Comparison of COVID-19 outcomes in organ transplant recipients (OTr) and non-transplant patients: a study protocol for rapid review

Background The COVID-19 pandemic has devastated the global community with nearly 4.9 million deaths as of October 2021. While organ transplant (OT) recipients (OTr) may be at increased risk for severe COVID-19 due to their chronic immunocompromised state, outcomes for OTr with COVID-19 remain disputed in the literature. This review will examine whether OTr with COVID-19 are at higher risk for severe illness and death than non-immunocompromised individuals. Methods MEDLINE (via Ovid and PubMed) and EMBASE (via Embase.com) will be searched from December 2019 to October 2021 for observational studies (including cohort and case-control) that compare COVID-19 clinical outcomes in OTr to those in individuals without history of OT. The primary outcome of interest will be mortality as defined in each study, with possible further analyses of in-hospital mortality, 28 or 30-day mortality, and all-cause mortality versus mortality attributable to COVID-19. The secondary outcome of interest will be the severity of COVID-19 disease, most frequently defined as requiring intensive care unit admission or mechanical ventilation. Two reviewers will independently screen all abstracts and full-text articles. Potential conflicts will be resolved by a third reviewer and potentially discussion among all investigators. Methodological quality will be appraised using the Newcastle-Ottawa Scale. If data permit, we will perform random-effects meta-analysis with the Sidik-Jonkman estimator and the Hartung-Knapp adjustment for confidence intervals to estimate a summary measure of association between histories of transplant with each outcome. Potential sources of heterogeneity will be explored using meta-regression. Additional analyses will be conducted to explore the potential sources of heterogeneity (e.g., subgroup analysis) considering least minimal adjustment for confounders. Discussion This rapid review will assess the available evidence on whether OTr diagnosed with COVID-19 are at higher risk for severe illness and death compared to non-immunocompromised individuals. Such knowledge is clinically relevant and may impact risk stratification, allocation of organs and healthcare resources, and organ transplantation protocols during this, and future, pandemics. Systematic review registration Open Science Framework (OSF) registration DOI: 10.17605/osf.io/4n9d7.

Breastfeeding in Cystic Fibrosis: A Systematic Review on Prevalence and Potential Benefits

Breastfeeding (BF) is considered the normative standard of feeding for all infants. However, the impact of BF in patients with cystic fibrosis (CF) is not completely defined. Therefore, we conducted a systematic review to evaluate BF prevalence in the CF population and its impact on anthropometric and pulmonary outcomes. We searched MEDLINE, Embase and the Cochrane Library for original articles published in English up to 4 December 2020 that report the prevalence of BF and/or any measure of association between BF and anthropometric or pulmonary outcomes. Nine observational studies were identified (six retrospective cohort studies, one prospective cohort study, one survey and one case–control study within a retrospective cohort). The BF rate in CF patients is lower than that of the healthy population (approximately 50–60% of infants were breastfed at any time). The benefits in anthropometric outcomes of BF for >2 months in this at-risk population are unclear. A few relatively small studies suggest a potential benefit of BF in reducing lung infections, although data are inconsistent. The currently available data are insufficient to draw definite conclusions on the benefits of exclusive BF in anthropometric and pulmonary outcomes in CF. Clinical trials evaluating well-defined BF promotion interventions are needed.

Incidence of Severe Acute Respiratory Syndrome Coronavirus-2 infection among previously infected or vaccinated employees

Introduction: The protective effect of previous infection versus vaccination is poorly studied. Among a clinical laboratory that has been conducting routine workforce screening since the beginning of the pandemic, we aimed to assess the relative risk of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection among individuals who were SARS-CoV-2 naive, previously infected, or vaccinated. Methods: Using an electronic laboratory information system, employees were divided into three groups: (1) SARS-CoV-2 naive and unvaccinated, (2) previous SARS-CoV-2 infection, and (3) vaccinated. Person-days were measured from the date of the employee first test and truncated at the end of the observation period. SARS-CoV-2 infection was defined as two positive SARS-CoV-2 PCR tests in a 30-day period. Individuals with fewer than 14 days of follow up were excluded. Incidence estimates and the 95% confidence intervals were calculated using the Poisson Exact equation. The incidence rate ratio (IRR) was used as a measure of association between groups. Analyses were performed on StataSE (StataCorp, College Station, TX). Results: We identified 4313, 254 and 739 employee records for groups 1, 2, and 3, respectively. The median age of employees was 29.0 years (interquartile range: 23.6, 39.9). During the observation period, 254, 0, and 4 infections were identified among groups 1, 2, and 3, respectively. Group 1 had an incidence of 25.9 per 100 person-years (95% CI: 22.8-29.3). Group 2 had an incidence of 0 per 100 person-years (95% CI: 0-5.0). Group 3 had an incidence of 1.6 per 100 person-years (95% CI: 0.04-4.2). The IRR of reinfection among those with previous infection compared to SARS-CoV-2 naive was 0 (95% CI: 0-0.19). The IRR of those vaccinated compared to SARS-CoV-2 naive was 0.06 (95% CI: 0.02-0.16). The IRR of those vaccinated compared to prior SARS-CoV-2 was 0 (95% CI: 0-4.98). Conclusion: Previous SARS-CoV-2 infection and vaccination for SARS-CoV-2 were associated with decreased risk for infection or re-infection with SARS-CoV-2 in a routinely screened workforce. The was no difference in the infection incidence between vaccinated individuals and individuals with previous infection. Further research is needed to determine whether our results are consistent with the emergence of new SARS-CoV-2 variants.

