Evaluation of Glycemic Control and Predictors of Severe Illness and Death in Patients with Diabetes Hospitalized With COVID-19.

Objectives: To identify risk factors for severe disease and death among patients with diabetes and coronavirus disease 2019 (COVID-19) infection. Methods: This retrospective cohort study conducted at three hospitals included 733 consecutive patients with DM admitted with confirmed COVID-19 (March 1 - December 31, 2020). Multivariable logistic regression was performed to identify predictors of severe disease and death. Results: The mean age was 67.4 ± 14.3 years, 46.9% were males and 61.5% were African American. Among all patients, 116 (15.8%) died in the hospital. A total of 317 (43.2%) patients developed severe disease, 183 (25%) were admitted to an ICU and 118 (16.1%) required invasive mechanical ventilation. Increasing BMI (OR, 1.13; 95% CI, 1.02-1.25), history of chronic lung disease (OR, 1.49; 95% CI, 1.05-2.10) and increasing time since the last HbA1c test (OR, 1.25; 95% CI, 1.05-1.49) were the preadmission factors associated with increased odds of severe disease. Preadmission use of metformin (OR, 0.67; 95% CI, 0.47-0.95) or GLP-1 agonists (OR, 0.49; 95% CI, 0.27-0.87) was associated with decreased odds of severe disease. Increasing age (OR, 1.21; 95% CI, 1.09-1.34), co-existing chronic kidney disease greater than stage 3 (OR, 3.38; 95% CI, 1.67-6.84), ICU admission (OR, 2.93; 95% CI, 1.28-6.69) and use of invasive mechanical ventilation (OR, 8.67, 95% CI, 3.88-19.39) were independently associated with greater odds of in-hospital death. Conclusion: Several clinical characteristics were identified to be predictive of severe disease and in-hospital death among patients with underlying diabetes hospitalized with COVID-19.

Surgical Aortic Valve Replacement Versus Conservative Treatment in Asymptomatic Severe Aortic Stenosis: An Updated Systematic Review and Meta-Analysis.

BACKGROUND: While aortic valve replacement (AVR) is indicated for symptomatic severe aortic stenosis (AS), the appropriate management of asymptomatic severe AS remains unclear. We conducted an updated meta-analysis to compare the outcomes of surgical AVR (SAVR) versus conservative treatment in patients with asymptomatic severe AS. METHODS: We searched PubMed, EMBASE, Cochrane, clinicaltrials.gov, and Google Scholar for studies comparing outcomes of SAVR versus conservative treatment in asymptomatic severe AS. Risk ratios (RRs) and 95% confidence intervals (CIs) were calculated for each individual study. Outcomes included all-cause mortality, cardiovascular and non-cardiovascular mortality, 30-day operative mortality, sudden cardiac death (SCD), heart failure hospitalization (HFH), myocardial infarction (MI), and stroke. RESULTS: A total of 8 studies with 2685 patients were included. The mean age was above 60 years, and the median follow-up duration was 4 years. Compared to conservative treatment, SAVR was associated with significantly lower all-cause mortality (RR 0.39; 95% CI 0.23-0.64) and HFH rates (RR 0.18; 95% CI 0.05-0.71). There were no significant differences in cardiovascular mortality (RR 0.24; 95% CI 0.03-1.67), non-cardiovascular mortality (RR 0.49; 95% CI 0.23-1.03), 30-day operative mortality (RR 0.48; 95% CI 0.10-2.32), SCD (RR 0.37; 95% CI 0.05-2.89), MI (RR 0.48; 95% CI 0.04-5.52), and stroke rates (RR 1.20; 95% CI 0.35-4.11) between the two strategies. CONCLUSIONS: In patients with asymptomatic severe AS, SAVR is associated with significantly lower all-cause mortality and HFH compared to conservative treatment. While SAVR is a promising option for asymptomatic severe AS, most studies were observational and nonrandomized; randomized trials are needed to establish a clear benefit.

A panel of microsatellites to individually identify leopards and its application to leopard monitoring in human dominated landscapes.

