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Purpose: To prescribe training loads to improve performance, one must know how an athlete is responding to loading. The maximal rate of heart-rate increase (rHRI) during the transition from rest to exercise is linearly related to changes in endurance exercise performance and can be used to infer how athletes are responding to changes in training load. Relationships between rHRI and anaerobic exercise performance have not been evaluated. The objective of this study was to evaluate relationships between rHRI and anaerobic exercise performance. Methods: Eighteen recreational strength and power athletes (13 male and 5 female) were tested on a cycle ergometer for rHRI, 6-second peak power output, anaerobic capacity (30-s average power), and blood lactate concentration prior to (PRE), and 1 (POST1) and 3 (POST3) hours after fatiguing high-intensity interval cycling. Results: Compared with PRE, rHRI was slower at POST1 (effect size [ES] = −0.38, P = .045) but not POST3 (ES = −0.36, P = .11). PPO was not changed at POST1 (ES = −0.12, P = .19) but reduced at POST3 (ES = −0.52, P = .01). Anaerobic capacity was reduced at POST1 (ES = −1.24, P P P P = .11). rHRI was positively related to PPO (B = 0.19, P = .03) and anaerobic capacity (B = 0.14, P = .005) and inversely related to blood lactate concentration (B = −0.22, P = .04). Conclusions: rHRI is linearly related to acute changes in anaerobic exercise performance and may indicate how athletes are responding to training to guide the application of training loads.

The maximal rate of heart rate (HR) increase (rHRI), a marker of HR acceleration during transition from rest to submaximal exercise, correlates with exercise performance. In this cohort study, whether rHRI tracked performance better when evaluated over shorter time-periods which include a greater proportion of HR acceleration and less steady-state HR was evaluated. rHRI and five-km treadmill running time-trial performance (5TTT) were assessed in 15 runners following one week of light training (LT), two weeks of heavy training (HT) and 10-day taper (T). rHRI was the first derivative maximum of a sigmoidal curve fit to one, two, three and four minutes of R-R data during transition from rest to running at 8 km/h (rHRI8 km/h), 10.5 km/h, 13 km/h and transition from 8 to 13 km/h (rHRI8–13km/h). 5TTT time increased from LT to HT (effect size [ES] 1.0, p p 8 km/h assessed over two (B = −5.54, p = 0.04) three (B = −5.34, p = 0.04) and four (B = −5.37, p = 0.04) minutes, and rHRI8–13km/h over one (B = −11.62, p = 0.006) and three (B = −11.44, p = 0.03) minutes. 5TTT correlated most consistently with rHRI8 km/h. rHRI8 km/h assessed over two to four minutes may be suitable for evaluating athlete responses to training.

Maximal rate of heart rate (HR) increase (rHRI) as a measure of HR acceleration during the transition from rest to exercise, or during an increase in workload, tracks exercise performance. rHRI assessed at relative rather than absolute workloads may track performance better, and a field test would increase applicability. This study therefore aimed to evaluate the sensitivity of rHRI assessed at individualised relative workloads during treadmill and overground running for tracking exercise performance. Treadmill running performance (5 km time trial; 5TTT) and rHRI were assessed in 11 male runners following 1 week of light training (LT), 2 weeks of heavy training (HT) and a 10-day taper (T). rHRI was the first derivative maximum of a sigmoidal curve fit to HR data collected during 5 min of treadmill running at 65% peak HR (rHRI65%), and subsequent transition to 85% peak HR (rHRI85%). Participants ran at the same speeds overground, paced by a foot-mounted accelerometer. Time to complete 5TTT likely increased following HT (ES = 0.14 ± 0.03), and almost certainly decreased following T (ES = − 0.30 ± 0.07). Treadmill and field rHRI65% likely increased after HT in comparison to LT (ES ≤ 0.48 ± 0.32), and was unchanged at T. Treadmill and field rHRI85% was unchanged at HT in comparison to LT, and likely decreased at T in comparison to LT (ES ≤ − 0.55 ± 0.50). 5TTT was not correlated with treadmill or field rHRI65% or rHRI85%. rHRI65% was highly correlated between treadmill and field tests across LT, HT and T (r ≥ 0.63), but correlations for rHRI85% were trivial to moderate (r ≤ 0.42). rHRI assessed at relative exercise intensities does not track performance. rHRI assessed during the transition from rest to running overground and on a treadmill at the same running speed were highly correlated, suggesting that rHRI can be validly assessed under field conditions at 65% of peak HR.

