Accuracy of the Cosmed K5 portable calorimeter

Purpose The purpose of this study was to assess the accuracy of the Cosmed K5 portable metabolic system dynamic mixing chamber (MC) and breath-by-breath (BxB) modes against the criterion Douglas bag (DB) method. Methods Fifteen participants (mean age±SD, 30.6±7.4 yrs) had their metabolic variables measured at rest and during cycling at 50, 100, 150, 200, and 250W. During each stage, participants were connected to the first respiratory gas collection method (randomized) for the first four minutes to reach steady state, followed by 3-min (or 5-min for DB) collection periods for the resting condition, and 2-min collection periods for all cycling intensities. Collection periods for the second and third methods were preceded by a washout of 1–3 min. Repeated measures ANOVAs were used to compare metabolic variables measured by each method, for seated rest and each cycling work rate. Results For ventilation (VE) and oxygen uptake (VO2), the K5 MC and BxB modes were within 2.1 l/min (VE) and 0.08 l/min (VO2) of the DB (p≥0.05). Compared to DB values, carbon dioxide production (VCO2) was significantly underestimated by the K5 BxB mode at work rates ≥150W by 0.12–0.31 l/min (p\u3c0.05). K5 MC and BxB respiratory exchange ratio values were significantly lower than DB at cycling work rates ≥100W by 0.03–0.08 (p\u3c0.05). Conclusion Compared to the DB method, the K5 MC and BxB modes are acceptable for measuring VE and VO2 across a wide range of cycling intensities. Both K5 modes provided comparable values to each other

Accuracy of the Cosmed K5 portable calorimeter.

PURPOSE:The purpose of this study was to assess the accuracy of the Cosmed K5 portable metabolic system dynamic mixing chamber (MC) and breath-by-breath (BxB) modes against the criterion Douglas bag (DB) method. METHODS:Fifteen participants (mean age±SD, 30.6±7.4 yrs) had their metabolic variables measured at rest and during cycling at 50, 100, 150, 200, and 250W. During each stage, participants were connected to the first respiratory gas collection method (randomized) for the first four minutes to reach steady state, followed by 3-min (or 5-min for DB) collection periods for the resting condition, and 2-min collection periods for all cycling intensities. Collection periods for the second and third methods were preceded by a washout of 1-3 min. Repeated measures ANOVAs were used to compare metabolic variables measured by each method, for seated rest and each cycling work rate. RESULTS:For ventilation (VE) and oxygen uptake (VO2), the K5 MC and BxB modes were within 2.1 l/min (VE) and 0.08 l/min (VO2) of the DB (p≥0.05). Compared to DB values, carbon dioxide production (VCO2) was significantly underestimated by the K5 BxB mode at work rates ≥150W by 0.12-0.31 l/min (p<0.05). K5 MC and BxB respiratory exchange ratio values were significantly lower than DB at cycling work rates ≥100W by 0.03-0.08 (p<0.05). CONCLUSION:Compared to the DB method, the K5 MC and BxB modes are acceptable for measuring VE and VO2 across a wide range of cycling intensities. Both K5 modes provided comparable values to each other

Discrimination of wear and non-wear in infants using data from hip- and ankle-worn devices.

IntroductionA key component to analyzing wearable sensor data is identifying periods of non-wear. Traditionally, strings of consecutive zero counts (e.g. >60-minutes) are identified indicating periods of non-movement. The non-movement window length is then evaluated as wear or non-wear. Given that non-movement is not equivalent to non-wear, additional criteria should be evaluated to objectively identify periods of non-wear. Identifying non-wear is especially challenging in infants due to their sporadic movement, sleep frequency, and proportion of caregiver-generated movement.PurposeTo use hip- and ankle-worn ActiGraph wGT3X-BT (wGT3X-BT) data to identify non-wear in infants.MethodsFifteen infant participants [mean±SD; age, 8.7±1.7 weeks (range 5.4-11.3 weeks); 5.1±0.8 kg; 56.2±2.1 cm; n = 8 females] wore a wGT3X-BT on the hip and ankle. Criterion data were collected during two, 2-hour directly observed periods in the laboratory. Using raw 30 Hz acceleration data, a vector magnitude and the inclination angle of each individual axis were calculated before being averaged into 1-minute windows. Three decision tree models were developed using data from 1) hip only, 2) ankle only, and 3) hip and ankle combined.ResultsThe hip model classified 86.6% of all minutes (wear and non-wear) correctly (F1 = 75.5%) compared to the ankle model which classified 90.6% of all minutes correctly (F1 = 83.0%). The combined site model performed similarly to the ankle model and correctly classified 90.0% of all minutes (F1 = 80.8%).ConclusionThe similar performance between the ankle only model and the combined site model likely indicates that the features from the ankle device are more important for identifying non-wear in infants. Overall, this approach provides an advancement in the identification of device wear status using wearable sensor data in infants

Deep phenotyping of post-infectious myalgic encephalomyelitis/chronic fatigue syndrome

Abstract Post-infectious myalgic encephalomyelitis/chronic fatigue syndrome (PI-ME/CFS) is a disabling disorder, yet the clinical phenotype is poorly defined, the pathophysiology is unknown, and no disease-modifying treatments are available. We used rigorous criteria to recruit PI-ME/CFS participants with matched controls to conduct deep phenotyping. Among the many physical and cognitive complaints, one defining feature of PI-ME/CFS was an alteration of effort preference, rather than physical or central fatigue, due to dysfunction of integrative brain regions potentially associated with central catechol pathway dysregulation, with consequences on autonomic functioning and physical conditioning. Immune profiling suggested chronic antigenic stimulation with increase in naïve and decrease in switched memory B-cells. Alterations in gene expression profiles of peripheral blood mononuclear cells and metabolic pathways were consistent with cellular phenotypic studies and demonstrated differences according to sex. Together these clinical abnormalities and biomarker differences provide unique insight into the underlying pathophysiology of PI-ME/CFS, which may guide future intervention