BACKGROUND: Leopards are the most widely distributed of the large cats, ranging from Africa to the Russian Far East. Because of habitat fragmentation, high human population densities and the inherent adaptability of this species, they now occupy landscapes close to human settlements. As a result, they are the most common species involved in human wildlife conflict in India, necessitating their monitoring. However, their elusive nature makes such monitoring difficult. Recent advances in DNA methods along with non-invasive sampling techniques can be used to monitor populations and individuals across large landscapes including human dominated ones. In this paper, we describe a DNA-based method for leopard individual identification where we used fecal DNA samples to obtain genetic material. Further, we apply our methods to non-invasive samples collected in a human-dominated landscape to estimate the minimum number of leopards in this human-leopard conflict area in Western India. RESULTS: In this study, 25 of the 29 tested cross-specific microsatellite markers showed positive amplification in 37 wild-caught leopards. These loci revealed varied levels of polymorphism (four-12 alleles) and heterozygosity (0.05-0.79). Combining data on amplification success (including non-invasive samples) and locus specific polymorphisms, we showed that eight loci provide a sibling probability of identity of 0.0005, suggesting that this panel can be used to discriminate individuals in the wild. When this microsatellite panel was applied to fecal samples collected from a human-dominated landscape, we identified 7 individuals, with a sibling probability of identity of 0.001. Amplification success of field collected scats was up to 72%, and genotype error ranged from 0-7.4%. CONCLUSION: Our results demonstrated that the selected panel of eight microsatellite loci can conclusively identify leopards from various kinds of biological samples. Our methods can be used to monitor leopards over small and large landscapes to assess population trends, as well as could be tested for population assignment in forensic applications.

Evaluation of dengue-related health information on the internet.

The objective of this study was to examine the quality of dengue-related health information on the Internet. Three raters used the keyword dengue to search the Google, Yahoo!, and Bing search engines during August 2011. The first 20 websites from each search engine were examined for a total of 60 sites. Duplicate, nonfunctional, non-English, and nonoperational websites were excluded from the study, resulting in 36 sites for final analysis. The 16-item DISCERN tool was used to evaluate the quality of dengue-related health information on the Internet. Chi-square analysis and analysis of variance were performed to compare the DISCERN scores. Inter-rater reliability analysis showed significant differences in the level of agreement among the three raters. The 36 unique websites were categorized into .com, .edu, .gov, .org, and other sites. The .com sites had the lowest DISCERN scores. Educating consumers on how to find and recognize valid health information on the Internet may lead to better informed decision making.

Ecology driving genetic variation: a comparative phylogeography of jungle cat (Felis chaus) and leopard cat (Prionailurus bengalensis) in India.

BACKGROUND: Comparative phylogeography links historical population processes to current/ecological processes through congruent/incongruent patterns of genetic variation among species/lineages. Despite high biodiversity, India lacks a phylogeographic paradigm due to limited comparative studies. We compared the phylogenetic patterns of Indian populations of jungle cat (Felis chaus) and leopard cat (Prionailurus bengalensis). Given similarities in their distribution within India, evolutionary histories, body size and habits, congruent patterns of genetic variation were expected. METHODOLOGY/PRINCIPAL FINDINGS: We collected scats from various biogeographic zones in India and analyzed mtDNA from 55 jungle cats (460 bp NADH5, 141 bp cytochrome b) and 40 leopard cats (362 bp NADH5, 202 bp cytochrome b). Jungle cats revealed high genetic variation, relatively low population structure and demographic expansion around the mid-Pleistocene. In contrast, leopard cats revealed lower genetic variation and high population structure with a F(ST) of 0.86 between North and South Indian populations. Niche-model analyses using two approaches (BIOCLIM and MaxEnt) support absence of leopard cats from Central India, indicating a climate associated barrier. We hypothesize that high summer temperatures limit leopard cat distribution and that a rise in temperature in the peninsular region of India during the LGM caused the split in leopard cat population in India. CONCLUSIONS/SIGNIFICANCE: Our results indicate that ecological variables describing a species range can predict genetic patterns. Our study has also resolved the confusion over the distribution of the leopard cat in India. The reciprocally monophyletic island population in the South mandates conservation attention.