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Combinatorial approaches to physiologic pattern recognition (CAPPER)

Detailed Technology Description

None

*Abstract

The inventors have developed a novel algorithm and software for diagnostic, monitoring, and prognostic applications. Populations of interest include those individuals with Sleep Disordered Breathing, Chronic Kidney Disease, those who are critically ill, and those with heart failure or hypertension.This invention involves a mathematical model that utilizes combinatorial approaches to recognize physiological patterns. The algorithm consists of determining physiological inputs like heart rate over a certain time frame. The physiological inputs are then converted to binary numbers by comparing values taken at consecutive times. The binary numbers are then combined and analyzed to identify common patterns.Applications1) Mechanical ventilationMechanical ventilation provokes very complex cardiopulmonary, neurophysiologic and biological (e.g. hormonal, chemcial and molecular) interactions. Injudicious ventilation can induce lung injury, compromise systemic hemodynamics (blood pressure and organ flow), cause patient discomfort and distress, modulate the inflammatory response, and prolong the period for which ventilatory support is required. Our approach can be used to characterize integrated physiologic responses to this intrusive intervention, and identify the dynamic signatures that are associated with patient:ventilator conflict. The ability to define and measure conflict will allow titration of support to minimize adverse effects and promote discovery of novel treatment approaches.2) Sleep Disordered BreathingThere is increasing awareness that Sleep-Disordered Breathing, including Sleep Apnea is a major public health problem. Respiratory, neurophysiologic, and cardiovascular mechanisms each play a role in compromising patient health, and their interactions reflect formidable complexity. This complexity escapes the current state of the practice, in which these variables are largely evaluated in isolationcounting the number of apneic events, measuring the electroencephalographic frequency, and monitoring the level of oxygen saturation, for example. Current diagnostic approaches to Sleep-Disordered Breathing are labor and resource intensive, imprecise, and poorly suited to close monitoring and titration of therapy. Our approach could be used to automate screening for Sleep-Disordered Breathing, provide rigorous descriptions of the patients integrated physiology that may be applied to develop novel means for risk stratification, and for discovery of the underlying mechanism(s) of disease that would lead to development of novel treatments and facilitate monitoring of systemic response to treatment.3) Patient monitoring in lower acuity settingsThe potential to identify physiologic signatures that suggest an impending crisis- such as a rising respiratory rate with declining tidal volumes ascertained by impedance plethysmography accompanied by intermittent declines in heart rate- is well within the capacity of this algorithm. Importantly, the combinatorial analysis approach will allow identification of complex dynamical signatures- that could elude inspection by humans- associated with impending respiratory failure, early sepsis, or impending cardiac failure. In essence, this will allow categorization of patient physiology at each point in time (as stable or suggestive of a risk for instability). This approach- defining the integrated physiology of the patient- is automated, addresses overall physiologic well-being, and can objectively integrate and interpret multiple simultaneous data streams. Such software could be used to monitor high-risk patients in less acute care settings, adding to patient safety. 4)Dialysis and chronic kidney diseasePersons with endstage renal disease display complex disorders of breathing, vascular regulation, and neurophysiology arising in part from the uremic milieuFor example, non-obstructive sleep disordered breathing is highly prevalent. Interactions between the level of uremic toxins and cardiovascular, pulmonary, and neurophysiologic disorders are just beginning to be understood. An integrated description of the patients physiologic behaviors could be used to assess the adequacy of dialysis and quantitatively monitor the complications of uremia in both the outpatient (>350,000 patients) and inpatient setting. These issues are also germane to those patients with advanced chronic kidney disease (>1,000,000 patients), in whom monitoring for uremia or complications of inadequate renal function is currently entirely qualitative.5) Heart failure and hypertensionSimilar to the aforementioned groups, individuals with heart failure and hypertension display complex neurophysiologic and vascular maladaptations. Tools for quantifying such derangements that are integrative (address more than one system simultaneously) and easily deployed for routine, inexpensive home/ambulatory use could aid in diagnosis, risk stratification, titration of therapy, and monitoring for complications and drug discovery and assessment.Stage of DevelopmentInventors have fully operational implementations of the software that run in Visual Basic, and a less detailed implementation that runs in Mathematica. They have completed initial testing and refinement using synthetic data from a detailed model of neurorespiratory regulation (Slutsky and Khoo), and have begun the analysis of human data on a pilot basis.

*Principal Investigator

Name: Philip Crooke, Professor of Mathematics

Department:

Name: John Hotchkiss, Assistant Professor, Critical Care Medic

Department: Med-Critical Care Medicine

Name: Mark Sanders, Professor of Medicine

Department:

Country/Region

USA