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Comparison Of Different Methods Used To Prescribe Exercise Intensities From Ramp-incremental Exercise

2022· article· en· W4294795936 on OpenAlexaff
Nikan Behboodpour, Daniel A. Keir, Brayden D. Halvorson, Glen R. Belfry

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsWestern University
Fundersnot available
KeywordsCycle ergometerBlood lactateTime trialVO2 maxExercise prescriptionLactate thresholdMathematicsIncremental exerciseLimits of agreementVentilatory thresholdAnimal scienceMedicineCardiologyPhysical therapyNuclear medicineInternal medicineHeart rateBlood pressure

Abstract

fetched live from OpenAlex

The oxygen uptake (V̇O2) vs power output (PO) relationship from ramp exercise (RAMP) is used to prescribe aerobic exercise. During a RAMP, as PO increases, there is a delay in breath-by-breath V̇O2 that contributes to a misalignment of V̇O2 from PO. This lag is known as the mean response time (MRT). If the MRT is not considered in exercise prescription, RAMP-identified POs will elicit V̇O2 values that are higher than intended. Three methods are used to quantify MRT including linear modeling (MRTLin), exponential modeling (τ’), and the steady-state method (MRTSS). PURPOSE: To compare the time delays between MRTLin, τ’, and the MRTSS at 75%, 85%, and 15% of the difference between estimated lactate threshold (θL)and V̇O2peak (Δ15%). METHODS: 10 males (24.6 ± 7.7 yr, V̇O2max 3.69 ± 0.72 L.min-1, Peak PO V̇O2max 352 ± 57 W, θL PO 180 ± 58 W, θL V̇O2 2.22 ± 0.69 L.min-1) performed a 30W/min RAMP on a cycle ergometer (CYCLE). τ’ and the MRTLin were calculated from the RAMP and converted to a coincident PO. Three 30 min CYCLE trials were performed on separate days, at τ’ left-shifted 75% and 85% of θL, and Δ15%. The RAMP PO corresponding to the steady-state V̇O2 from the 75% θL trial PO was determined. The difference between that PO and the 75% θL trial PO was the MRTSS. Pre-and post-blood lactates were recorded from all trials. RESULTS: τ’ and MRTLin were different (22 ± 13 W, 17 ± 9 W, P=0.04). MRTSS was similar to τ’ and MRTLin (22 ± 11 W, (P=1.000, P= 0.07). The τ’ and MRTLin-corrected POs corresponding to the V̇O2 over the last 5 min of the 75% of θL trial (114 ± 53 P=0.573 and 121 ± 49 P=0.372, respectively) were similar to the actual PO performed (116 ± 52). τ’ and MRTLin-corrected POs corresponding to the V̇O2 last 5 min at 85% of θL (142 ± 70, 149 ± 66, P=0.087 respectively) were similar to the actual PO performed(140 ± 65). The τ’-corrected PO corresponding to the V̇O2 last 5 min at Δ15% (P=0.088) was similar to the actual PO performed. The MRTLin-corrected PO corresponding to the V̇O2 last 5 min at Δ15% (P= 0.025) was different from the actual PO. CONCLUSION: Left-shifting the RAMP PO by τ’ or MRTLin results in a similar corresponding V̇O2 at 75% or 85% of θL. At Δ15% only left-shifting by τ’ results in the same PO as is performed. Using τ’ or MRTLin can be used with confidence when prescribing exercise below θL. At intensities slightly above θL only left-shifting by τ’ is reliable.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.044
GPT teacher head0.362
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2022
Admission routes1
Has abstractyes

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