Explore the vast range of titles available.

The public is bombarded daily with reports about risk factors, many conflicting with each other, other accepted as \"scientific truth\" for awhile, then scientifically disproved, yet others questionable that later prove to be true. Physicians are faced with trying to make sense of those conflicting or questionable results in the scientific literature in order to guide their patients to the best possible decisions. The situation is not much easier for scientists who may waste years of their productive life, and considerable resources, basing their research efforts on what prove to be misleading earlier research findings. What this book does is to present, in non \"academese\" and with many examples from the general media and scientific journals, a guide to a critical reading of research reports, which, in turn, serves as a guide to researchers as to which approaches are likely to be regarded with raised eyebrows, and what they need to do to generate results that will be taken seriously. This stimulating and helpful book was written for informed consumers and physicians as well as for scientists evaluating the risk research literature or contemplating projects on risk research.

To determine the advantages and disadvantages of a stepped wedge design for a specific clinical application. The clinical application was a pragmatic cluster randomized surgical trial intending to find an increased percentage of curable recurrences in patients in follow-up after colorectal cancer. Advantages and disadvantages of the stepped wedge design were evaluated, and for this application, new advantages and disadvantages were presented. A main advantage of the stepped wedge design was that the intervention rolls out to all participants, motivating patients and doctors, and a large number of patients who were included in this study. The stepped wedge design increased the complexity of the data analysis, and there were concerns regarding the informed consent procedure. The repeated measurements may bring burden to patients in terms of quality of life, satisfaction, and costs. The stepped wedge design is a strong alternative for pragmatic cluster randomized trials. The known advantages hold, whereas most of the disadvantages were not applicable to this application. The main advantage was that we were able to include a large number of patients. Main disadvantages were that the informed consent procedure can be problematic and that the analysis of the data can be complex.

In a companion paper by Cohen-Adad et al . we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assessing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject dataset across 19 centers and a multi-subject dataset across 42 centers (for a total of 260 participants), spanning the three main MRI manufacturers: GE, Philips and Siemens. Both datasets are publicly available via git-annex. Data were analysed using the Spinal Cord Toolbox to produce normative values as well as inter/intra-site and inter/intra-manufacturer statistics. Reproducibility for the spine generic protocol was high across sites and manufacturers, with an average inter-site coefficient of variation of less than 5% for all the metrics. Full documentation and results can be found at https://spine-generic.rtfd.io/ . The datasets and analysis pipeline will help pave the way towards accessible and reproducible quantitative MRI in the spinal cord. Measurement(s) spinal cord Technology Type(s) magnetic resonance imaging Factor Type(s) manufacturer • site Sample Characteristic - Organism Homo sapiens Sample Characteristic - Location Canada • Switzerland • Australia • United States of America • United Kingdom • Germany • French Republic • Czech Republic • Italy • Japan • Kingdom of Spain • China Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14052269

Mendelian randomisation (MR) studies allow a better understanding of the causal effects of modifiable exposures on health outcomes, but the published evidence is often hampered by inadequate reporting. Reporting guidelines help authors effectively communicate all critical information about what was done and what was found. STROBE-MR (strengthening the reporting of observational studies in epidemiology using mendelian randomisation) assists authors in reporting their MR research clearly and transparently. Adopting STROBE-MR should help readers, reviewers, and journal editors evaluate the quality of published MR studies. This article explains the 20 items of the STROBE-MR checklist, along with their meaning and rationale, using terms defined in a glossary. Examples of transparent reporting are used for each item to illustrate best practices.

For researchers using observational data, a useful way to answer a causal question is to design the target trial that would answer it and then emulate its protocol. The example of the HIV-treatment-as-prevention strategy illustrates the benefits of this approach.

