Buschtranberg7034

Oxygen (O2) is a mainstay of treatment in acute severe asthma but how it is administered varies widely. The objectives were to examine whether a trial comparing humidified O2 to standard O2 in children is feasible, and specifically to obtain data on recruitment, tolerability and outcome measure stability.

Heated humidified, cold humidified and standard O2 treatments were compared for children (2-16 years) with acute severe asthma in a multi-centre, open, parallel, pilot randomised controlled trial (RCT). Multiple outcomes were assessed.

Of 258 children screened, 66 were randomised (heated humidified O2 n = 25; cold humidified O2 n = 21; standard O2 n = 20). Median (IQR) length of stay (hours) in hospital was 37.9 (29.1), 52 (35.4) and 49.1 (29.7) for standard, heated humidified and cold humidified respectively and time (hours) on O2 was 15.9 (9.4), 13.6 (14.9) and 13.1 (14.9) for the three groups respectively. The mean (standard deviation) time (hours) taken to step down nebulised to inhaled treatment wnd standard O2 therapy in acute severe asthmatics of any age. These findings and accompanying screening data show that a large RCT of O2 therapy is feasible. However, challenges associated with randomisation and data collection should be addressed in any future trial design.Alzheimer's disease (AD) is the leading cause of dementia and has received considerable research attention, including using neuroimaging biomarkers to classify patients and/or predict disease progression. Generalized linear models, e.g., logistic regression, can be used as classifiers, but since the spatial measurements are correlated and often outnumber subjects, penalized and/or Bayesian models will be identifiable, while classical models often will not. Many useful models, e.g., the elastic net and spike-and-slab lasso, perform automatic variable selection, which removes extraneous predictors and reduces model variance, but neither model exploits spatial information in selecting variables. Spatial information can be incorporated into variable selection by placing intrinsic autoregressive priors on the logit probabilities of inclusion within a spike-and-slab elastic net framework. We demonstrate the ability of this framework to improve classification performance by using cortical thickness and tau-PET images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to classify subjects as cognitively normal or having dementia, and by using a simulation study to examine model performance using finer resolution images.

Studies have demonstrated a potential correlation between low vitamin D status and both an increased risk of infection with SARS-CoV-2 and poorer clinical outcomes. This retrospective study examines if, and to what degree, a relationship exists between pre-infection serum 25-hydroxyvitamin D (25(OH)D) level and disease severity and mortality due to SARS-CoV-2.

The records of individuals admitted between April 7th, 2020 and February 4th, 2021 to the Galilee Medical Center (GMC) in Nahariya, Israel, with positive polymerase chain reaction (PCR) tests for SARS-CoV-2 (COVID-19) were searched for historical 25(OH)D levels measured 14 to 730 days prior to the positive PCR test.

Patients admitted to GMC with COVID-19 were categorized according to disease severity and level of 25(OH)D. An association between pre-infection 25(OH)D levels, divided between four categories (deficient, insufficient, adequate, and high-normal), and COVID-19 severity was ascertained utilizing a multivariable regression analysis. To isolate the possible influence of the sinusoidal pattern of seasonal 25(OH)D changes throughout the year, a cosinor model was used.

Of 1176 patients admitted, 253 had records of a 25(OH)D level prior to COVID-19 infection. JKE-1674 A lower vitamin D status was more common in patients with the severe or critical disease (<20 ng/mL [87.4%]) than in individuals with mild or moderate disease (<20 ng/mL [34.3%] p < 0.001). Patients with vitamin D deficiency (<20 ng/mL) were 14 times more likely to have severe or critical disease than patients with 25(OH)D ≥40 ng/mL (odds ratio [OR], 14; 95% confidence interval [CI], 4 to 51; p < 0.001).

Among hospitalized COVID-19 patients, pre-infection deficiency of vitamin D was associated with increased disease severity and mortality.

Among hospitalized COVID-19 patients, pre-infection deficiency of vitamin D was associated with increased disease severity and mortality.

Globally, the estimated annual number of new cases of curable sexually transmitted infections occurring among young people aged 15-24 years is approximately 178.5 million. There are fragmented and inconsistent findings on preventive practices for sexually transmitted infections. Thus, this systematic review and meta-analysis protocol aimed to estimate the pooled prevalence of preventive practices of sexually transmitted infections and identify its determinants among young people in Ethiopia.

The Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) will be used to develop the review protocol. Online databases such as PubMed, CINAHL, Scopus, Google, and Google Scholar will be used to search published and unpublished studies. The Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument will be used to assess the quality of the study. Statistical heterogeneity will be checked using the Cochran Q test and I2 statistics. Subgroup analysis and meta-regression wil infections, there is no study finding on the pooled prevalence of preventive practices for sexually transmitted infections and its determinants among young people in Ethiopia. Thus, this systematic review and meta-analysis protocol will help to develop appropriate strategies.

