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Greater COVID-19 related mortality has been reported among persons with various non-communicable diseases (NCDs). We performed an ecological study to determine the association of state-level cases and deaths with NCD risk factors and healthcare and social indices.

We obtained cumulative national and state-level data on COVID-19 cases and deaths from publicly available database www.covid19india.org from February to end November 2020. To identify association with major NCD risk factors, NCDs, healthcare related and social variables we obtained data from public sources. Association was determined using univariate and multivariate statistics.

More than 9.5 million COVID-19 cases and 135,000 deaths have been reported in India towards end of November 2020. There is significant positive correlation (Pearson r) of state-level COVID-19 cases and deaths per million, respectively, with NCD risk factors- obesity (0.64, 0.52), hypertension (0.28, 0.16), diabetes (0.66, 0.46), NCD epidemiological transition index (0.58, 0.54) and ischemic heart disease mortality (0.22, 0.33). Correlation is also observed with indices of healthcare access and quality (0.71, 0.61), urbanization (0.75, 0.73) and human (0.61, 0.56) and sociodemographic (0.70, 0.69) development. Multivariate adjusted analyses shows strong correlation of COVID-19 burden and deaths with NCD risk factors (r

=0.51, 0.43), NCDs (r

=0.32, 0.16) and healthcare (r

=0.52, 0.38).

COVID-19 disease burden and mortality in India is ecologically associated with greater state-level burden of NCDs and risk factors, especially obesity and diabetes.

COVID-19 disease burden and mortality in India is ecologically associated with greater state-level burden of NCDs and risk factors, especially obesity and diabetes.

Although the Clinical Institute Withdrawal Assessment for Alcohol - Revised (CIWA-Ar) is a gold standard tool for the clinical evaluation of alcohol withdrawal syndrome (AWS), a systematic analysis using the total scores of the CIWA-Ar as a means of an objective follow-up of the course and treatment of AWS is missing. The aims of the present study were to systematically evaluate scientific data using the CIWA-Ar, to reveal whether the aggregated CIWA-Ar total scores follow the course of AWS and to compare benzodiazepine (BZD) and non-benzodiazepine (nBZD) therapies in AWS.

1054 findings were identified with the keyword "ciwa" from four databases (PubMed, ScienceDirect, Web of Science, Cochrane Registry). Articles using CIWA-Ar in patients treated with AWS were incorporated and two measurement intervals (cumulative mean data of day 1-3 and day 4-9) of the CIWA-Ar total scores were compared. Subgroup analysis based on pharmacotherapy regimen was conducted to compare the effectiveness of BZD and nBZD treatments.

The random effects analysis of 423 patients showed decreased CIWA-Ar scores between the two measurement intervals (BZD d = -1.361; CI -1.829 < δ < -0.893; nBZD d = -0.858; CI -1.073 < δ < -0.643). Sampling variances were calculated for the BZD (v

= 0.215) and the nBZD (v

= 0.106) groups, which indicated no significant group difference (z = -1.532).

Our findings support that the CIWA-Ar follows the course of AWS. Furthermore, nBZD therapy has a similar effectiveness compared to BZD treatment based on the CIWA-Ar total scores.

Our findings support that the CIWA-Ar follows the course of AWS. Furthermore, nBZD therapy has a similar effectiveness compared to BZD treatment based on the CIWA-Ar total scores.

To compare the levels of various cytokines between pregnant women with confirmed coronavirus disease (COVID-19) infection and pregnant women without any defined risk factor.

Pregnant women with confirmed COVID-19 infection (study group)(n=90) were prospectively compared to a gestational age-matched control group of pregnant women without any defined risk factors (n=90). Demographic features, clinical characteristics, laboratory parameters, interferon-gamma (IFN γ), interleukin (IL-2), IL-6, IL-10, and IL-17 levels were compared between the groups. Additionally, a correlation analysis was performed in the study group for the assessment of IFN γ, IL-2, IL-6, IL-10, and IL-17 levels with disease severity and CRP levels.

Study group had significantly higher pregnancy complication rate, erythrocyte sedimentation rate, C-reactive protein, procalcitonin, ferritin, D-dimer, lactate dehydrogenase, IFN γ, and IL-6 values (p<0.05). On the other hand, the control group had significantly higher hemoglobin, leukocpregnancy trimesters and cytokine levels seem to be correlated with disease severity.The clinical spectrum of leishmaniasis depends on several factors, including Leishmania species and immunogenetic factors. Tumor necrosis factor α (TNFα) plays a central role in immunity against intracellular infections. Many studies have reported that TNFα-308G > A polymorphism is associated with susceptibility to intracellular infections and influences TNFα production. Some studies on the implications of TNFα-308G > A polymorphism in the susceptibility to cutaneous leishmaniasis and visceral leishmaniasis showed controversial results. this website To draw an overall conclusion using accurate data analysis by increasing the number of cases studied, a meta-analysis was performed based on data from the studies included in the analysis. A total of 1264 patients and 2350 controls were enrolled in the meta-analysis. The results showed no significant association between allele G and allele A of -308G > A polymorphism and leishmaniasis by taking the two subgroups separately [ORCL = 0.99 (0.84-1.18) and ORVL = 1.19 (0.88-1.59)] or together [OR = 1.04 (0.90-1.20)]. This meta-analysis insinuates the absence of statistical evidence for an association between allele G and allele A of TNFα-308G > A polymorphism and Leishmania infection outcome. This suggests that TNFα, despite its crucial role in the immune response against Leishmania infection, is not the sole determinant factor. Other factors, such as gene-gene and gene-environment interactions, receptors, and signaling pathway efficiency, may influence TNFα function.

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