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Record W1972668327 · doi:10.1186/1532-429x-16-s1-p49

Breathing maneuvers may elicit a stronger myocardial vascular response than clinical adenosine protocols

2014· article· en· W1972668327 on OpenAlexaff
Kady Fischer, Dominik P. Guensch, Matthias G. Friedrich

Bibliographic record

VenueJournal of Cardiovascular Magnetic Resonance · 2014
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsMedicineAdenosineVasodilationHyperventilationAngiologyBreathingCardiologyOxygenationAnesthesiaAdenosine receptorPerfusionInternal medicineReceptor

Abstract

fetched live from OpenAlex

Adenosine is one of the currently used agents for pharmacological vasodilation protocols used in imaging myocardial perfusion deficits. Yet, its clinical utility is limited by cost, need for i.v. access, and by side effects such as dyspnea and AV block, requiring the presence of a trained physician during administration. Recently, breath holds have been proposed as a potential alternative to adenosine administration; yet, the vasodilatory response has not been compared with adenosine as a standard vasodilatory agent. We investigated the use of breath-holds to induce vasodilation in healthy volunteers in direct comparison to the reference adenosine using oxygenation-sensitive (OS)-CMR, which allows for non-invasive monitoring of changes in myocardial tissue oxygenation. We combined a period of hyperventilation with a long voluntary breath-hold to maximize the range of the inducible vasodilatory response. We studied 19 healthy volunteers (mean age 43 ± 4 y) using a clinical 3T MRI system. OS-CMR images were acquired in one mid-ventricular short axis slice using an ECG-triggered balanced SSFP sequence. Volunteers hyperventilated for 60 s aiming for a rate of 40 breaths/min followed by a maximal long breath-hold at end-expiration (HVBH). OS-CMR images were acquired continuously throughout the long breath-hold at an acquisition rate of 1 measurement every 4 heart beats until the participant voluntarily commenced breathing. Single measurement acquisitions were obtained for a baseline image and during (3.5 minutes after start) adenosine infusion (140 μg/kg/min, i.v.). Systolic images were analyzed for the global myocardial signal intensity (SI) change in comparison to baseline, expressed as % change. The breath hold was assessed at two time points; the end of the breath-hold and the when the maximal SI occurred. On a questionnaire, volunteers ranked the maneuvers based on difficulty to perform. The mean duration of the HVBH was 74 s (± 7 s) with a final change in SI of 12.8%* (± 2.0), but a peak SI of 18.1%* (± 3.9) was reached after 41 s (± 4). In comparison, the change after adenosine was significant but yielded a change of 2.8%(± 1.2)* only. Both the final and peak SI values were significantly greater than adenosine (*p < 0.05, n = 19). There was not a significant difference in difficulty between the two maneuvers from the questionnaire but 5 volunteers experienced adverse effects with the HVBH that all disappeared with normal breathing, whereas 11 volunteers (58%) experienced adverse effects from adenosine, with 3 saying the effects persisted even after the drug was stopped. A breathing maneuver combining hyperventilation with a long breath-hold may elicit a stronger vasodilatory response than a standard clinical infusion of adenosine and may be a simpler, cheaper, and more effective approach to assess the vascular response in patients with suspected coronary artery disease.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0030.000

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 head0.025
GPT teacher head0.336
Teacher spread0.311 · 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".

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Citations1
Published2014
Admission routes1
Has abstractyes

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