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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance
A
Examples of Physiological and Cognitive Markers of Performance
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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance
TABLE A-1 Examples of Metabolic Markers
Tissue, Organ, Function
Intermediate Marker
Source
Body temperature
Cold strain index
Esophageal telemetry device
Galvanic skin response
Heart rate
Heat flux
Oral temperature
Reaction time
Skin temperature
Physiological strain index
Hydration
Aldosterone
Arginine
Blood pressure
Heart rate
Hydration status from bioelectrical impedance
Sodium
Total body water
Vasopressin
Blood
Saliva
Urine
Physical activity/energy expenditure
Accelerometers
Activity logs
Activity monitors (integrated, i.e., body movement, heart rate, and core temperature)
Dietary questionnaires
Doubly labeled water
Foot-ground contact/body weight
Glucose
Heart rate monitors
Insulin
Insulin-like growth factor-1
Lactate
Blood
NOTE: Metabolic monitoring biomarkers can be categorized according to outcome function or intermediate measure that can be quantified to reflect the outcome function. This table summarizes outcome functions of various organs/systems/physiological/ psychological states and some intermediate biomarkers that might be used to predict or quantify these outcome functions and optimal performance. In general, it was felt that no single intermediate biomarker accurately predicts outcome function. Accurate measures of outcome function are often invasive and not applicable to field situations. More emphasis should be placed on developing noninvasive measures that accurately predict peak performance or catastrophic failure of a given organ/system or physiological/psychological state.
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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance
Performance, Outcome
Measure
Heat stress
Hypo- and hyperthermia
Core temperature
Cognitive performance
De- and overhydration
Fatigue
Heat exhaustion
Heat tolerance
Muscular endurance
Body-weight change
Eye pressure
Plasma volume, osmolarity
Saliva flow
Skin turgor
Urine color
Urine specific gravity, osmolarity
Urine volume
Cognition
Hypo- and hyperglycemia
Heat cramps
Heat exhaustion
Sunstroke
Body weight
Calorimetry (direct and indirect)
Lean body mass
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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance
TABLE A-2 Examples of Brain Function Markers
Tissue, Organ, Function
Intermediate Marker
Source
Cognitive
Blood flow
Electrocardiogram
Functional magnetic resonance imaging
Imaging
Magneto-electroencephalography
Metabolism
Positron emission tomography
Spectroscopy
Mood
Odor profiles
Sleep
Ambulatory sleep monitor
Electrocardiogram pattern
Stress response
Autonomic nervous system
Cortisol
Dehydroepiandrosterone
Growth hormones
Heart rate variability
Impedance
Insulin-like growth factor-1
Neuropeptide Y
Neurotransmitters
Norepinephrine
Other hormones
Prolactin
Stress hormones
Testosterone
Blood
Salivaa
Urineb
NOTE: Metabolic monitoring biomarkers can be categorized according to outcome function or intermediate measure that can be quantified to reflect the outcome function. This table summarizes outcome functions of various organs/systems/ physiological/psychological states and some intermediate biomarkers that might be used to predict or quantify these outcome functions and optimal performance. In general, it was felt that no single intermediate biomarker accurately predicts outcome function. Accurate measures of outcome function are often invasive and not applicable to field situations. More emphasis should be placed on developing noninvasive measures that accurately predict peak performance or catastrophic failure of a given organ/system or physiological/psychological state.
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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance
Performance, Outcome
Measure
Focused attention
Memory
Problem solving
Ratings of perceived exertion
Self-assessment scales
Appropriate relative to situation
Fear
Modified STROOP
Profile mood
Self-assessment scales
Visual analog
Reaction time
Sleepiness/alertness
Task performance
Self-assessment scales
Appropriate activation relative to situation
Self-assessment scales
a Salivary cortisol is an accurate measure of single plasma-free cortisol at the time point collected.
b Urinary cortisol measured in 24-hour urine reflects average cortisol secretion over 24 hours.