Background: There are no known objective biomarkers to assist with the diagnosis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). A small number of studies have shown that ME/CFS patients exhibit an earlier onset of ventilatory threshold (VT) on the second of two cardiopulmonary exercise tests (CPET) performed on consecutive days. However, cut-off values which could be used to differentiate between ME/CFS patients have not been established. Methods: 16 ME/CFS patients and 10 healthy controls underwent CPET on a cycle-ergometer on 2-consecutive days. Heart rate (HR), ventilation, ratings of perceived exertion (RPE) and work rate (WR) were assessed on both days. Results: WR at VT decreased from day 1 to day 2 and by a greater magnitude in ME/CFS patients (p < 0.01 group × time interaction). No interaction effects were found for any other parameters. ROC curve analysis of the percentage change in WR at VT revealed decreases of - 6.3% to - 9.8% provided optimal sensitivity and specificity respectively for distinguishing between patients with ME/CFS and controls. Conclusion: The decrease in WR at VT of 6.3-9.8% on the 2nd day of consecutive-day CPET may represent an objective biomarker that can be used to assist with the diagnosis of ME/CFS. Refereed/Peer-reviewed

BACKGROUND: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex condition with no reliable diagnostic biomarkers. Studies have shown evidence of autonomic dysfunction in patients with ME/CFS, but results have been equivocal. Heart rate (HR) parameters can reflect changes in autonomic function in healthy individuals; however, this has not been thoroughly evaluated in ME/CFS. METHODS: A systematic database search for case-control literature was performed. Meta-analysis was performed to determine differences in HR parameters between ME/CFS patients and controls. RESULTS: Sixty-four articles were included in the systematic review. HR parameters assessed in ME/CFS patients and controls were grouped into ten categories: resting HR (RHR), maximal HR (HRmax), HR during submaximal exercise, HR response to head-up tilt testing (HRtilt), resting HR variability (HRVrest), HR variability during head-up tilt testing (HRVtilt), orthostatic HR response (HROR), HR during mental task(s) (HRmentaltask), daily average HR (HRdailyaverage), and HR recovery (HRR) Meta-analysis revealed RHR (MD ± 95% CI = 4.14 ± 1.38, P

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Purpose: Correlations between fatigue-induced changes in exercise performance and maximal rate of heart rate (HR) increase (rHRI) may be affected by exercise intensity during assessment. This study evaluated the sensitivity of rHRI for tracking performance when assessed at varying exercise intensities. Method: Performance (time to complete a 5-km treadmill time-trial [5TTT]) and rHRI were assessed in 15 male runners following 1 week of light training, 2 weeks of heavy training (HT), and a 10-day taper (T). Maximal rate of HR increase (measured in bpm·s−¹) was the first derivative maximum of a sigmoidal curve fit to HR data recorded during 5 min of running at 8 km·h⁻¹ (rHRI⁸–¹³ᵏᵐ·ʰ−¹), and during subsequent transition to 13 km·h−¹ (rHRI⁸–¹³ᵏᵐ·ʰ−¹) for a further 5 min. Results: Time to complete a 5-km treadmill time-trial was likely slower following HT (effect size ± 90% confidence interval = 0.16 ± 0.06), and almost certainly faster following T (–0.34 ± 0.08). Maximal rate of HR increase during 5 min of running at 8 km·h−¹ and rHRI⁸–¹³ᵏᵐ·ʰ−¹ were unchanged following HT and likely increased following T (0.77 ± 0.45 and 0.66 ± 0.62, respectively). A moderate within-individual correlation was found between 5TTT and rHRI⁸–¹³ᵏᵐ·ʰ−¹ (r value ± 90% confidence interval = –.35 ± .32). However, in a subgroup of athletes (n = 7) who were almost certainly slower to complete the 5TTT (4.22 ± 0.88), larger correlations were found between the 5TTT and rHRI⁸–¹³ᵏᵐ·ʰ−¹ (r = –.84 ± .22) and rHRI⁸–¹³ᵏᵐ·ʰ−¹ (r = –.52 ± .41). Steady-state HR during rHRI assessment in this group was very likely greater than in the faster subgroup (≥ 1.34 ± 0.86). Conclusions: The 5TTT performance was tracked by both rHRI⁸–¹³ᵏᵐ·ʰ−¹ and rHRI⁸–¹³ᵏᵐ·ʰ−¹. Correlations between rHRI and performance were stronger in a subgroup of athletes who exhibited a slower 5TTT. Individualized workloads during rHRI assessment may be required to account for varying levels of physical conditioning. Refereed/Peer-reviewed

