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Presence of Hysteresis in the Cerebral Pressure‐Flow Relationship During Repeated Squat‐Stand Maneuvers in Humans

2017· article· en· W4389017623 on OpenAlexafffundabout
Patrice Brassard, Hélène Ferland‐Dutil, Jonathan D. Smirl, Myriam Paquette, Olivier Blanc, Simon Malenfant, Philip N. Ainslie

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsMiddle cerebral arteryMedicineAnesthesiaBlood pressureCerebral blood flowTranscranial DopplerPhotoplethysmogramCardiologyMean arterial pressureRadial arteryCerebral arteriesSquatInternal medicineArteryHeart rateIschemiaPhysical medicine and rehabilitationFilter (signal processing)

Abstract

fetched live from OpenAlex

In humans, the cerebrovasculature is more efficient at compensating for transient hypertension compared with transient hypotension – a phenomenon called hysteresis. To date, however, these asymmetrical responses of cerebral blood flow (CBF) in response to changes in blood pressure have been reported using cyclic inflation and deflation of thigh cuffs in patients with head injury or via pharmacological interventions in healthy participants. Whether this phenomenon exists during non‐pharmacologically and physiologically‐induced transient hypertension and hypotension is unknown. In this study, we compared the relative change in CBF, as indexed by mean velocity in the middle cerebral artery (MCAvmean; transcranial Doppler), per relative change in mean arterial pressure (MAP; finger photoplethysmography) (%MCAvmean/%MAP) during transient hypertension and hypotension. These changes in MAP were reliability and repetitively induced during 5 minutes of repeated squat‐stand maneuvers performed at 0.05 Hz (10‐second squat–10‐second stand) and 0.10 Hz (5‐second squat–5‐second stand) in 64 healthy participants (Age [(mean±SD)] 32±14 yrs). These large oscillations in MAP (~25–30 mmHg) are transmitted to the cerebrovasculature when executed at frequencies within the high‐pass filter buffering range (<0.20 Hz). However, the results revealed the %MCAvmean/%MAP was attenuated by 26% ([median (range)]: 0.96 (−3.79–5.22) vs. 1.29 (−1.12–8.55) %/%; p=0.02 ] and 47% [0.92 (−2.93–3.26) vs. 1.74 (−0.29–9.38) %/%; p=0.0001 ] during transient hypertension compared to transient hypotension performed at 0.05 and 0.10 Hz, respectively. These findings suggest that the human cerebrovascular function is better adapted to compensate for physiologically relevant transient hypertension than transient hypotension. Support or Funding Information This research was supported via the Ministère de l'Education, du Loisir et du Sport du Quebec (PB), the Foundation of the Institut universitaire de cardiologie et de pneumologie de Quebec (PB), and an NSERC Discovery grant (PNA). PB was a Junior 1 Research Scholar of the Fonds de recherche du Québec – Santé.JDS was supported via an NSERC PGS‐D2 Fellowship and the Killam Pre‐Doctoral Fellowship. MP was supported via a scholarship from CIHR.

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 score0.001
Threshold uncertainty score0.002

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 head0.048
GPT teacher head0.289
Teacher spread0.241 · 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

Citations1
Published2017
Admission routes3
Has abstractyes

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