The corona virus disease of 2019 (Covid-19) is a deadly viral infection rampaging the world since 2019. Health practitioners have identified co-morbidities as one of the factors contributing to the severity of the disease among patients, with diabetes being one of the leading co-morbid. A systematic search was performed on PubMed, Google Scholar and Science hub databases to obtain articles that have addressed the link between diabetes and severity in Covid-19 infection. A meta-analysis to obtain a pooled effect of the effect of diabetes on the severity of Covid-19 (odd ratio OR) was calculated using R programming language and a funnel plot to check for publication bias was also plotted. Twelve studies with 3,180,125 diabetic patients with confirmed cases of Covid-19 (out of 61,820,553 confirmed Covid-19 participants) were included for the meta-analysis. The obtained pooled effect of diabetes on the severity of Covid-19 infection was (OR=1.47; 95% CI 1.33-1.63). From the meta-analysis results; Age, diabetic complications and drugs for the treatment of diabetes were identified as possible co-factors to the diabetic effect on Covid-19 infection, as diabetes was seen to be significantly related to its severity but not mortality. It is therefore very important for diabetic patients to adhere strictly to every laid down regulation regarding Covid-19. More clinical research on alternative diabetic therapy is needed as this will reduce the negative effect of insulin usage.

Background. Roux-en-Y gastric bypass (RYGB) is an effective treatment for obesity, where gut peptides such as ghrelin, glucagon-like peptide-1 (GLP-1) and peptide YY (PYY) play an instrumental role in reduced appetite after RYGB. This systematic review and meta-analysis aimed to establish the magnitude of change of ghrelin, GLP-1, PYY and appetite sensation following RYGB. Methods. A systematic search was conducted in Medline Ovid, Embase, Scopus, and Cochrane Central Register of Controlled Trials up until March 2021. Two independent reviewers screened articles for studies that evaluated ghrelin, GLP-1, PYY or appetite sensation via visual analogue scales (VAS) before and after RYGB in adults. Risk of bias was assessed with the quality assessment tool for before-after studies with no control group from the National Heart, Lung and Blood Institute (NHLBI). A multilevel model with random effects for study and follow-up time points nested in study was fit to the data. The model included kilocalorie consumption as a covariate and time points as moderators. Results. Among the 2,559 articles identified, 47 met the inclusion criteria, among which k=19 evaluated ghrelin, k=40 GLP-1, k=22 PYY and k=8 appetite sensation via VAS. Our results indicate that fasting ghrelin levels are decreased 2 weeks post-RYGB (p = .005) but do not differ from baseline from 6 weeks to 1-year post-RYGB. Postprandial ghrelin levels at 6 months and 1-year post-RYGB were not different from pre-surgical values (p = .51). Fasting GLP-1 levels were not different from pre-surgical levels up to 2 years post-RYGB. Postprandial levels of GLP-1 increased significantly from 1 week (p < .001) to 2 years post-RYGB (p < .01) compared to before surgery. Compared to pre-RYGB levels, fasting PYY increased at 6 months (p = .034) and 1 year (p = .0299) post-surgery and postprandial levels were increased up to 1 year (p < .01). Heterogeneity was significant in most analyses. Insufficient data on appetite sensation was available to be meta-analyzed. Conclusion. Our analyses illustrate the magnitude of change of ghrelin, GLP-1 and PYY before and after RYGB surgery. Importantly, between study heterogeneity within the current literature warrants more standardized protocols and studies with longer follow-up periods for better comprehension of changes in gut peptides following RYGB surgery.

No description available.

