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Record W1599635067 · doi:10.1113/jphysiol.2014.280586

Impact of hypocapnia and cerebral perfusion on orthostatic tolerance

2014· article· en· W1599635067 on OpenAlexaff
Nia C. S. Lewis, Anthony R. Bain, David B. MacLeod, Kevin W. Wildfong, Kurt J. Smith, Christopher K. Willie, Marit L. Sanders, Tianne Numan, Shawnda A. Morrison, Glen E. Foster, Julian M. Stewart, Philip N. Ainslie

Bibliographic record

VenueThe Journal of Physiology · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Syncope and Autonomic Disorders
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsHypocapniaOrthostatic vital signsMedicineCardiologyAnesthesiaCerebral perfusion pressurePerfusionInternal medicineNeurosciencePsychologyHypercapniaBlood pressure

Abstract

fetched live from OpenAlex

Key points Vasovagal syncope (a common form of fainting) is frequently associated with excessive breathing and leads to reductions in carbon dioxide (hypocapnia) and cerebral hypoperfusion. The prevention of hypocapnia during orthostatic stress has been shown to improve orthostatic tolerance, but it still remains to be quantified in a larger population, with a more sustained orthostatic stress. Resting brain blood flow has been shown to impact orthostatic tolerance; however, the importance of resting brain blood flow per se in the pathophysiology of vasovagal syncope has not been clearly explicated. Our findings show that cerebral hypoperfusion either at rest or induced by hypocapnia at pre‐syncope do not impact on orthostatic tolerance, probably due to a compensatory increase in oxygen extraction of the brain. Abstract We examined two novel hypotheses: (1) that orthostatic tolerance (OT) would be prolonged when hyperventilatory‐induced hypocapnia (and hence cerebral hypoperfusion) was prevented; and (2) that pharmacological reductions in cerebral blood flow (CBF) at baseline would lower the ‘CBF reserve’, and ultimately reduce OT. In study 1 ( n = 24; aged 25 ± 4 years) participants underwent progressive lower‐body negative pressure (LBNP) until pre‐syncope; end‐tidal carbon dioxide ( ) was clamped at baseline levels (isocapnic trial) or uncontrolled. In study 2 ( n = 10; aged 25 ± 4 years), CBF was pharmacologically reduced by administration of indomethacin (INDO; 1.2 mg kg −1 ) or unaltered (placebo) followed by LBNP to pre‐syncope. Beat‐by‐beat measurements of middle cerebral artery blood flow velocity (MCAv; transcranial Doppler), heart rate (ECG), blood pressure (BP; Finometer) and end‐tidal gases were obtained continuously. In a subset of subjects’ arterial‐to‐jugular venous differences were obtained to examine the independent impact of hypocapnia or cerebral hypoperfusion (following INDO) on cerebral oxygen delivery and extraction. In study 1, during the isocapnic trial, was successfully clamped at baseline levels at pre‐syncope (38.3 ± 2.7 vs . 38.5 ± 2.5 mmHg respectively; P = 0.50). In the uncontrolled trial, at pre‐syncope was reduced by 10.9 ± 3.9 mmHg ( P ≤ 0.001). Compared to the isocapnic trial, the decline in mean MCAv was 15 ± 4 cm s −1 (35%; P ≤ 0.001) greater in the uncontrolled trial, yet the time to pre‐syncope was comparable between trials (544 ± 130 vs . 572 ± 180 s; P = 0.30). In study 2, compared to placebo, INDO reduced resting MCAv by 19 ± 4 cm s −1 (31%; P ≤ 0.001), but time to pre‐syncope remained similar between trials (placebo: 1123 ± 138 s vs . INDO: 1175 ± 212 s; P = 0.53). The brain extracted more oxygen in face of hypocapnia (34% to 53%) or cerebral hypoperfusion (34% to 57%) to compensate for reductions in delivery. In summary, cerebral hypoperfusion either at rest or induced by hypocapnia at pre‐syncope does not impact OT, probably due to a compensatory increase in oxygen extraction.

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 score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.007
GPT teacher head0.254
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".

Quick stats

Citations46
Published2014
Admission routes1
Has abstractyes

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