Half Empty or Half Full?

Abstract

Logic, anecdote, and data collectively suggest that early detection and prompt intervention in critical illness improve outcomes at lower costs. Process engineering (e.g., standardization and aggregation of interventions into bundles ) has increased care effectiveness. The next step involves transforming critical care from reactive to preemptive practice through recognition of impending collapse. The excursion of conventional measures, such as traditional vital signs (VS), urine output, and lactate, beyond normal ranges is insufficient to predict critical illness. First, such excursions are used to classify established illness. Acute physiology scores depend on those measures such that prediction and occurrence are indistinguishable. Second, they do not distinguish decompensation that requires life-saving interventions (LSIs) from compensated responses; two decades of experience with the systemic inflammatory response syndrome criteria suggest as much. Third, they occur in the absence of pathology: athletes commonly display hyperthermia, tachycardia, tachypnea, relative hypotension, and low urine output.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2010
Accession Number
ADA629374

Entities

People

  • Andriy I Batchinsky
  • Leopoldo C. Cancio
  • Timothy G. Buchman

Organizations

  • United States Army Institute of Surgical Research

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Autonomic Nervous System
  • Department Of Defense
  • Disease Attributes
  • Health Services
  • Heart Rate
  • Information Operations
  • Information Science
  • Machine Learning
  • Monitoring
  • Multivariate Analysis
  • Nervous System
  • Patient Care
  • Physiology
  • Signal Processing
  • Standards
  • Statistics
  • Vital Signs

Readers

  • Cardiovascular Physiology
  • Gulf War Illness and Chronic Multisymptom Illness in Veterans.
  • Systems Analysis and Design