Clostridium difficile infection (CDI) prevention is of high priority. We reviewed clinical practice guidelines (CPGs), and conducted an individual participant data meta-analysis (IPMDA) of randomized controlled trials (RCTs) to assess effectiveness and safety of probiotic prophylaxis. For CPGs, we rated quality, summarized recommendations with their strength and author-reported evidence, then re-evaluated evidence. For the IPDMA, we pooled RCTs investigating probiotics versus control for CDI prevention among antibiotic consumers, using generalized linear mixed models. Our outcomes were CDI and serious adverse events (SAEs). We adjusted for age, sex, hospitalization status, and exposure to high risk antibiotics. We assessed study risk of bias and confidence in estimates of effect. Five international guidelines were evaluated, and all scored poorly for applicability, stakeholder involvement, and rigor of development. Recommendations were not always linked to evidence, and guideline authors were not transparent about how evidence limitations impacted their decisions. None of the guidelines recommended probiotics. Fourteen studies contributed data, with one pending. Probiotics reduced CDI among all studies and the adjusted model. No covariates were significantly associated with CDI. Subgroups suggested that high incidence did not affect probiotic effectiveness, and high-dose, multi-strain probiotics were more beneficial. Our estimate was robust to sensitivity analyses. Probiotics did not significantly affect SAE odds among all studies and the adjusted model. Increasing age was a significantly associated with SAEs. No SAEs were reportedly probiotics-related. For both outcomes, estimates were similar from data of obtained and not obtained studies. Confidence in estimates was moderate for both outcomes, due to low event rates. Current guidelines on CDI prevention did not adhere well to validated standards for development and reporting, most notably due to insufficient links between recommendations and supporting evidence. Our preliminary analysis suggests that probiotic prophylaxis is useful and safe for CDI prevention. / Thesis / Master of Science (MSc) / Clostridium difficile infection (CDI) is a common hospital-associated infection, and prevention is of high priority. We reviewed clinical practice guidelines on CDI prevention to summarize their recommendations, and assess the quality of guideline development and reporting. Furthermore, we analysed patient data from randomized clinical trials to obtain an overall estimate (meta-analysis) of whether using a novel strategy, probiotic prophylaxis, is effective and safe. The guidelines had several limitations, importantly that authors were not transparent about how recommendation were developed, and recommendations were not always linked to evidence. Although no guideline recommended using probiotics to prevent CDI, our advanced analysis of previously conducted trials suggested that it was an effective intervention, reducing infections by approximately 76%, and was not associated with differences in serious adverse events compared to participants not receiving probiotics. In summary, guidelines on CDI prevention should be improved, and probiotics may be considered as an additional strategy.

In traditional meta-analysis, a random-effects model is used to deal with heterogeneity and the random-effect is assumed to be normally distributed. However, this can be problematic in the presence of outliers. One solution involves using a heavy tailed distribution for the random-effect to more adequately model the excess variation due to the outliers. Failure to consider an alternative approach to the standard in the presence of unusual or outlying points can lead to inaccurate inference. A heavy tailed distribution is favoured because it has the ability to down-weight outlying studies appropriately, therefore the removal of a study does not need to be considered. In this thesis, the performance of the t-distribution and a finite mixture model are assessed as alternatives to the normal distribution through a comprehensive simulation study. The parameters varied are the average mean of the non-outlier studies, the number of studies, the proportion of outliers, the heterogeneity and the outlier shift distance from the average mean. The performance of the distributions is measured using bias, mean squared error, coverage probability, coverage width, Type I error and power. The methods are also compared through an empirical study of meta-analyses from The Cochrane Library (2008). The simulation showed that the performance of the alternative distributions is better than the normal distribution for a number of scenarios, particularly for extreme outliers and high heterogeneity. Generally, the mixture model performed quite well. The empirical study reveals that both alternative distributions are able to reduce the influence of the outlying studies on the overall mean estimate and thus produce more conservative p-values than the normal distribution. It is recommended that a practitioner consider the use of an alternative random-effects distribution in the presence of outliers because they are more likely to provide robust results. / Thesis / Master of Science (MSc)

Symptomatic spinal disorders affect a large proportion of the population and are associated with substantial morbidity, social burden, and economic impact. Spine surgery interventions can provide excellent results in carefully selected patients whose symptoms fail to improve with non-operative management, but an evidence-based approach is paramount to optimize outcomes and rigorous standards of health research methodology are critical to avoid misleading conclusions. This thesis aimed to investigate and apply modern innovations in health research methodology to the field of spine surgery. It consists of seven chapters divided between three sections: randomized controlled trials, observational studies, and systematic reviews and meta-analyses. By applying the findings of each chapter, clinicians, researchers, and other evidence users can advance the credibility of future research and enhance the care of patients with spinal disorders. / Thesis / Doctor of Philosophy (PhD)