EXPLORATORY SPATIAL ANALYSIS OF HOUSING PRICES OBTAINED FROM WEB SCRAPING TECHNIQUE

The exploratory spatial analysis allows to describe patterns of spatial distribution, to identify clusters and outliers through specific techniques of spatial association and data model. The objective of the study is to verify the spatial autocorrelation between the mean prices of the housing obtained from web scraping technique in online platforms in the city of Salvador, on the coast of northeast Brazil. For this purpose, the Global Moran’s Index (which provides a general measure of association) and the Local Index of Spatial Association (LISA) were calculated. The results of Global Moran’s Index indicate positive autocorrelation between the mean prices of housing prices in the 163 districts of the municipally that are statistically significant, such as identification of clusters through LISA. Thus, the analysis allows to conclude the existence of a heterogeneous pattern in the distribution of these mean prices in the urban space of Salvador.

A parameter-less algorithm for tensor co-clustering

The majority of the data produced by human activities and modern cyber-physical systems involve complex relations among their features. Such relations can be often represented by means of tensors, which can be viewed as generalization of matrices and, as such, can be analyzed by using higher-order extensions of existing machine learning methods, such as clustering and co-clustering. Tensor co-clustering, in particular, has been proven useful in many applications, due to its ability of coping with n-modal data and sparsity. However, setting up a co-clustering algorithm properly requires the specification of the desired number of clusters for each mode as input parameters. This choice is already difficult in relatively easy settings, like flat clustering on data matrices, but on tensors it could be even more frustrating. To face this issue, we propose a new tensor co-clustering algorithm that does not require the number of desired co-clusters as input, as it optimizes an objective function based on a measure of association across discrete random variables (called Goodman and Kruskal’s $$\tau$$ τ ) that is not affected by their cardinality. We introduce different optimization schemes and show their theoretical and empirical convergence properties. Additionally, we show the effectiveness of our algorithm on both synthetic and real-world datasets, also in comparison with state-of-the-art co-clustering methods based on tensor factorization and latent block models.

Alcohol use and associated factors among adolescent boys and young men in Kampala, Uganda

Background Alcohol use leads to about 3 million deaths globally. The alcohol industry employs marketing strategies to establish their brands in the lives of young people at a time when addictive behaviors are initiated and reinforced. We conducted a survey among adolescent boys and young men (ABYM) to estimate the prevalence of alcohol use and associated factors using the Health Belief Model as the guiding framework. Methods The study was conducted among ABYM in- or out-of-school aged 10–24 years in Kampala, Uganda. We used questions adopted from the Global School-based Student Health Survey and the WHO STEPwise approach to Surveillance questionnaire to collect data. The outcome of interest was alcohol use within 30 days before the interview. We also asked about characteristics such as alcohol use by siblings, parents/ guardians, school status among others. We used odds ratios obtained via a logistic regression model as the measure of association. Results A total of 2500 ABYM participated, of which 262 (10.5 %, 95 %CI 9.3–11.7) had consumed alcohol within 30 days before the interview. Out-of-school ABYM had higher odds of consuming alcohol compared with their in-school counterparts AOR 1.55 (95 %CI 1.09–2.20). Compared with ABYM whose parents/ guardians did not drink alcohol, ABYM whose both parents consumed alcohol had higher odds of consuming alcohol AOR 2.24 (95 %CI 1.38–3.64) as were those with only a mother or female guardian who consumed alcohol AOR 1.95 (95 %CI 1.11–3.41). ABYM with siblings that drink alcohol had higher odds of consuming alcohol AOR 2.25 (95 %CI 1.80–3.52). ABYM who possessed items with an alcohol brand logo had higher odds of consuming alcohol AOR 2.00 (95 %CI 1.33–3.01). Conclusions There are significant levels of alcohol consumption among ABYM which calls for evidence-based measures targeting this age group to reduce consumption and recognizing the role of the family, school and community in prevention and promotion of use. There is need to regulate alcohol marketing and ensuring availability of alcohol dependence treatment services that build confidence among youth.

