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Dynamic Adjustment Of Beat-by-beat Cardiac Output And Vo2 Kinetics During Moderate Intensity Exercise Transitions

2019· article· en· W2955435990 on OpenAlexaff
Erin Calaine Inglis, Danilo Iannetta, Juan M. Murias

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCardiologyBeat (acoustics)Cardiorespiratory fitnessVO2 maxCycle ergometerIntensity (physics)Internal medicineMedicineMathematicsHeart rateBlood pressurePhysics

Abstract

fetched live from OpenAlex

The kinetic adjustment of oxygen utilization (VO2) to exercise transitions of higher metabolic demands is proposed to be affected by central and peripheral alterations within the O2 transport system and/or intracellular mechanisms of control. Although limitations in O2 availability within the microcirculation but not at the conduit artery level have been proposed, knowledge is limited in relation to the contribution of the dynamic adjustment of cardiac output (Q) to the VO2 kinetics response, and how training status might modify this response. PURPOSE: This study aimed to compare the adjustment of muscle VO2 (i.e., Phase II VO2) to that of central O2 delivery as examined by the adjustment of Q during step transitions to moderate intensity exercise. METHODS: Sixteen young healthy male participants (35 ± 6 yrs) performed 3 step transitions from 20W to moderate-intensity cycling on a cycle ergometer to determine the breath-by-breath VO2 and the beat-by-beat Q responses. Participants were separated into two groups: trained (n= 9, VO2max 4.54 ± 0.40 L/min) and untrained (n= 7, VO2max 3.49 ± 0.68 L/min). Phase II VO2 and Q were modeled with a monoexponential model. Paired and unpaired t-tests and Pearson product moment correlations were used to compare the time constants of VO2 (τVO2) and Q (τQ). Statistical significance was set at P<0.05. RESULTS: Mean τVO2 was faster in the trained (13.9 ± 2.7s) compared to untrained (24.4 ± 6.4 s). τQ was slower than τVO2 in the trained (18.5 ± 6.0 s) but not untrained (20.2 ± 9.2 s). No difference was found between τQ between groups. Overall mean data showed no difference between τVO2 (18.5 ± 7.1 s) and τQ (19.3 ± 7.3 s). No significant correlations were found between τVO2 and τQ in trained (r=0.34), untrained (r=0.47), or when considering the two conditions together (r=0.37). CONCLUSION: This study demonstrated the dynamic adjustment of Q to exercise transition within the moderate intensity domain does not differ amongst trained and untrained individuals, even in the presence of training induced speeding of the VO2 kinetics. These data support the notion that mechanisms other than central delivery of O2, such as improved blood flow redistribution within the active tissues and/or intracellular components are responsible for controlling the rate of adjustment of VO2.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.008
GPT teacher head0.240
Teacher spread0.232 · 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
Published2019
Admission routes1
Has abstractyes

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