Kai Roecker

New physiological insights into exercise-induced diaphragmatic fatigue.

Data on the dynamic process and time-point of manifestation of exercise-induced diaphragmatic fatigue (DF) are lacking. Therefore, this study was aimed assessing dynamic changes of diaphragmatic strength during exercise and determining the time-point of DF manifestation. Fourteen trained subjects (maximal oxygen uptake (VO2(max)) 59.3+/-5.5 ml/min/kg) performed standardized exercise protocols (maximal workload: 85% VO2(max)) followed by recovery (6 min). Ergospirometric data and twitch transdiaphragmatic pressure (TwPdi) were consecutively assessed. DF was induced (TwPdi-rest: 2.34+/-0.26 versus TwPdi-end-recovery 2.01+/-0.21 kPa, p<0.01). TwPdi progressively increased during exercise (TwPdi-rest: 2.34+/-0.26 versus TwPdi-maximal-workload: 3.28+/-0.38 kPa, p<0.001). DF was detectable immediately after exercise-termination (TwPdi-maximal-workload: 3.28+/-0.38 versus TwPdi-early-recovery 2.55+/-0.34 kPa, p<0.001). TwPdi during exercise was highly correlated to workload, VO2(max) and dyspnea (r=0.96/r=0.92/r=0.97; all p<0.0001). In conclusion, diaphragmatic strength progressively increases with increasing workload, and DF manifests after - rather than during - exercise. In addition, TwPdi is highly correlated to key-measures of ergospirometry, approving the physiological thesis that muscle strength is progressively enhanced and escapes fatiguing failure during high-intensity exercise performance.

Independence of exercise-induced diaphragmatic fatigue from ventilatory demands

Exercise-induced diaphragmatic fatigue (DF) manifests after - rather than during - exercise. This suggests that DF reflects post-exercise diaphragm-shielding. This study tested the physiological hypothesis that diaphragmatic force-generation undergoes similar regulations during either whole-body-exercise or controlled hyperventilation, but differs during recovery. Ten trained subjects (VO2(max) 60.3+/-6.4 ml/kg/min) performed: I, cycling exercise (maximal workload: 85% VO2(max)); II, controlled hyperventilation (exercise breathing pattern) followed by recovery. Ergospirometric data and twitch transdiaphragmatic pressure (TwPdi) were consecutively assessed. DF occurred following exercise, while hyperventilation enhanced diaphragmatic force-generation (TwPdi-rest 2.28+/-0.58 vs. 2.52+/-0.54, TwPdi-end-recovery: 1.94+/-0.32 kPa vs. 2.81+/-0.49 kPa, both p<0.05). TwPdi was comparable between the two protocols until recovery (p>0.05, RM-ANOVA) whereby it underwent a progressive increase. In conclusion, TwPdi progressively increases and is subject to similar regulations during exercise versus controlled hyperventilation, but differs markedly during recovery. Here, DF occurred after exercise while TwPdi increased subsequent to hyperventilation. Therefore, ventilatory demands regulate diaphragmatic force-generation during exercise, whereas DF must be attributed to non-ventilatory controlled feedback mechanisms.

Respiratory Inductance Plethysmography—a Rationale for Validity during Exercise

INTRODUCTION The aim of this study was to provide a rationale for future validations of a priori calibrated respiratory inductance plethysmography (RIP) when used under exercise conditions. Therefore, the validity of a posteriori-adjusted gain factors and accuracy in resultant breath-by-breath RIP data recorded under resting and running conditions were examined. METHODS Healthy subjects, 98 men and 88 women (mean ± SD: height = 175.6 ± 8.9 cm, weight = 68.9 ± 11.1 kg, age = 27.1 ± 8.3 yr), underwent a standardized test protocol, including a period of standing still, an incremental running test on treadmill, and multiple periods of recovery. Least square regression was used to calculate gain factors, respectively, for complete individual data sets as well as several data subsets. In comparison with flowmeter data, the validity of RIP in breathing rate (fR) and inspiratory tidal volume (VTIN) were examined using coefficients of determination (R). Accuracy was estimated from equivalence statistics. RESULTS Calculated gains between different data subsets showed no equivalence. After gain adjustment for the complete individual data set, fR and VTIN between methods were highly correlated (R = 0.96 ± 0.04 and 0.91 ± 0.05, respectively) in all subjects. Under conditions of standing still, treadmill running, and recovery, 86%, 98%, and 94% (fR) and 78%, 97%, and 88% (VTIN), respectively, of all breaths were accurately measured within ± 20% limits of equivalence. CONCLUSION In case of the best possible gain adjustment, RIP confidentially estimates tidal volume accurately within ± 20% under exercise conditions. Our results can be used as a rationale for future validations of a priori calibration procedures.

Biometric approximation of diaphragmatic contractility during sustained hyperpnea.