Purpose: Being able to identify how an athlete is responding to training would be useful to optimise adaptation and performance. The maximal rate of heart rate increase (rHRI), a marker of heart rate acceleration has been shown to correlate with performance changes in response to changes in training load in male athletes; however, it has not been established if it also correlates with performance changes in female athletes. Methods: rHRI and cycling performance were assessed in six female cyclists following 7 days of light training (LT), 14 days of heavy training (HT) and a 10 day taper period. rHRI was the first derivative maximum of a sigmoidal curve fit to R-R data recorded during 5 min of cycling at 100 W. Cycling performance was assessed as work done (kJ) during time-trials of 5 (5TT) and 60 (60TT) min duration. Results: 5TT was possibly decreased at HT (ES ± 90% confidence interval = − 0.16 ± 0.25; p = 0.60), while, 5TT and 60TT very likely to almost certainly increased from HT to taper (ES = 0.71 ± 0.24; p = 0.007 and ES = 0.42 ± 0.19; p = 0.02, respectively). Large within-subject correlations were found between rHRI, and 5TT (r = 0.65 ± 0.37; p = 0.02) and 60TT (r = 0.70 ± 0.31; p = 0.008). Conclusions: rHRI during the transition from rest to light exercise correlates with training induced-changes in exercise performance in females, suggesting that rHRI may be a useful monitoring tool for female athletes. Refereed/Peer-reviewed

BackgroundFoods rich in nutrients, such as nitrate, nitrite, L-arginine and polyphenols, can promote the synthesis of nitric oxide (NO), which may induce ergogenic effects on endurance exercise performance. Thus, consuming foods rich in these components, such as almonds, dried grapes and dried cranberries (AGC), may improve athletic performance. Additionally, the antioxidant properties of these foods may reduce oxidative damage induced by intense exercise, thus improving recovery and reducing fatigue from strenuous physical training. Improvements in NO synthesis may also promote cerebral blood flow, which may improve cognitive function.Methods and analysisNinety-six trained male cyclists or triathletes will be randomised to consume ~2550 kJ of either a mixture of AGC or a comparator snack food (oat bar) for 4 weeks during an overreaching endurance training protocol comprised of a 2-week heavy training phase, followed by a 2-week taper. The primary outcome is endurance exercise performance (5 min time-trial performance) and secondary outcomes include markers of NO synthesis (plasma and urinary nitrites and nitrates), muscle damage (serum creatine kinase and lactate dehydrogenase), oxidative stress (F2-isoprostanes), endurance exercise function (exercise efficiency, submaximal oxygen consumption and substrate utilisation), markers of internal training load (subjective well-being, rating of perceived exertion, maximal rate of heart rate increase and peak heart rate) and psychomotor speed (choice reaction time).ConclusionThis study will evaluate whether consuming AGC improves endurance exercise performance, recovery and psychomotor speed across an endurance training programme, and evaluate the mechanisms responsible for any improvement.Trial registration numberACTRN12618000360213.

Objectives: Heart rate kinetics are faster in well-trained athletes at exercise onset, indicating sensitivity to training status, but whether they track performance changes due to changes in training load is unknown. Design: Randomised, counterbalanced, cross-over. Methods: 17 cyclists completed two weeks of light and two weeks of heavy training. The day after each training period heart rate was recorded during 5. min cycling at 100. W to determine the maximal rate of heart rate increase. Participants then performed a 5. min cycle time-trial after which heart rate recovery was determined. Results: Work during 5. min cycle time-trial decreased 3.5% (P