pakhtunkhwa province (AOR = 1.549, 95% (CI: 1.210-1.982) and female gender(AOR = 1.551, 95% (CI: 1.303, 1.847). was significantly associated with increased use of social media for getting information. Conclusion: Use of non-peer reviewed information for COVID-19 pandemic by postgraduate trainee doctors is common. [ABSTRACT FROM AUTHOR] Copyright of Annals of King Edward Medical University is the property of King Edward Medical University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)