World Neurosurg
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It is essential for any epidemiologic and clinical investigation to determine the appropriate covariates for which to ascertain measures and subsequently model. A number of recent articles have sought to elucidate covariate selection in the context of data analysis. Unfortunately, few articles characterize covariate selection in the context of data collection and discuss their principles under the assumption that data are measured and available for analyses. ⋯ To the extent possible, this paper attempts to communicate these principles clearly and in the absence of advanced causal inference terminology. Finally, this paper provides a conceptual framework for covariate inclusion and exclusion with respect to data analysis and regression modeling. Specifically, this framework suggests that regression models 1) include all known common cause covariates; 2) include all sociodemographic covariates; 3) exclude any covariate that is known to be both a consequence of the exposure and cause of the outcome; and 4) generally, for every term included in the statistical model, there should be at least 10 observations in the data set.
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Undergraduate neurosurgery conferences are acknowledged to play an important role in bridging the gap between a limited exposure to neurosurgery within medical schools and a highly competitive application process. Hands-on workshops are attractive for any conference but can be prohibitively expensive, especially for student societies. ⋯ These workshop models have been praised by medical students for increasing exposure and awareness toward neurosurgical procedures and the sophistication of investigations used by the specialty. Consultant neurosurgeons have praised the simulation provided by these models as closely mimicking the procedure in reality.
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Biomedical research can generally be categorized into 1 of 3 aims: describing the occurrence of disease; identifying persons with or at increased risk of disease including diagnostic and prognostic studies; and explaining the occurrence of disease including etiologic and efficacy studies.
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Spinal cord injury (SCI) triggers a signalling cascade that produces oxidative stress and damages the spinal cord. Voltammetry is a clinically accessible technique to detect, monitor, and guide correction of this potentially reversible secondary injury mechanism. Voltammetry is well suited for clinical translation because the method is inexpensive, simple, rapid, and portable. Voltammetry relies on the measurement of anodic current from a reagent-free, electrochemical reaction on the surface of a small electrode. ⋯ AC measured by CNT-SPE demonstrated a time- and severity-dependent decline after SCI. Plasma AC could serve as a surrogate marker for spinal cord AC.