Title |
Heart rate variability in elite triathletes, is variation in variability the key to effective training? A case comparison
|
---|---|
Published in |
European Journal of Applied Physiology, February 2012
|
DOI | 10.1007/s00421-012-2354-4 |
Pubmed ID | |
Authors |
Daniel J. Plews, Paul B. Laursen, Andrew E. Kilding, Martin Buchheit |
Abstract |
Measures of an athlete's heart rate variability (HRV) have shown potential to be of use in the prescription of training. However, little data exists on elite athletes who are regularly exposed to high training loads. This case study monitored daily HRV in two elite triathletes (one male: 22 year, VO2max 72.5 ml kg min(-1); one female: 20 year, VO2max 68.2 ml kg min(-1)) training 23 ± 2 h per week, over a 77-day period. During this period, one athlete performed poorly in a key triathlon event, was diagnosed as non-functionally over-reached (NFOR) and subsequently reactivated the dormant virus herpes zoster (shingles). The 7-day rolling average of the log-transformed square root of the mean sum of the squared differences between R-R intervals (Ln rMSSD), declined towards the day of triathlon event (slope = -0.17 ms/week; r2 = -0.88) in the NFOR athlete, remaining stable in the control (slope = 0.01 ms/week; r2 = 0.12). Furthermore, in the NFOR athlete, coefficient of variation of HRV (CV of Ln rMSSD 7-day rolling average) revealed large linear reductions towards NFOR (i.e., linear regression of HRV variables versus day number towards NFOR: -0.65%/week and r2 = -0.48), while these variables remained stable for the control athlete (slope = 0.04%/week). These data suggest that trends in both absolute HRV values and day-to-day variations may be useful measurements indicative of the progression towards mal-adaptation or non-functional over-reaching. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 6 | 13% |
Spain | 5 | 11% |
Netherlands | 4 | 9% |
Australia | 3 | 7% |
United States | 2 | 4% |
France | 2 | 4% |
Ireland | 2 | 4% |
Switzerland | 1 | 2% |
New Zealand | 1 | 2% |
Other | 2 | 4% |
Unknown | 17 | 38% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 31 | 69% |
Scientists | 10 | 22% |
Science communicators (journalists, bloggers, editors) | 3 | 7% |
Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | <1% |
Brazil | 3 | <1% |
United Kingdom | 2 | <1% |
Spain | 2 | <1% |
Germany | 1 | <1% |
Canada | 1 | <1% |
Mexico | 1 | <1% |
Netherlands | 1 | <1% |
Singapore | 1 | <1% |
Other | 1 | <1% |
Unknown | 444 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 81 | 18% |
Student > Ph. D. Student | 64 | 14% |
Researcher | 45 | 10% |
Student > Bachelor | 42 | 9% |
Student > Doctoral Student | 29 | 6% |
Other | 112 | 24% |
Unknown | 87 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Sports and Recreations | 228 | 50% |
Medicine and Dentistry | 41 | 9% |
Nursing and Health Professions | 18 | 4% |
Agricultural and Biological Sciences | 17 | 4% |
Engineering | 13 | 3% |
Other | 45 | 10% |
Unknown | 98 | 21% |