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Examples of Physiological and Cognitive Markers of Performance



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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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