Imposing load on respiratory muscles results in a loss of diaphragmatic contractility that develops early, is independent of task failure, and levels off following the initial decrease. This study assessed the progression of diaphragmatic contractility during sustained normocapnic hyperpnea and applied a biometric approximation (hypothesis: non-linear decay). Ten healthy subjects performed three consecutive hyperpnea bouts (I:6 min warm up/II:9 min/III:task failure 28.6 ± 11.5 min; mean ± SD) at maximal voluntary ventilation fractions (I:30-60%/II:70%/III:70%), followed by recovery periods (I:18 min/II:6 min/III:30 min). Twitch transdiaphragmatic pressure (TwPdi) was assessed throughout the protocol. Bouts II and III induced diaphragmatic fatigue (TwPdi baseline vs. Recovery -19 ± 17% and -30 ± 16%, both p < 0.05 RM-ANOVA) while bout I did not. During sustained hyperpnea (II/III), TwPdi followed an exponential decay (r(2) = 0.91). The reduction in diaphragmatic contractility closely follows a non-linear function with an early loss in diaphragmatic contractility during sustained hyperpnea, levels off thereafter, and is independent of task failure. Thus, reasons other than diaphragmatic fatigue are likely to be responsible for task failure during sustained hyperpnea.

Diaphragmatic fatigue is counterbalanced during exhaustive long-term exercise.

Based on externally paced (repetitive) short-term trials exercise-induced diaphragmatic fatigue has been shown to manifest after rather than during exercise. The current study aimed at investigating diaphragmatic contractility and diaphragmatic fatigue during self-paced long-term exhaustive exercise at maximally tolerated loading by the use of supramaximal twitch transdiaphragmatic pressure (TwPdi). Seven trained subjects (VO(2max) 63.3+/-13.9 ml kg(-1) min(-1)) performed self-paced long-term exhaustive exercise at maximally tolerated loading (45 min+endspurt, initial workload 85% VO(2max)) followed by recovery (9 min). TwPdi (every 45 s) and ergospirometric data (continuously) were assessed throughout the protocol. Diaphragmatic contractility tended to initially increase during the exercise protocol with a slight decline and final increase during endspurt. Diaphragmatic fatigue manifested only after exercise termination (TwPdi rest 2.6+/-0.8 kPa; TwPdi exercise start/mid/end 2.9+/-0.7 kPa vs. 2.6+/-0.8 kPa vs. 2.4+/-0.6 kPa; TwPdi endspurt/recovery 2.7+/-0.8 kPa vs. 1.9+/-0.6 kPa). In conclusion, diaphragmatic contractility tends to decrease but manifestation of diaphragmatic fatigue is counterbalanced during self-paced long-term exhaustive exercise at maximally tolerated loading.

Postural Control in Dual-Task Situations: Does Whole-Body Fatigue Matter?

Postural control is important to cope with demands of everyday life. It has been shown that both attentional demand (i.e., cognitive processing) and fatigue affect postural control in young adults. However, their combined effect is still unresolved. Therefore, we investigated the effects of fatigue on single- (ST) and dual-task (DT) postural control. Twenty young subjects (age: 23.7 ± 2.7) performed an all-out incremental treadmill protocol. After each completed stage, one-legged-stance performance on a force platform under ST (i.e., one-legged-stance only) and DT conditions (i.e., one-legged-stance while subtracting serial 3s) was registered. On a second test day, subjects conducted the same balance tasks for the control condition (i.e., non-fatigued). Results showed that heart rate, lactate, and ventilation increased following fatigue (all p < 0.001; d = 4.2–21). Postural sway and sway velocity increased during DT compared to ST (all p < 0.001; d = 1.9–2.0) and fatigued compared to non-fatigued condition (all p < 0.001; d = 3.3–4.2). In addition, postural control deteriorated with each completed stage during the treadmill protocol (all p < 0.01; d = 1.9–3.3). The addition of an attention-demanding interference task did not further impede one-legged-stance performance. Although both additional attentional demand and physical fatigue affected postural control in healthy young adults, there was no evidence for an overadditive effect (i.e., fatigue-related performance decrements in postural control were similar under ST and DT conditions). Thus, attentional resources were sufficient to cope with the DT situations in the fatigue condition of this experiment.

Respiratory muscle function during a six-week period of normocapnic hyperpnoea training.

