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Lower dynamic cerebral autoregulation following acute bout of low-volume high-intensity interval exercise in chronic stroke compared to healthy adults

2024· article· en· W4391872791 on OpenAlexaff
Alicen A. Whitaker, Stacey E. Aaron, Mark E. Chertoff, Patrice Brassard, Jake Buchanan, Katherine Nguyen, Eric D. Vidoni, Saniya Waghmare, Sarah M. Eickmeyer, Robert N. Montgomery, Sandra A. Billinger

Bibliographic record

VenueJournal of Applied Physiology · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentAmerican Heart AssociationNational Center for Research ResourcesNational Heart, Lung, and Blood InstituteNational Institute on AgingNational Center for Advancing Translational Sciences
KeywordsCerebral autoregulationMiddle cerebral arteryAutoregulationBlood pressureCardiologyMedicineMean arterial pressureStroke (engine)Intensity (physics)AnesthesiaInternal medicinePhysical medicine and rehabilitationHeart rateIschemiaPhysics

Abstract

fetched live from OpenAlex

This study provides novel insights into poststroke dynamic cerebral autoregulation (dCA) following an acute bout of high-intensity interval exercise (HIIE). In people after stroke, dCA appears attenuated during spontaneous fluctuations in mean arterial pressure (MAP) and middle cerebral artery blood velocity (MCAv) following HIIE. However, the dCA response during a single sit-to-stand transition after HIIE showed no significant difference from controls. These findings suggest that HIIE may temporarily challenge dCA after exercise in individuals with stroke.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

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 head0.269
Teacher spread0.260 · 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".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractyes

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