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Is A 90 Min Recovery Period Following Fatiguing Handgrip Exercise Enough To Ensure Maximal Performance During A Critical Impulse Test (CIT) Or Incremental Exercise Test (IET)?

2016· article· en· W4389025544 on OpenAlexaff
Alyssa M. Fenuta, Michael E. Tschakovsky

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsQueen's University
Fundersnot available
KeywordsIsometric exerciseAnaerobic exerciseReproducibilitySupine positionMedicineHeart rateVO2 maxPhysical therapyForearmMathematicsCardiologyPhysical medicine and rehabilitationInternal medicineBlood pressureSurgeryStatistics

Abstract

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Introduction The critical impulse (CIT) and incremental exercise (IET) tests are used to quantify important performance capacity indices. The CIT requires maximal effort for 10 min enabling determination of the highest work rate sustainable by aerobic metabolism (CI) and anaerobic work capacity (W’). The IET involves 25 N increases every 3.5 min enabling determination of peak work rate (VO 2 ). Since these protocols are fatiguing, methodological considerations must be made when both parameters are assessed in a single session to ensure the second test performance is not compromised. Purpose To establish the reproducibility of the CIT and IET performance and to determine if 90 min of rest between trials allowed complete performance recovery. Methods 12 healthy recreationally active adults (24.3±3.9 yrs; 24.2±3.9 kg/m 2 ) completed rhythmic isometric forearm handgripping (1s contraction:2s relaxation) while supine with exercising muscles at heart level. Day 1 consisted of completing one exercise test followed 90 min later by the other. The order of test presentation was reversed on Day 2. Pre‐test maximal voluntary contractions (MVCs) were completed prior to each trial. CI was calculated as the average contraction impulse of the last 30s of the CIT and W’ was calculated as the area under the curve between CI and the maximal effort contractions over the course of the test. Peak IET Performance was calculated as the average impulse of final stage contractions. Total IET Work was calculated as the cumulative impulse from first to final contraction. Fatigue during the CIT and IET protocols were measured as the relative change in impulse from the pre‐test MVC to CI or Peak IET Performance respectively. Results Whether the CIT was preceded by the IET or not did not affect CIT performance: CI (p=0.2;ICC=0.9;CV=8.8) and W’ (p=0.5;ICC=0.9; CV=8.3%). Whether the IET was preceded by a CIT or not did not affect Peak IET Performance (p=0.6; ICC=1.0;CV=5.0) or Total IET Work (p=0.1;ICC=0.9;CV=11.5%). Total IET Work and W’ were equally reproducible (CV=8.0% vs. CV=7.0%; p=0.7). The impulse at the end of the CIT was ~86.6%±3.3% of the impulse at the end of the IET. Fatigue was greater during the CIT versus IET (−56.8% vs. −48.6%) (p<0.001). There was a strong correlation between CIT and Peak IET Performance (R 2 = 0.8; p<0.001) and W’ and Total IET Work (R 2 = 0.8; p<0.001). Conclusion Performance for both exercise tests demonstrates good day‐to‐day repeatability and 90 min of recovery is adequate to ensure peak performance in both tests. Therefore, to assess both CIT and Peak IET Performance in one session it is recommended at least 90 min of recovery be provided to ensure the prior fatiguing protocol does not compromise subsequent maximal performance. Support or Funding Information Alyssa M. Fenuta, MSc, is supported by Queen's University School of Graduate Studies Bruce Mitchell Academic Leadership Award.

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)0.001
metaresearch head score (Gemma)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.265
Teacher spread0.247 · 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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Citations1
Published2016
Admission routes1
Has abstractyes

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