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Comparison of Non‐Invasive Peripheral Vascular Function to Invasive Measures of Coronary Function in Patients with Suspected Coronary Microvascular Dysfunction

2019· article· en· W3173393094 on OpenAlexafffund
Massimo Nardone, Steven E.S. Miner, Mary C. McCarthy, Heather Edgell

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsSouthlake Regional Health CenterYork University
FundersSt. Jude MedicalYork University
KeywordsMedicineReactive hyperemiaCoronary flow reserveCardiologyInternal medicineBrachial arteryEndothelial dysfunctionCoronary artery diseaseDobutamineVascular resistanceCuffForearmHemodynamicsIschemiaFractional flow reserveBlood pressureBlood flowSurgeryMyocardial infarction

Abstract

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Introduction The purpose of this study is to compare non‐invasive vascular assessments to invasive gold standard measures of coronary flow and resistance in patients with suspected coronary microvascular dysfunction (CMD), a condition driven by systemic endothelial dysfunction. We hypothesize that non‐invasive measures will be associated with both coronary flow and resistance following pharmacological hyperemia. Methods Forty‐one patients with suspected CMD attended the Cardiovascular Integrative Physiology Clinic at Southlake Regional Health Centre. Patients underwent finger‐based arterial tonometry (RHPAT) to non‐invasively quantify microvascular endothelial function (EndoPAT). A subset of participants (n=15) also concurrently completed flow mediated dilation (FMD) of the brachial artery to assess conduit artery endothelial function. Briefly, a standard blood pressure cuff was positioned on the right arm of patients, distal to the elbow joint. Baseline recordings preceded 5 minutes of forearm ischemia, and was followed by cuff deflation, eliciting reperfusion. Within 4 months, patients underwent coronary reactivity testing using the Doppler guidewire method. Specifically, the coronary flow reserve (CFR), and the index of microvascular resistance (IMR) were calculated during pharmacologically‐induced hyperemia using adenosine, then acetylcholine, then dobutamine. Prior to each stimuli, baseline measures were obtained to ensure hemodynamics results to baseline. Results RHPAT was negatively correlated to the IMR during dobutamine (r=−0.39, p=0.04), but not the CFR (r=0.14, p=0.49). FMD was negatively correlated to the IMR during adenosine (r=−0.64, p=0.01), but not the CFR (r=0.29, p=0.30). RHPAT and FMD were not correlated to the IMR or CFR during acetylcholine. Conclusion These preliminary results suggest that measures of non‐invasive peripheral vascular function can predict pharmacologically induced changes in coronary resistance, but not coronary flow. Support or Funding Information St. Jude Medical The Heart of Gold Cardiac Research Fund York University This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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)0.003
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.014
GPT teacher head0.246
Teacher spread0.232 · 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
Published2019
Admission routes2
Has abstractyes

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