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Modeling the clinical predictivity of palpitation symptom reports : mapping body cognition onto cardiac and neurophysiological measurements / Mapping body cognition onto cardiac and neurophysiological measurements

This dissertation models the relationship between symptoms of heart rhythm
fluctuations and cardiac measurements in order to better identify the probabilities of
either a primarily organic or psychosomatic cause, and to better understand cognition of
the internal body. The medical system needs to distinguish patients with actual cardiac
problems from those who are misperceiving benign heart rhythms due to psychosomatic
conditions. Cognitive neuroscience needs models showing how the brain processes
sensations of palpitations. Psychologists and philosophers want data and analyses that
address longstanding controversies about the validity of introspective methods. I
therefore undertake a series of measurements to model how well patient descriptions of heartbeat fluctuations correspond to cardiac arrhythmias.

First, I employ a formula for Bayesian inference and an initial probability for disease. The presence of particular phrases in symptom reports is shown to modify the probability that a patient has a clinically significant heart rhythm disorder. A second measure of body knowledge accuracy uses a corpus of one hundred symptom reports to estimate the positive predictive value for arrhythmias contained in language about palpitations. This produces a metric representing average predictivity for cardiac arrhythmias in a population. A third effort investigates the percentage of patients with palpitations report actually diagnosed with arrhythmias by examining data from a series of studies. The major finding suggests that phenomenological reports about heartbeats are as or are more predictive of clinically significant arrhythmias than non-introspection-based data sources. This calculation can help clinicians who must diagnose an organic or psychosomatic etiology. Secondly, examining a corpus of reports for how well they predict the presence of cardiac rhythm disorders yielded a mean positive predictive value
of 0.491. Thirdly, I reviewed studies of palpitations reporters, half of which showed
between 15% and 26% of patients had significant or serious arrhythmias. In addition, evidence is presented that psychosomatic-based palpitation reports are likely due to cognitive filtering and processing of cardiac afferents by brainstem, thalamic, and cortical neurons. A framework is proposed to model these results, integrating neurophysiological, cognitive, and clinical levels of explanation. Strategies for developing therapies for patients suffering from identifiably psychosomatic-based palpitations are outlined. / text

Identiferoai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2011-12-4735
Date30 January 2012
CreatorsMcNally, Robert Owen
Source SetsUniversity of Texas
LanguageEnglish
Detected LanguageEnglish
Typethesis
Formatapplication/pdf

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