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Record W2732477594 · doi:10.1177/8756479317716394

Analysis of the Velocity Profile of the Popliteal Artery and Its Relevance During Blood Flow Studies

2017· article· en· W2732477594 on OpenAlexaff
Omodele Olowoyeye, Stephanie Chiu, General Leung, Graham A. Wright, Alan R. Moody

Bibliographic record

VenueJournal of diagnostic medical sonography · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsPopliteal arteryMedicineBlood flowCardiologyReactive hyperemiaBrachial arteryInternal medicineOcclusionArteryFlow velocityAnatomyBlood pressure

Abstract

fetched live from OpenAlex

The mean blood velocity is required to calculate blood flow and to determine the associated shear rate. The maximal blood flow velocity is assumed to have a parabolic velocity profile; therefore, the mean velocity is half of the maximal value. Previous studies have been carried out on vessels such as the brachial and femoral artery, but none have been reported for the popliteal artery. To assess the velocity profile of the popliteal artery, a spectral Doppler analysis was performed on ten healthy patients during varied flow states (resting, distal occlusion, hyperemia). The results were then averaged over the entire cardiac cycle. The flow described in these patients’ popliteal artery had a blunted parabolic flow profile with a TAV mean :TAV max ratio of 0.68 ± 0.07 at baseline. The baseline measures were compared to a TAV mean :TAV max ratio of 0.68 ± 0.12 during distal occlusion and 0.67 ± 0.16 during reactive hyperemia. These descriptive results may suggest that adjustments may be needed for a blunted parabolic profile, especially when calculating the mean velocity of the popliteal artery.

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)0.001
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.016
GPT teacher head0.302
Teacher spread0.286 · 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.

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

Citations6
Published2017
Admission routes1
Has abstractyes

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