Background and Objectives: I investigated the use of sensitivity analyses in assessing statistical results or analytical approaches in three different statistical issues: (1) accounting for within-subject correlations in analyzing discrete choice data, (2) handling both-armed zero-event studies in meta-analyses for rare event outcomes, and (3) incorporating external information using Bayesian approach to estimate rare-event rates. Methods: Project 1: I empirically compared ten statistical models in analyzing correlated data from a discrete choice survey to elicit patient preference for colorectal cancer screening. Logistic and probit models with random-effects, generalized estimating equations or robust standard errors were applied to binary, multinomial or bivariate outcomes. Project 2: I investigated the impacts of including or excluding both-armed zero-event studies on pooled odds ratios for classical meta-analyses using simulated data. Five commonly used pooling methods: Peto, Mantel-Haenszel fixed/random effects and inverse variance fixed/random effects, were compared in terms of bias and precision. Project 3: I explored the use of Bayesian approach to incorporate external information through priors to verify, enhance or modify the study evidence. Three study scenarios were derived from previous studies to estimate inhibitor rates for hemophilia A patients treated with rAHF-PFM: 1) a single cohort of previously treated patients, 2) individual patient data meta-analysis, and 3) an previously unexplored patient population with limited data. Results and Conclusion: Project 1: When within-subject correlations were substantial, the results from different statistical models were inconsistent. Project 2: Including both-armed zero-event studies in meta-analyses increased biases for pooled odd ratios when true treatment effects existed. Project 3: Through priors, Bayesian approaches effectively incorporated different types of information to strengthen or broaden research evidence. Through this thesis I demonstrated that when analyzing complicated health research data, it was important to use sensitivity analyses to assess the robustness of analysis results or proper choice of statistical models. / Dissertation / Doctor of Philosophy (PhD)

To date, only a few studies have investigated relationships between Diffusion-weighted imaging (DWI) and Vascular endothelial growth factor (VEGF) expression in tumors. The reported results are contradictory. The aim of the present analysis was to review the published results and to perform a meta-analysis regarding associations between apparent diffusion coefficients (ADC) derived from DWI and VEGF expression. MEDLINE library was screened for relationships between ADC and VEGF expression up to January 2019. Overall, 14 studies with 578 patients were identified. In 10 studies (71.4%) 3 T scanners were used and in four studies (28.6%) 1.5 T scanners. Furthermore, seven studies (50%) had a prospective design and seven studies (50%) had a retrospective design. Most frequently, prostate cancer, followed by rectal cancer, cervical cancer and esophageal cancer were identified. The pooled correlation coeffcient of all tumors was r = 0.02 [95% CI 0.26–0.21]. ADC values derived from routinely acquired DWI do not correlate with VEGF expression in various tumors. Therefore, DWI is not sensitive enough to reflect angiogenesis-related microstructure of tumors.

