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A more holistic view of the logarithmic dose-response curve offers greater insights into insulin responses.

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November 2024

Laboratory of Biocomplexity and Engineering Biology, School of Medicine, The Chinese University of Hong Kong, Shenzhen, China; Futian Biomedical Innovation R&D Center, The Chinese University of Hong Kong, Shenzhen, China; Ciechanover Institute of Precision and Regenerative Medicine, School of Medicine, The Chinese University of Hong Kong, Shenzhen, China; Center for Endocrinology and Metabolic Diseases, Second Affiliated Hospital, The Chinese University of Hong Kong, Shenzhen, China. Electronic address:

The stimulus-response curve is usually modeled by the Hill function due to its simplicity and clear molecular mechanisms (Michaelis-Menten type of kinetics). Unfortunately, the mechanisms do not explain why the stimulus is ubiquitously measured by logarithmic dose rather than the dose itself and why the log(dose)-response curve possesses such fine properties as symmetry and wide adjustability. Here, the dose-response is considered from a holistic perspective spanning multiple biological levels from molecules to the whole organism, which reveals that an appropriate model for log(dose) response is the cumulative normal distribution (CND) function, which had only statistical implication previously but now possess mechanistic-statistical duality.

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The waveform of ventricular action potential (AP) is a key determinant of the cardiac cycle, a marker of beating pathophysiology, and a target for anti-arrhythmic drug design. The information contained in the waveform, though, is limited to the actual dynamics of the AP under consideration. By measuring quasi-instantaneous current-voltage relationships during repolarization, I propose a three-dimensional representation of the ventricular AP which includes potential dynamic responses that the beat can show when electrically perturbed.

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Background: Considering multiple endpoints in clinical trials provide a more comprehensive understanding of treatment effects and may lead to increased power or reduced sample size, which may be beneficial in rare diseases. Besides the small sample sizes, allocation bias is an issue that affects the validity of these trials. We investigate the impact of allocation bias on testing decisions in clinical trials with multiple endpoints and offer a tool for selecting an appropriate randomization procedure (RP).

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Research on best practices in theory assessment highlights that testing theories is challenging because they inherit a new set of assumptions as soon as they are linked to a specific methodology. In this article, we integrate and build on this work by demonstrating the breadth of these challenges. We show that tracking auxiliary assumptions is difficult because they are made at different stages of theory testing and at multiple levels of a theory.

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Introduction: The transition of experience from unconscious to conscious, the emergent process, is a crucial topic in consciousness studies. Three frameworks exist to explain the process: (1) consciousness arises in an all-or-none manner; (2) consciousness arises gradually; (3) consciousness arises either all at once or gradually, depending on the level of stimulus processing (low- vs. high-level).

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