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Record W3022273626 · doi:10.3389/fspor.2020.00041

Ischemic Preconditioning Enhances Aerobic Adaptations to Sprint-Interval Training in Athletes Without Altering Systemic Hypoxic Signaling and Immune Function

2020· article· en· W3022273626 on OpenAlexafffund
Pénélope Paradis‐Deschênes, Denis R. Joanisse, Pascale Mauriège, François Billaut

Bibliographic record

VenueFrontiers in Sports and Active Living · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsInstitut Universitaire de Cardiologie et de Pneumologie de QuébecUniversité Laval
FundersInstitut universitaire de cardiologie et de pneumologie de Québec, Université LavalUniversité Laval
KeywordsSprintMedicineHigh-intensity interval trainingHeart rateTime trialInterval trainingPlaceboCardiologyAthletesHypoxia (environmental)Physical therapyBlood lactateAerobic capacityInternal medicineBlood pressure

Abstract

fetched live from OpenAlex

Optimising traditional training methods to elicit greater adaptations is paramount for athletes. Ischemic preconditioning (IPC) can improve maximal exercise capacity and up-regulate signaling pathways involved in physiological training adaptations. However, data on the chronic use of IPC are scarce and its impact on high-intensity training is still unknown. We investigated the benefits of adding IPC to sprint-interval training (SIT) on performance and physiological adaptations of endurance athletes. In a randomized controlled trial, athletes included eight SIT sessions in their training routine for 4 weeks, preceded by IPC (3x5-min ischemia/5-min reperfusion cycles at 220 mmHg, n=11) or placebo (20 mmHg, n=9). Athletes were tested pre-, mid- and post-training on 30-sec Wingate test, 5-km time trial (TT) and maximal incremental step test. Arterial O2 saturation, heart rate, rate of perceived exertion and quadriceps muscle oxygenation changes in total hemoglobin (∆nTHb]), deoxy-hemoglobin (∆[HHb]) and tissue saturation index (∆TSI) were measured during exercise. Blood samples were taken pre- and post-training to determine blood markers of hypoxic response, lipid-lipoprotein profile and immune function. Differences within and between groups were analyzed using Cohen’s effect size (ES). Compared to PLA, IPC improved time to complete the TT (Mid vs. Post: -1.6%, Cohen’s ES±90% confidence limits -0.24, -0.40;-0.07) and increased power output (Mid vs. Post: 4.0%, ES 0.20, 0.06;0.35), ∆[THb] (Mid vs. Post: 73.6%, ES 0.70, -0.15;1.54, Pre vs. Post: 68.5%, ES 0.69, -0.05;1.43), Δ[HHb] (Pre vs. Post: 12.7%, ES 0.24, -0.11;0.59) and heart rate (Pre vs. Post: 1.4%, ES 0.21, -0.13;0.55, Mid vs. Post: 1.6%, ES 0.25, -0.09;0.60). IPC also attenuated the fatigue index in the Wingate test (Mid vs. Post: -8.4%, ES -0.37, -0.79;0.05). VO2peak and maximal aerobic power remained unchanged in both groups. Changes in blood markers of the hypoxic response, vasodilation, and angiogenesis remained within the normal clinical range in both groups. We concluded that IPC combined with SIT induces greater adaptations in cycling endurance performance that may be related to muscle perfusion and metabolic changes. The absence of elevated markers of immune function suggests that chronic IPC is devoid of deleterious effects in athletes, and is thus a safe and potent ergogenic tool.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.824
Threshold uncertainty score0.597

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.223
Teacher spread0.210 · 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 teacher head, 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".

Quick stats

Citations20
Published2020
Admission routes2
Has abstractyes

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