Sensitivity, which denotes the proportion of subjects correctly given a positive assignment out of all subjects who are actually positive for the outcome, indicates how well a test can classify subjects who truly have the outcome of interest. Specificity, which denotes the proportion of subjects correctly given a negative assignment out of all subjects who are actually negative for the outcome, indicates how well a test can classify subjects who truly do not have the outcome of interest. Positive predictive value reflects the proportion of subjects with a positive test result who truly have the outcome of interest. Negative predictive value reflects the proportion of subjects with a negative test result who truly do not have the outcome of interest. Sensitivity and specificity are inversely related, wherein one increases as the other decreases, but are generally considered stable for a given test, whereas positive and negative predictive values do inherently vary with pre-test probability (e.g., changes in population disease prevalence). This article will further detail the concepts of sensitivity, specificity, and predictive values using a recent real-world example from the medical literature.

Blinding mitigates several sources of bias which, if left unchecked, can quantitively affect study outcomes. Blinding remains under-utilized, particularly in non-pharmaceutical clinical trials, but is often highly feasible through simple measures. Although blinding is generally viewed as an effective method by which to eliminate bias, blinding does also pose some inherent limitations, and it behooves clinicians and researchers to be aware of such caveats. This article will review general principles for blinding in clinical trials, including examples of useful blinding techniques for both pharmaceutical and non-pharmaceutical trials, while also highlighting the limitations and potential consequences of blinding. Appropriate reporting on blinding in trial protocols and manuscripts, as well as future directions for blinding research, will also be discussed.

Evidence-based medicine is predicated on the integration of best available research evidence with clinical expertise and patient values to inform care. In medical research, several distinct measures are commonly used to describe the associations between variables, and a sound understanding of these pervasive measures is foundational in the clinician’s ability to interpret, synthesize, and apply available evidence from the medical literature. Accordingly, this article aims to provide an educational tutorial/topic primer on some of the most ubiquitous measures of association and risk quantification in medical research, including odds ratios, relative risk, absolute risk, and number needed to treat, using several real-world examples from the medical literature.

This narrative review synthesizes current evidence on the medical management of nocturnal polyuria, including antidiuretic replacement therapy as well as other emerging modalities, with particular emphasis on areas of active investigation and future research directions. Relative to earlier formulations, the pharmacological profiles of novel desmopressin acetate nasal spray and orally disintegrating tablet formulations appear favorable in optimizing the balance between efficacy and safety. Additionally, several highly selective small-molecule arginine vasopressin 2 receptor agonists are under active development, while appropriately timed short-acting diuretics, pharmacotherapy for hypertension, nonsteroidal anti-inflammatory drugs, and sex hormone replacement therapy are also a focal point of extensive ongoing nocturnal polyuria research. Emerging laboratory technologies now make feasible a sub-stratification of nocturnal polyuria patients into substrate-based phenotypes for individualized treatment. An increasingly refined understanding of the pathogenesis of nocturnal polyuria, and arginine vasopressin dysregulation in particular, has also introduced new opportunities for point-of-care testing in patients with nocturnal polyuria.