As the last days of 2023 approach, I would like to briefly point out several key findings published over the past 12 months. This is not meant to be totally definitive and I may have missed some good studies. However, from my viewpoint, the following subjects stand out:
- The value of combining surrogate thresholds.
- The need for better agreement of the HRVT1 with VT1/LT1.
- The use of DFA a1 for assessment and monitoring of fatigue.
- The day to day reliability of DFA a1 thresholds and behavior.
- Effects of ramp slope on a1 threshold behavior
Ramp Slope - does it matter?
One of the key observations concerning a1 threshold determination was that ramp slope (between 15 and 45w/min) does not affect HRVT1/2. Before this study was done, I would have bet that ramp slope would affect threshold determination and certainly 45w/min should be a dealbreaker. After all, 45w/min is a massive 90 watt rise over the 2 minute DFA a1 measurement window! Instead, we found that the a1:HR profile was nearly identical for the different ramp slope tests:This is the first (and only) published evaluation of (any) ramp slope on HRV thresholds. Many thanks to my co authors including Juan Murias and Pablo Fleitas- Paniagua for making this possible.
Day to day reliability of a1 testing
In other words, does a1 behave similarly on a day to day repetitive basis, either during an exercise ramp or just (short term) constant load testing?
This article done by Bas VanHooren and Thomas Gronwald looked at a1 during both easy and post ramp exercise:
- It was found that both HR and a1 were very similar on repeated testing (2 different days), both on the warm-up and after the exhaustive ramp.
Although not specifically designed as a day to day reliability study, the ramp slope paper essentially indicated the same result - that a1 thresholds will be similar for a given individual on repeat testing (in this case the slope was different on the 3 test days):
The need for better agreement between the HRVT1 and VT1/LT1/GET
This leads us to the next issue, why do some studies show tight agreement of the HRVT1 to the LT1/VT1/GET and some don't? As part of the triple ramp study, there was a large discrepancy between the VT1 (or GET) with the HRVT1 (yellow). However, the HRVT2 relationship/agreement with the RCP (or maximal metabolic steady state) continued to be excellent (red):
On the other hand, this study by Bas VanHooren showed good VT1:HRVT1 agreement:
- One of my priority projects for the next year is to work on this issue and explore the nuances of the HRVT1 to VT1/GET relationship, hopefully improving the HRV threshold agreement. Which leads us to the next section...
Combining surrogate threshold markers for better agreement to gold standards:
I was involved with 2 papers that approached this hypothesis, which I explained in depth previously. In short - It was proposed that combining 2 disparate surrogate markers (HRVT plus something else) would produce better agreement with both the VT1/GET and the RCP. The "something else" was either muscle O2 desaturation breakpoints for RCP localization and/or EDRT (ECG derived respiratory rate) for both VT1/GET and RCP. Both hypotheses were shown to be valid and I was also happy to see that the Kubios team has picked up on that idea as seen in this abstract (from ECSS 2023):
My belief is that multiple surrogates will be better than single measures for threshold determination, and hope to see more about this over the next year.
The use of DFA a1 for assessment and monitoring of fatigue:
Last but not least of the DFA a1 findings for 2023, was the paper with Bas VanHooren using two ramps back to back separated by a very short active rest, looking at threshold behavior.
Method summary - a ramp to exhaustion, active rest then another ramp - Whew!
As anticipated, a1 was markedly suppressed on the second ramp despite similar gas kinetics:
The practical implications of this study are twofold:
- Don't do a threshold ramp when fatigued/ill or post heavy/severe exercise. In fact, given the previously noted finding after an ultramarathon, even low intensity exercise, if performed long enough, may suppress the a1.
- Second - a1 shows great promise as an indicator of "autonomic" fatigue/durability. One may see variable degrees of a1 "drift" depending on individual fitness characteristics, length and intensity of exercise. Therefore, monitoring of either a1 during longer training sessions is of potential use as far as zone distribution goes. For instance, does the lower a1 post HIT "count" for a higher training zone than what the wattage shows?
Honorable mentions (in no order):
Continued improvement of the alphaHRV app for Garmin devices. Despite major hardware and software limitations, the developers have achieved good a1 agreement to Kubios standards.
Web app enhancements to both AIEndurance and Runalyze.
Finally, my thanks to all co-authors over the past years for making many of these studies possible.
Happy New Year!