A Novel Approach for Identifying Individual Responses to Compromised Cerebral Oxygenation Challenges and Guided Intervention Using Compensatory Reserve Measurement

Abstract

One of the primary challenges of effectively treating bleeding trauma patients is the difficulty with using relatively traditional vital signs to provide early and accurate detection for the onset of hemorrhagic shock. At present, an individual-specific, non-invasive method for early detection of patients at risk of progression to shock is a CDID gap requirement. The overall objectives of this research is to: (1) develop and validate a new algorithm that will provide early identification of hemorrhagic shock using real-time machine-learning technology for analysis of changes in features of non-invasive photoplethysmographic (PPG) waveforms specific to individual patients and clinical conditions (i.e., precision medicine); and (2) identify clinically useful genetic and epigenetic correlates of tolerance to blood loss as well as identify gene expression and metabolic changes that could reveal underlying molecular mechanism.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2021
Accession Number
AD1168862

Entities

People

  • VĂ­ctor A. Convertino

Tags

Communities of Interest

  • Autonomy
  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Artificial Intelligence
  • Birds
  • Burns
  • Cardiovascular Physiological Phenomena
  • Cardiovascular Surgery
  • Combat Casualty Care
  • Data Analysis
  • Dermatologic Agents
  • Health Services
  • Hemorrhage
  • Hemorrhagic Shock
  • Information Science
  • Machine Learning
  • Medical Personnel
  • Personnel Management
  • Statistical Analysis

Fields of Study

  • Medicine

Readers

  • Cardiovascular Physiology
  • Oncology
  • Oncology and Biomarker-Based Cancer Detection.

Technology Areas

  • AI & ML
  • Biotechnology