Early rehabilitation is indicated in critically ill adults to counter functional complications. However, the physiological response to rehabilitation is poorly understood. This study aimed to determine the cardiorespiratory response to rehabilitation and to investigate the effect of explanatory variables on physiological changes during rehabilitation and recovery.

In a prospectively planned, secondary analysis of a randomised controlled trial conducted in a tertiary, mixed intensive care unit (ICU), we analysed the 716 physiotherapy-led, pragmatic rehabilitation sessions (including exercise, cycling and mobilisation). Participants were previously functionally independent, mechanically ventilated, critically ill adults (n = 108). Physiological data (2-minute medians) were collected with standard ICU monitoring and indirect calorimetry, and their medians calculated for baseline (30min before), training (during physiotherapy) and recovery (15min after). We visualised physiological trajectories and investigatation during rehabilitation and recovery mirrors the heterogenous interventions and patient reactions. This warrants close monitoring and individual tailoring, whereby the best option to stimulate a cardiorespiratory response seems to be active patient participation, shorter session durations and mobilisation.

German Clinical Trials Register (DRKS) identification number DRKS00004347, registered on 10 September 2012.

German Clinical Trials Register (DRKS) identification number DRKS00004347, registered on 10 September 2012.We developed the DriverFuse package to integrate orthogonal data types such as Structural Variants (SV) and Copy Number Variations (CNV) to characterize fusion genes in cancer datasets. A fusion gene is reported as a driver or passenger fusion gene, based on mapping SV and CNV profiles. DriverFuse generates a fusion plot of fusion genes with their mapping SV, CNV profile, domain architecture and classification of its role in cancer. The analysis facilitates discrimination of driver fusions from passenger fusions. To demonstrate the utility of DriverFuse, we analyzed two datasets, one each for CCLE (Cancer Cell Line Encyclopedia) for lung cancer and HCC1395BL for breast cancer. The analysis validates the driver fusion genes that are already reported for the datasets. Thus, DriverFuse is a valuable tool for studying the driver fusion genes in cancers, enabling the identification of recurrent complex rearrangements that provide intuitive insights into disease driver events.Meta-analyses typically quantify heterogeneity of results, thus providing information about the consistency of the investigated effect across studies. Numerous heterogeneity estimators have been devised. Past evaluations of their performance typically presumed lack of bias in the set of studies being meta-analysed, which is often unrealistic. The present study used computer simulations to evaluate five heterogeneity estimators under a range of research conditions broadly representative of meta-analyses in psychology, with the aim to assess the impact of biases in sets of primary studies on estimates of both mean effect size and heterogeneity in meta-analyses of continuous outcome measures. To this end, six orthogonal design factors were manipulated Strength of publication bias; 1-tailed vs. 2-tailed publication bias; prevalence of p-hacking; true heterogeneity of the effect studied; true average size of the studied effect; and number of studies per meta-analysis. Our results showed that biases in sets of primary studies caused much greater problems for the estimation of effect size than for the estimation of heterogeneity. For the latter, estimation bias remained small or moderate under most circumstances. Effect size estimations remained virtually unaffected by the choice of heterogeneity estimator. For heterogeneity estimates, however, relevant differences emerged. For unbiased primary studies, the REML estimator and (to a lesser extent) the Paule-Mandel performed well in terms of bias and variance. In biased sets of primary studies however, the Paule-Mandel estimator performed poorly, whereas the DerSimonian-Laird estimator and (to a slightly lesser extent) the REML estimator performed well. The complexity of results notwithstanding, we suggest that the REML estimator remains a good choice for meta-analyses of continuous outcome measures across varied circumstances.

Whether fluid overload is associated with vascular stiffness parameters in hemodialysis (HD) patients has not been fully elucidated. We hypothesized that interdialytic fluid accumulation increases vascular stiffness parameters, which improves with intradialytic ultrafiltration.

Fluid overload and vascular stiffness parameters were assessed in 39 HD patients (20 with and 19 without fluid overload) and compared to 26 healthy controls. Fluid status was assessed 15 minutes before the mid-week HD session by bio-impedance spectroscopy. Following this, ambulatory pulse wave velocity (PWV) and augmentation index (AIx) were measured for 24 hours before another mid-week HD session and then for 5 hours starting 30 minutes before and ending 30 minutes after the session.

HD patients had significant fluid overload compared to healthy controls (2.0±2.4 vs. -0.2±0.6 L; P<0.001) and baseline PWV was higher (10.3±1.7 vs. 8.8±1.4 m/s; P<0.001). There was no significant difference between PWV and AIx in fluid overloahat the effect of fluid overload correction on vascular stiffness parameters requires long-term adjustments in the vasculature.