Noninvasive measurement of cardiac output during exercise by inert gas rebreathing technique

Reduced exercise tolerance and dyspnea during exercise are hallmarks of heart failure syndrome. Exercise capacity and various parameters of cardiopulmonary response to exercise are of important prognostic value. All the available parameters only indirectly reflect left ventricular dysfunction and hemodynamic adaptation to an increased demand. Noninvasive assessment of cardiac output, especially during an incremental exercise stress test, would allow the direct measure of cardiac reserve and may become the gold standard for prognostic evaluation in the future.

Corticospinal output and loss of force during motor fatigue

The objective of this study was to analyze central motor output changes in relation to contraction force during motor fatigue. The triple stimulation technique (TST, Magistris et al. in Brain 121(Pt 3):437-450, 1998) was used to quantify a central conduction index (CCI = amplitude ratio of central conduction response and peripheral nerve response, obtained simultaneously by the TST). The CCI removes effects of peripheral fatigue from the quantification. It allows a quantification of the percentage of the entire target muscle motor unit pool driven to discharge by a transcranial magnetic stimulus. Subjects (n = 23) performed repetitive maximal voluntary contractions (MVC) of abductor digiti minimi (duration 1 s, frequency 0.5 Hz) during 2 min. TST recordings were obtained every 15 s, using stimulation intensities sufficient to stimulate all cortical motor neurons (MNs) leading to the target muscle, and during voluntary contractions of 20% of the MVC to facilitate the responses. TST was also repetitively recorded during recovery. This basic exercise protocol was modified in a number of experiments to further characterize influences on CCI of motor fatigue (4 min exercise at 50% MVC; delayed fatigue recovery during local hemostasis, "stimulated exercise" by 20 Hz trains of 1 s duration at 0.5 Hz during 2 min). In addition, the cortical silent period was measured during the basic exercise protocol. Force fatigued to approximately 40% of MVC in all experiments and in all subjects. In all subjects, CCI decreased during exercise, but this decrease varied markedly between subjects. On average, CCI reductions preceded force reductions during exercise, and CCI recovery preceded force recovery. Exercising at 50% for 4 min reduced muscle force more markedly than CCI. Hemostasis induced by a cuff delayed muscle force recovery, but not CCI recovery. Stimulated exercise reduced force markedly, but CCI decreased only marginally. Summarized, force reduction and reduction of the CCI related poorly quantitatively and in time, and voluntary drive was particularly critical to reduce the CCI. The fatigue induced reduction of CCI may result from a central inhibitory phenomenon. Voluntary muscle activation is critical for the CCI reduction, suggesting a primarily supraspinal mechanism.

Comparing the validity and output of the GT1M and GT3X accelerometer in 5- to 9-year-old children

The purpose of this study was to compare the validity and output of the biaxial ActiGraph GT1M and the triaxial GT3X (ActiGraph, LLC, Pensacola, FL, USA)accelerometer in 5- to 9-year-old children. Thirty-two children wore the two monitors while their energy expenditure was measured with indirect calorimetry. They performed four locomotor and four play activities in an exercise laboratory and were further measured during 12 minutes of a sports lesson. Validity evidence in relation to indirect calorimetry was examined with linear regression equations applied to the laboratory data. During the sports lessons predicted energy expenditure according to the regression equations was compared to measured energy expenditure with the Wilcoxon-signed rank test and the Spearman correlation. To compare the output, agreement between counts of the two monitors during the laboratory activities was assessed with Bland-Altman plots. The evidence of validity was similar for both monitors. Agreement between the output of the two monitors was good for vertical counts (mean bias = −14 ± 22 counts) but not for horizontal counts (−17 ± 32 counts). The current results indicate that the two accelerometer models are able to estimate energy expenditure of a range of physical activities equally well in young children. However, they show output differences for movement in the horizontal direction.

Influence of directionality and maximal power output on speech understanding with bone anchored hearing implants in single sided deafness

Bone-anchored hearing implants (BAHI) are routinely used to alleviate the effects of the acoustic head shadow in single-sided sensorineural deafness (SSD). In this study, the influence of the directional microphone setting and the maximum power output of the BAHI sound processor on speech understanding in noise in a laboratory setting were investigated. Eight adult BAHI users with SSD participated in this pilot study. Speech understanding in noise was measured using a new Slovak speech-in-noise test in two different spatial settings, either with noise coming from the front and noise from the side of the BAHI (S90N0) or vice versa (S0N90). In both spatial settings, speech understanding was measured without a BAHI, with a Baha BP100 in omnidirectional mode, with a BP100 in directional mode, with a BP110 power in omnidirectional and with a BP110 power in directional mode. In spatial setting S90N0, speech understanding in noise with either sound processor and in either directional mode was improved by 2.2-2.8 dB (p = 0.004-0.016). In spatial setting S0N90, speech understanding in noise was reduced by either BAHI, but was significantly better by 1.0-1.8 dB, if the directional microphone system was activated (p = 0.046), when compared to the omnidirectional setting. With the limited number of subjects in this study, no statistically significant differences were found between the two sound processors.