Common Mental Disorder and early interruption of exclusive maternal breastfeeding in Quilombola women: a population-based study

Objectives: to investigate the prevalence of exclusive maternal breastfeeding (EMBF) and evaluate whether common mental disorder (CMD) and other predictors promote its early interruption (EI-EMBF4). Methods: a cross-sectional study involving all children <24 months (n=252) residing in 50% (n=34) of the Quilombola communities in Alagoas. The EI-EMBF4 was established when EMBF was ≤4 months. The Self-Reporting Questionnaire was used to identify the occurrence of CMD. Other predictors were obtained through interviews. The measure of association was the prevalence ratio calculated by the Poisson regression, following a hierarchical theoretical model. The prevalence of EMBF for 4 and 6 months, and its median duration (survival analysis) were calculated. Results: the prevalence of EI-EMBF4 and CMD was 57.6% and 42.9%, respectively. The risk factors independently associated with EI-EMBF4 were: living in a mud house, maternal age ≤18 years, low birth weight and the use of a pacifier or baby bottle. There was no association with CMD. The prevalence of EMBF for four and six months was 42.4% and 25.4%, respectively, and the median duration was 106 days. Conclusion: EMBF indicators are below the established recommendations, justifying the implementation of measures that prioritize women subjected to risk factors identified here. CMD is not configured among these.

Linear causal filtering: definition and theory

This work provides a framework based on multivariate autoregressive modeling for linear causal filtering in the sense of Granger. In its bivariate form, the linear causal filter defined here takes as input signals A and B, and it filters out the causal effect of B on A, thus yielding two new signals only containing the Granger-causal effect of A on B. In its general multivariate form for more than two signals, the effect of all indirect causal connections between A and B, mediated by all other signals, are accounted for, partialled out, and filtered out also. The importance of this filter is that it enables the estimation of directional measures of causal information flow from any non-causal, non-directional measure of association. For instance, based on the classic coherence, a directional measure of strength of information flow from A to B is obtained when applied to the linear causal filtered pair containing only A to B connectivity information. This particular case is equivalent to the isolated effective coherence (doi.org/10.3389/fnhum.2014.00448). Of more recent interest are the large family of phase-phase, phase-amplitude, and amplitude-amplitude cross-frequency coupling measures which are non-directional. The linear causal filter makes it now possible to estimate the directional causal versions these measures of association. One important field of application is in brain connectivity analysis based on cortical signals of electric neuronal activity (e.g. estimated sources of EEG and MEG, and invasive intracranial ECoG recordings). The linear causal filter introduced here provides a novel solution to the problem of estimating the direction of information flow from any non-directional measure of association. This work provides definitions, non-ambiguous equations, and clear prescriptions for implementing the linear causal filter in diverse settings.

Comparative Evaluation of Saliva and Serum Proteins in Diabetics and Normo-Glycemics

One of the most probable markers of inflammatory response is serum protein. Recently, serum levels of these some proteins have been proven to be useful in clinical diagnosis. In this study, we comparatively investigated serum and saliva C - reactive protein (CRP), α-amylase and α-glucosidase activities in type II Diabetic and Normo-glycemic humans. Two hundred and thirteen (213) subjects of 173 Diabetics and 40 Non-diabetics (Control) were ethically recruited from the central hospital, warri, Delta State. For each participant, serum and saliva was collected and laboratorily analyzed for α-amylase, α-glucosidase and CRP levels, while comparing mean differences between groups with a student t-test and statistical measure of association (correlation). Result showed a statistically significant increase in CRP and α-amylase activity of diabetics than non-diabetic subjects, with a statistically significant increase in salivary and serum CRP, α-glucosidase and α-amylase levels across groups. This finding is suggestive that saliva and/or serum levels may be useful bioanalytes for non-invasive, alternative diagnosis of blood glucose levels. Similar studies that corroborate the efforts of this study is recommended. Further studies that assay other saliva and serum biomarkers may also be useful and thus recommended.