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Physiological and Clinical Assessment of Resting Physiological Indexes

2019· article· en· W2924653705 on OpenAlexaff
Joo Myung Lee, Ki Hong Choi, Jonghanne Park, Doyeon Hwang, Tae‐Min Rhee, Jinseob Kim, Jinhyoung Park, Hyung Yoon Kim, Hae Won Jung, Yun‐Kyeong Cho, Hyuck‐Jun Yoon, Young Bin Song, Joo‐Yong Hahn, Chang‐Wook Nam, Eun‐Seok Shin, Joon‐Hyung Doh, Seung‐Ho Hur, Bon‐Kwon Koo

Bibliographic record

VenueCirculation · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsMedicineCardiologyInternal medicineFractional flow reserveStenosisDiastoleMyocardial infarctionBlood pressureCoronary angiography

Abstract

fetched live from OpenAlex

Background: Recently, resting pressure–derived indexes such as resting full-cycle ratio (RFR) and diastolic pressure ratio (dPR) have been introduced to assess the functional significance of epicardial coronary stenosis. The present study sought to investigate the agreement of RFR or dPR with other pressure-derived indexes (instantaneous wave-free ratio [iFR] or fractional flow reserve), the sensitivity of RFR or dPR for anatomic or hemodynamic stenosis severity, and the prognostic implications of RFR or dPR compared with iFR Methods: RFR and dPR were calculated from resting pressure tracings by an independent core laboratory in 1024 vessels (435 patients). The changes in resting physiological indexes according to diameter stenosis were compared among iFR, RFR, and dPR. Among 115 patients who underwent 13 N-ammonia positron emission tomography, the changes in those indexes according to basal and hyperemic stenosis resistance and absolute hyperemic myocardial blood flow were compared. The association between resting physiological indexes and the risk of 2-year vessel-oriented composite outcomes (a composite of cardiac death, vessel-related myocardial infarction, and vessel-related ischemia-driven revascularization) was analyzed among 864 deferred vessels. Results: Both RFR and dPR showed a significant correlation with iFR ( R =0.979, P <0.001 for RFR; and R =0.985, P <0.001 for dPR), which was higher than that with fractional flow reserve ( R =0.822, P <0.001; and R =0.819, P <0.001, respectively). RFR and dPR showed a very high agreement with iFR (C index, 0.987 and 0.993). Percent difference of iFR, RFR, and dPR according to the increase in anatomic and hemodynamic severity was almost identical. The diagnostic performance of iFR, RFR, and dPR was not different in the prediction of myocardial ischemia defined by both low hyperemic myocardial blood flow and low coronary flow reserve by 13 N-ammonia positron emission tomography. All resting physiological indexes showed significant association with the risk of 2-year vessel-oriented composite outcomes (iFR per 0.1 increase: hazard ratio, 0.514 [95% CI, 0.370–0.715], P <0.001; RFR per 0.1 increase: hazard ratio, 0.524 [95% CI, 0.378–0.725], P <0.001; dPR per 0.1 increase: hazard ratio, 0.587 [95% CI, 0.436–0.791], P <0.001) in deferred vessels. Conclusions: All resting pressure–derived physiological indexes (iFR, RFR, and dPR) can be used as invasive tools to guide treatment strategy in patients with coronary artery disease. Clinical Trial Registration: URL: https://www.clinicaltrials.gov . Unique identifier: NCT01621438.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.019
Threshold uncertainty score0.172

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.067
GPT teacher head0.394
Teacher spread0.327 · 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 teacher head, 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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Citations121
Published2019
Admission routes1
Has abstractyes

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