Assessing collective defensive performances in football: A Qualitative Comparative Analysis of central back pairs

Ahead of the World Cup in Brazil the crucial question for the Swiss national coach is the nomination of the starting eleven central back pair. A fuzzy set Qualitative Comparative Analysis assesses the defensive performances of different Swiss central back pairs during the World Cup campaign (2011 – 2014). This analysis advises Ottmar Hitzfeld to nominate Steve von Bergen and Johan Djourou as the starting eleven central back pair. The alternative with a substantially weaker empirical validity would be Johan Djourou together with Phillippe Senderos. Furthermore, this paper aims to be a step forward in mainstream football analytics. It analyses the undervalued and understudied defense (Anderson and Sally 2012, Statsbomb 2013) by explaining collective defensive performances instead of assessments of individual player or team performances. However, a qualitatively (better defensive metrics) and quantitatively (more games) improved and extended data set would allow for a more sophisticated analysis of collective defensive performances.

Reliability of lithium dilution cardiac output in anaesthetized sheep

BACKGROUND: Cardiac output (CO) measurement with lithium dilution (COLD) has not been fully validated in sheep using precise ultrasonic flow probe technology (COUFP). Sheep generate important cardiovascular research models and the use of COLD has become more popular in experimental settings. METHODS: Ultrasonic transit-time perivascular flow probes were surgically implanted on the pulmonary artery of 13 sheep. Paired COLD readings were taken at six time points, before and after implantation of a left ventricular assist device (LVAD) and compared with COUFP recorded just after lithium injection. RESULTS: The mean COLD was 5.7 litre min(-1) (range 3.8-9.6 litre min(-1)) and mean COUFP 5.9 litre min(-1) (range 4.0-9.2 litre min(-1)). The bias (standard deviation) was 0.3 (1.0) litre min(-1) [5.1 (16.9)%] and limits of agreement (LOA) were -1.7 to 2.3 litre min(-1) (-28.8 to 39.0%) with a percentage error (PE) of 34.4%. Data to assess trending [rate (95% confidence intervals)] included a 78 (62-93)% concordance rate in the four-quadrant plot (n=27). In the half moon polar plot (n=19), the mean polar angle was +5°, the radial LOA were -49 to +35° and 68 (47-89)% of data points fell within 22.5° of the mean polar angle. Both tests indicated moderate to poor trending ability. CONCLUSION: COLD is not precise when evaluated against COUFP in sheep based on the statistical criteria set, but the results are comparable with previously published animal studies. KEYWORDS:

An Early-Warning System for Hypo-/Hyperglycemic Events Based on Fusion of Adaptive Prediction Models

Introduction: Early warning of future hypoglycemic and hyperglycemic events can improve the safety of type 1 diabetes mellitus (T1DM) patients. The aim of this study is to design and evaluate a hypoglycemia / hyperglycemia early warning system (EWS) for T1DM patients under sensor-augmented pump (SAP) therapy. Methods: The EWS is based on the combination of data-driven online adaptive prediction models and a warning algorithm. Three modeling approaches have been investigated: (i) autoregressive (ARX) models, (ii) auto-regressive with an output correction module (cARX) models, and (iii) recurrent neural network (RNN) models. The warning algorithm performs postprocessing of the models′ outputs and issues alerts if upcoming hypoglycemic/hyperglycemic events are detected. Fusion of the cARX and RNN models, due to their complementary prediction performances, resulted in the hybrid autoregressive with an output correction module/recurrent neural network (cARN)-based EWS. Results: The EWS was evaluated on 23 T1DM patients under SAP therapy. The ARX-based system achieved hypoglycemic (hyperglycemic) event prediction with median values of accuracy of 100.0% (100.0%), detection time of 10.0 (8.0) min, and daily false alarms of 0.7 (0.5). The respective values for the cARX-based system were 100.0% (100.0%), 17.5 (14.8) min, and 1.5 (1.3) and, for the RNN-based system, were 100.0% (92.0%), 8.4 (7.0) min, and 0.1 (0.2). The hybrid cARN-based EWS presented outperforming results with 100.0% (100.0%) prediction accuracy, detection 16.7 (14.7) min in advance, and 0.8 (0.8) daily false alarms. Conclusion: Combined use of cARX and RNN models for the development of an EWS outperformed the single use of each model, achieving accurate and prompt event prediction with few false alarms, thus providing increased safety and comfort.