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Coronary Blood Flow Velocity Responses to Oxygen and Carbon Dioxide in Humans

2016· article· en· W4389026564 on OpenAlexafffund
Lindsey M. Boulet, Mike Stembridge, Michael M. Tymko, Josh C Tremblay, Glen E. Foster

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsUniversity of British Columbia, Okanagan CampusKelowna General HospitalUniversity of British ColumbiaInterior Health
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHypocapniaCardiologyInternal medicineHemodynamicsMedicineBlood flowHeart rateHypercapniaBlood pressureHypoxia (environmental)AnesthesiaOxygenChemistryRespiratory system

Abstract

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In humans, coronary blood flow (CBF) is tightly regulated by microvessels within the myocardium. While there is clear evidence that CBF rises to match myocardial workload, there is conflicting evidence regarding the inherent sensitivity of the coronary vasculature to changes in the partial pressure of arterial carbon dioxide (PaCO 2 ) and oxygen (PaO 2 ) within the physiological range. The purpose of this study was to investigate the changes in CBF associated with isooxic hypo‐ and hyper‐capnia and isocapnic hypoxia. We hypothesized that a modest systemic increase in end‐tidal partial pressure of CO 2 (PetCO 2 ) or decrease in end‐tidal partial pressure of O 2 (PetO 2 ) would result in a significant increase in coronary blood flow velocity (CBF V ) due to downstream vessel dilatation. Likewise, we hypothesized that hypocapnia would cause a reduction in CBF V . Finally, we hypothesized that normalizing for cardiac workload (W C ) or mechanical energy (E M ) would diminish the observed reactivity. Young men free of cardiovascular disease (age = 23.4 ± 1.3 years, n=14) were exposed to two ventilatory challenges: (1) an isooxic CO 2 test that consisted of six, 8‐min steps of PetCO 2 (−8, −4, 0, +4, and +8 mmHg from baseline values) and (2) an isocapnic hypoxic test that involved three, 8‐min steps of hypoxia (PetO 2 = 64, 52 and 45 mmHg). CBF V was measured using Doppler echocardiography in the mid segment of the left anterior descending coronary artery (LAD). W C and E M were estimated using the rate pressure product (RPP; systolic blood pressure × heart rate) and the area of a derived pressure‐volume loop (PV A ) respectively. The PV A was calculated using volumes derived from echocardiographic measurements, a validated estimation of left ventricular end‐systolic elastance and beat‐by‐beat blood pressure from photoplethsmography. A PetCO 2 of +8 mmHg evoked a 34.6 ± 8.5% increase in mean peak diastolic CBF V (P<0.01). CBF V increased by 38.3 ± 12.6% and 51.4 ± 8.8% in response to a PetO 2 of 52 and 45 mmHg, respectively (P<0.05). RPP and PV A were significantly elevated during hypercapnia (+4, +8 mmHg PetCO 2 ; P<0.05), hypoxia (52 and 45 mmHg PetO 2 ; P<0.01) and were not different during hypocapnia (P>0.05). When CBF V was indexed against either measure of RPP and PV A , the CBF V responses to hypercapnia and hypoxia were abolished. Estimated coronary vascular resistance (CBF V /mean arterial pressure) did not change significantly across any protocols (P>0.05). With respect to absolute changes in CBF V , hypercapnia and hypoxia elicit increases in peak diastolic velocity; though when corrected for changes in RPP and PV A associated with each condition the changes in CBF V were absent (P>0.05). In summary, the lack of sensitivity of the coronary vasculature supplied by the LAD is underscored by the lack of both a CBF V and cardiac workload response in hypocapnia. It can be surmised that the regulation of coronary vessels is mediated primarily through metabolic changes within the heart rather than an inherent sensitivity to changes in arterial blood gases within a physiological range. Support or Funding Information Funding: NSERC, CFI

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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 score0.003

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 integrity0.0010.000
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 head0.019
GPT teacher head0.270
Teacher spread0.252 · 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

Citations0
Published2016
Admission routes2
Has abstractyes

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