Chest
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Retraction Of Publication
Clinical and Genetic Spectrum of Children with Primary Ciliary Dyskinesia in China.
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Cross-sectional studies are observational studies that analyze data from a population at a single point in time. They are often used to measure the prevalence of health outcomes, understand determinants of health, and describe features of a population. Unlike other types of observational studies, cross-sectional studies do not follow individuals up over time. ⋯ They are useful for establishing preliminary evidence in planning a future advanced study. This article reviews the essential characteristics, describes strengths and weaknesses, discusses methodological issues, and gives our recommendations on design and statistical analysis for cross-sectional studies in pulmonary and critical care medicine. A list of considerations for reviewers is also provided.
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Cohort studies are types of observational studies in which a cohort, or a group of individuals sharing some characteristic, are followed up over time, and outcomes are measured at one or more time points. Cohort studies can be classified as prospective or retrospective studies, and they have several advantages and disadvantages. This article reviews the essential characteristics of cohort studies and includes recommendations on the design, statistical analysis, and reporting of cohort studies in respiratory and critical care medicine. Tools are provided for researchers and reviewers.
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Mortality has long been used as a primary end point for randomized controlled trials in critical care. Recently, a plurality of trials targeting mortality end points as their primary outcome has failed to detect a difference between study arms. ⋯ We explore some of the reasons why such trials may be biased toward a neutral result, as well as reasons to consider alternative end points that are better coupled to the expected therapeutic effect. We also discuss to what extent mortality as a binary outcome is patient-important in the ICU.
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Sample size determination is an essential step in planning a clinical study. It is critical to understand that different study designs need different methods of sample size estimation. Although there is a vast literature discussing sample size estimation, incorrect or improper formulas continue to be applied. ⋯ To assist clinical researchers in performing sample size calculations, we have developed an online calculator for common clinical study designs. The calculator is available at http://riskcalc.org:3838/samplesize/. Finally, we offer our recommendations on reporting sample size determination in clinical studies.