Respiratory muscle endurance training (normocapnic hyperpnoea, RMET) improves maximal volitional ventilation (MVV) and respiratory muscle endurance while volitionally-assessed respiratory muscle strength remains unchanged (prior-to-post comparison). What remains unclear is how respiratory muscle function changes/adapts during a defined period of RMET in highly-trained subjects. This study assessed respiratory muscle function during a six-week period of RMET in 13 highly-trained, healthy subjects. Weekly-assessed twitch mouth pressure (prior/post 2.20 ± 0.41 kPa vs. 2.43 ± 0.61 kPa; p=0.14); twitch transdiaphragmatic pressure (prior/post 3.04 ± 0.58 kPa vs. 3.13 ± 0.48 kPa; p=0.58) and maximal inspiratory pressure (prior/post 12.6 ± 3.6 kPa vs. 13.9 ± 3.8 kPa; p=0.06) did not increase. MVV (prior/post 175 ± 18 l/min vs. 207 ± 30 l/min; p=0.001), sniff nasal pressure (prior/post 11.8 ± 2.8 kPa vs. 14.0 ± 2.9 kPa; p=0.003) and maximal expiratory pressure (prior/post 16.9 ± 5.8 kPa vs. 20.9 ± 4.9 kPa; p=0.006) each increased. In conclusion, non-volitionally assessed diaphragmatic strength does not increase during six weeks of RMET in highly-trained subjects, while expiratory muscle strength and MVV rose. Future studies should clarify if these findings apply when assessed during respiratory muscle strength rather than endurance training.

The relationship between movement speed and duration during soccer matches

The relationship between the time duration of movement (t(dur)) and related maximum possible power output has been studied and modeled under many conditions. Inspired by the so-called power profiles known for discontinuous endurance sports like cycling, and the critical power concept of Monod and Scherrer, the aim of this study was to evaluate the numerical characteristics of the function between maximum horizontal movement velocity (HSpeed) and t(dur) in soccer. To evaluate this relationship, GPS data from 38 healthy soccer players and 82 game participations (≥30 min active playtime) were used to select maximum HSpeed for 21 distinct t(dur) values (between 0.3 s and 2,700 s) based on moving medians with an incremental t(dur) window-size. As a result, the relationship between HSpeed and Log(t(dur)) appeared reproducibly as a sigmoidal decay function, and could be fitted to a five-parameter equation with upper and lower asymptotes, and an inflection point, power and decrease rate. Thus, the first three parameters described individual characteristics if evaluated using mixed-model analysis. This study shows for the first time the general numerical relationship between t(dur) and HSpeed in soccer games. In contrast to former descriptions that have evaluated speed against power, HSpeed against t(dur) always yields a sigmoidal shape with a new upper asymptote. The evaluated curve fit potentially describes the maximum moving speed of individual players during the game, and allows for concise interpretations of the functional state of team sports athletes.

A Wearable Respiratory Monitoring Device – the Between-Days Variability of Calibration

The between-days variability in ascertained gain factors for calibration of a wearable respiratory inductance plethysmograph (RIP) and validity thereof for the repeated use during exercise were examined. Consecutive 5-min periods of standing still, slow running at 8 km·h(-1), fast running at 14 km·h(-1) (male) or 12 km·h(-1) (female) and recovery were repeated by 10 healthy subjects on 5 days. Breath-by-breath data were recorded simultaneously by flow meter and RIP. Gain factors were determined individually for each trial (CALIND) via least square regression. Reliability and variability in gain factors were quantified respectively by intraclass correlation coefficients (ICC) and limits of agreement. Within a predefined error range of ±20% the amount of RIP-derived tidal volumes after CALIND was compared to corresponding amounts when gain factors of the first trial were applied on the following 4 trials (CALFIRST). ICC ranged within 0.96 and 0.98. The variability in gain factors (up to ± 24.06%) was reduced compensatively by their sum. Amounts of breaths within the predefined error range did not differ between CALIND and (CALFIRST) (P>0.32). The between-days variability of gain factors for a wearable RIP-device does not show impaired reliability in further derived tidal volumes.

Diaphragmatic fatigue during inspiratory muscle loading in normoxia and hypoxia

INTRODUCTION Diaphragmatic fatigue (DF) occurs during strenuous loading of respiratory muscles (e.g., heavy-intensity whole-body exercise, normocapnic hyperpnea, inspiratory resistive breathing). DF develops early on during normoxia, without further decline toward task failure; however, its progression during inspiratory muscle loading in during hypoxia remains unclear. Therefore, the present study used volume-corrected transdiaphragmatic pressures during supramaximal magnetic phrenic nerve stimulation (Pdi,twc) to investigate the effect of hypoxia on the progression of diaphragmatic fatigue during inspiratory muscle loading. METHODS Seventeen subjects completed two standardized rounds of inspiratory muscle loading (blinded, randomized) under the following conditions: (i) normoxia, and (ii) normobaric hypoxia (SpO2 80%), with Pdi,twc assessment every 45 s. RESULTS In fatiguers (i.e., Pdi,twc reduction >10%, n=10), biometric approximation during normoxia is best represented by Pdi,twc=4.06+0.83 exp(-0.19 × x), in contrast to Pdi,twc=4.38-(0.05 × x) during hypoxia. CONCLUSION Progression of diaphragmatic fatigue during inspiratory muscle loading assessed by Pdi,tw differs between normoxia and normobaric hypoxia: in the former, Pdi,tw follows an exponential decay, whereas during hypoxia, Pdi,tw follows a linear decline.