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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance
TABLE A-3 Examples of Bone Markers
Tissue, Organ, Function
Intermediate Marker
Source
Bone
Collagen breakdown products
Carboxy-terminal telepeptide
Deoxypridinoline
Hydroproline
N-telepeptide
Pyridinoline
Plasma
Urine
Cytokines
Interleukin-1 and -6
Tumor necrosis factor
Transforming growth factor
Endocrine markers
Calcitonin
Growth hormone
Insulin-like growth factor-1
Osteocalcin
Parathyroid hormone
Thyroid hormones
Enzymes
Alkaline phosphatase
Bone-specific alkaline
Phosphatase
Resorption markers
24-hour urinary calcium
Calcium balance
Phosphatase
Tartrate-resistant acid
NOTE: Metabolic monitoring biomarkers can be categorized according to outcome function or intermediate measure that can be quantified to reflect the outcome function. This table summarizes outcome functions of various organs/systems/physiological/ psychological states and some intermediate biomarkers that might be used to predict or quantify these outcome functions and optimal performance. In general, it was felt that no single intermediate biomarker accurately predicts outcome function. Accurate measures of outcome function are often invasive and not applicable to field situations. More emphasis should be placed on developing noninvasive measures that accurately predict peak performance or catastrophic failure of a given organ/system or physiological/psychological state.
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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance
Performance, Outcome
Measure
Bone fracture, including stress fracture
Edema
Inflammation/damage
Pain
Weakness
Bone mineral density:
Dual-energy X-ray absorptiometry
Ultrasound
Quantitative computed topography
Histology
Mono accumulation
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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance
TABLE A-4 Examples of Cardiac, Muscle, and Pulmonary Markers
Tissue, Organ, Function
Intermediate Marker
Source
Cardiac
Heart rate
Heart rate variability
Impedance
Muscle
Amino acids (glutamine, histidine, 3-methyl-histidine)
Enzymes/molecules
Carbonic anhydrase
Isoenzymes of creatine kinase
Myoglobin
Myosin heavy chains
Phosphocreatine levels
Ubiquitin
Muscle
Immune
Circulatory polymorphonuclear leukocytes
Insulin-like growth factor-1
Interleukin-1, -6
Tumor necrosis factor
Blood
Salivaa
Urineb
Metabolism/catabolism/anabolism
Lactate
Glycogen
Blood ammonia
Blood
Urine
Protein turnover
Blood
Urine
Structure/metabolism
3-methyl-/histidine excretion
Glycogen
Trace metals
Muscle
Pulmonary
Expired air
Oxygen and carbon dioxide saturation
NOTE: Metabolic monitoring biomarkers can be categorized according to outcome function or intermediate measure that can be quantified to reflect the outcome function. This table summarizes outcome functions of various organs/systems/ physiological/psychological states and some intermediate biomarkers that might be used to predict or quantify these outcome functions and optimal performance. In general, it was felt that no single intermediate biomarker accurately predicts outcome function. Accurate measures of outcome function are often invasive and not applicable to field situations. More emphasis should be placed on developing noninvasive developing noninvasive measures that accurately predict peak performance or catastrophic failure of a given organ/system or physiological/psychological state.
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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance
Performance, Outcome
Measure
Cardiac output
Relative sympathetic and parasympathetic control
Dynamometers
Ergometers
Strain gauges
Ratings of perceived exertion
Decreased endurance
Decreased performance
Decreased strength
Fatigue
Delayed onset muscle soreness
Increased muscle atrophy
Pulse oximeter
Capnograph
a Salivary cytokine concentrations vary according to salivary gland source from which saliva is collected and presence and degree of periodontal disease.
b 24-hour urine for Interleukin-6 and soluble receptors for tumor necrosis factor normalized to creatine are currently used and are sensitive measures of cytokine production.
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Representative terms from entire chapter:
outcome function