Ruminant livestock play a vital role in fulfilling the nutrient requirements of humans by providing protein, energy, and essential microminerals. With the increasing demand for meat and dairy products, the ruminant industry must continue to improve the productivity and efficiency of ruminant animals with limited resources while minimizing the environmental impact. Rumen fermentation is the focal point of the productivity and efficiency of the animal and numerous chemical, physical and biochemical interactions make the rumen a complex ecosystem. Therefore, improving the understanding of fermentation dynamics in a holistic manner and characterizing how fermentation varies in response to different nutrient supplies can greatly expand our knowledge on rumen fermentation to develop better engineered rumen manipulation strategies. The central aim of these investigations was to employ alternative analytical strategies for holistic exploration of complex relationships among rumen, animal, and dietary variables and to estimate rumen volatile fatty acid (VFA) dynamics under different nutrient supplies. The objective of the first study was to explore the strengths and limitations of mixed-model meta-analysis, recursive feature elimination (RFE), and additive Bayesian networking (ABN) in identifying relationships among diet, rumen, and milk performance variables. Both mixed-models and ABN agreed upon most of the variables and relationships identified while RFE failed to capture interactions. Given the capacity of mixed models for quantitative inquiry and the potential of ABN to illustrate complex associations in a more intuitive way, future investigations combining both approaches hold potential to explore intercorrelated data in a holistic manner. Followed by the successful use of ABN in the first study, the goal of a follow up study was to investigate the potential of two different network approaches to explore rumen level interactions using data generated in continuous culture experiments. Two network analysis approaches, EBIC-LASSO network (ELN) and Bayesian learning network (BLN) were leveraged to explore the relationships among rumen fermentation parameters in continuous culture experiments. Unidirectional ELN illustrated prominent variables while BLN, which produces a directed acyclic graph, identified directional relationships implying causality. Overall, both networking approaches demonstrate strengths in capturing connectedness and directionality of rumen fermentation variables. In a complementary line of work, the next experiment focused on developing an alternative method for iso-tope based assessments to produce less expensive, and more efficient screening of fermentation conditions driven by diet. Cannulated wethers were used in this study and 4 dietary treatments combining lowly and highly degradable fiber (timothy hay and beet pulp, respectively) and protein (heat-treated soybean meal and soybean meal, respectively) were tested. Results indicated that fluid volume of the rumen and the rate of passage were influenced by protein, but not fiber, source. Higher rumen volumes and lower passage rates were associated with heat-treated soybean meals. The effect of dietary treatments on VFA absorption dynamics was prominent compared to the minimal changes in production dynamics. Overall, heat-treated soybean meal appears to influence VFA disappearance resulting in low concentrations within the rumen, but greater flux of VFA disappearance. In conclusion, this method demonstrated the capacity to estimate VFA dynamics beyond concentrations and molar proportions while being cost effective and more physiologically relevant. In a fourth study, we sought to investigate the growth performance and rumen VFA profile in response to different planes of nutrients and naturally occurring coccidiosis. Coccidiosis infection altered rumen isobutyrate concentrations and tended to alter major VFA concentrations suggesting the need of future work to explore coccidiosis effects on rumen fermentation. The first two investigations highlighted the potential and strength of leveraging alternative analytical tools to complement statistical approaches generally used in ruminant nutrition while concurrently improving ability to explain complex associations in the rumen. The third and fourth projects characterized the rumen VFA dynamics and profile in response to the different nutrient degradability and health status, respectively. Collectively, these investigations contribute to better understanding of rumen dynamics through novel analytical and experimental approaches. / Doctor of Philosophy / With increasing global population, income, urbanization, and changes in dietary habits, the demand for meat and milk continues to grow. The ruminant animal industries (beef cattle, dairy cattle, sheep, goat, and buffalo) carry the burden of increasing production utilizing limited resources while minimizing the negative environmental impact caused by ruminant operations. To achieve this goal the productivity of the animal must be increased, and in order to increase the efficiency of production a better understanding of factors driving the production is critical. Ruminant animals have the unique ability to convert plant fiber into human edible milk and meat through a process that predominantly occurs in the special gut compartment called the rumen. In this process several compounds are produced, and among those volatile fatty acid (VFA) is of utmost importance because it fulfills energy demands for growth, production and reproduction. The rumen is a complex ecosystem consisting of numerous variables and associations. Understanding those relationships is crucial to manipulate rumen mechanisms. The overall objective of this work was to evaluate the potential of alternative statistical approaches, which demonstrated success in other disciplines, for better depiction of complex associations and characterization of production and absorption mechanisms of rumen VFA in response to different nutrient supplies. The objective of first investigation was to evaluate a feature selection method (recursive feature elimination; RFE) and a network approach (Additive Bayesian network; ABN) concurrently with a standard variable selection method (mixed model meta-analysis) commonly used to develop animal nutrition models. We attempted to find out the most important dietary, rumen, and animal variables for milk yield, milk fat and protein content as an example. Results indicate that the network approach was well aligned with the standard tool and can be used as a complementary approach. In our second investigation, we leveraged two networking analyses, a frequentist network which was unidirectional and a Bayesian network which was directional to explore rumen level interactions. The unidirectional network approach highlighted the most important variables in the rumen and numerous relationships among these variables. The directional network was more useful in understanding of causal associations within the system. In the third experiment we estimated the production and absorption of VFA in response to the different protein (heat-treated and regular soybean meal) and fiber (timothy hay and beet pulp) sources. The results revealed that the production of VFA was minimally affected by the diet, but the absorption was higher with heat-treated soybean meal. Our last project investigated the effect of parasitic infection, i.e., coccidiosis, and high and low levels of nutrition on growth and rumen VFA of growing lambs. Infection of coccidiosis altered a minor VFA (isobutyrate) and tended to alter total and major VFA (acetate and propionate). All these findings help to improve our understanding of rumen fermentation and subsequently develop strategies to manipulate rumen fermentation to enhance efficiency and productivity.

Abstract: Objective: This meta-analysis reviews the evidence for training in patients with tension-type headache on pain intensity and headache frequency. Method: Electronic databases were searched for randomized controlled trials evaluating training on patients with tension-type headache. Data was extracted by the reviewer. Methodological quality was assessed using risk of bias two and a meta-analysis was made using Revman 5. The quality of the evidence was calculated using GRADEproGDT. Results: Regarding pain intensity four studies were included (n = 330 participants). The meta-analysis indicates that training is effective in reducing pain intensity in patients with tension-type headache. This result does not reach a clinical important difference. The quality of evidence is moderate. For headache frequency three studies were included in the meta-analysis (n = 290 participants). The meta-analysis showed that training is effective in reducing headache frequency in patients with tension-type headache. This change does not reach a clinical important difference. The quality of evidence for this result is high. Conclusion: There is moderate quality of evidence that exercise reduces pain intensity in patients with tension-type headache. There is high quality evidence that exercise reduces headache frequency in patients with tension-type headache. Neither of these results reach a clinically important difference. This may be due to the active control groups and needs to be researched further.