To introduce a new design that explores how an acute exposure might lead to a sustained change in the risk of a recurrent outcome. The exposure-crossover design uses self-matching to control within-person confounding due to genetics, personality, and all other stable patient characteristics. The design is demonstrated using population-based individual-level health data from Ontario, Canada, for three separate medical conditions (n > 100,000 for each) related to the risk of a motor vehicle crash (total outcomes, >2,000 for each). The exposure-crossover design yields numerical risk estimates during the baseline interval before an intervention, the induction interval immediately ahead of the intervention, and the subsequent interval after the intervention. Accompanying graphs summarize results, provide an intuitive display to readers, and show risk comparisons (absolute and relative). Self-matching increases statistical efficiency, reduces selection bias, and yields quantitative analyses. The design has potential limitations related to confounding, artifacts, pragmatics, survivor bias, statistical models, potential misunderstandings, and serendipity. The exposure-crossover design may help in exploring selected questions in epidemiology science.

Injury and illness surveillance, and epidemiological studies, are fundamental elements of concerted efforts to protect the health of the athlete. To encourage consistency in the definitions and methodology used, and to enable data across studies to be compared, research groups have published 11 sport-specific or setting-specific consensus statements on sports injury (and, eventually, illness) epidemiology to date. Our objective was to further strengthen consistency in data collection, injury definitions and research reporting through an updated set of recommendations for sports injury and illness studies, including a new Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist extension. The IOC invited a working group of international experts to review relevant literature and provide recommendations. The procedure included an open online survey, several stages of text drafting and consultation by working groups and a 3-day consensus meeting in October 2019. This statement includes recommendations for data collection and research reporting covering key components: defining and classifying health problems; severity of health problems; capturing and reporting athlete exposure; expressing risk; burden of health problems; study population characteristics and data collection methods. Based on these, we also developed a new reporting guideline as a STROBE Extension—the STROBE Sports Injury and Illness Surveillance (STROBE-SIIS). The IOC encourages ongoing in- and out-of-competition surveillance programmes and studies to describe injury and illness trends and patterns, understand their causes and develop measures to protect the health of the athlete. Implementation of the methods outlined in this statement will advance consistency in data collection and research reporting.

AbstractObjectivesTo study the impact of blinding on estimated treatment effects, and their variation between trials; differentiating between blinding of patients, healthcare providers, and observers; detection bias and performance bias; and types of outcome (the MetaBLIND study).DesignMeta-epidemiological study.Data sourceCochrane Database of Systematic Reviews (2013-14).Eligibility criteria for selecting studiesMeta-analyses with both blinded and non-blinded trials on any topic.Review methodsBlinding status was retrieved from trial publications and authors, and results retrieved automatically from the Cochrane Database of Systematic Reviews. Bayesian hierarchical models estimated the average ratio of odds ratios (ROR), and estimated the increases in heterogeneity between trials, for non-blinded trials (or of unclear status) versus blinded trials. Secondary analyses adjusted for adequacy of concealment of allocation, attrition, and trial size, and explored the association between outcome subjectivity (high, moderate, low) and average bias. An ROR lower than 1 indicated exaggerated effect estimates in trials without blinding.ResultsThe study included 142 meta-analyses (1153 trials). The ROR for lack of blinding of patients was 0.91 (95% credible interval 0.61 to 1.34) in 18 meta-analyses with patient reported outcomes, and 0.98 (0.69 to 1.39) in 14 meta-analyses with outcomes reported by blinded observers. The ROR for lack of blinding of healthcare providers was 1.01 (0.84 to 1.19) in 29 meta-analyses with healthcare provider decision outcomes (eg, readmissions), and 0.97 (0.64 to 1.45) in 13 meta-analyses with outcomes reported by blinded patients or observers. The ROR for lack of blinding of observers was 1.01 (0.86 to 1.18) in 46 meta-analyses with subjective observer reported outcomes, with no clear impact of degree of subjectivity. Information was insufficient to determine whether lack of blinding was associated with increased heterogeneity between trials. The ROR for trials not reported as double blind versus those that were double blind was 1.02 (0.90 to 1.13) in 74 meta-analyses.ConclusionNo evidence was found for an average difference in estimated treatment effect between trials with and without blinded patients, healthcare providers, or outcome assessors. These results could reflect that blinding is less important than often believed or meta-epidemiological study limitations, such as residual confounding or imprecision. At this stage, replication of this study is suggested and blinding should remain a methodological safeguard in trials.