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Record W1966324100 · doi:10.1016/j.cjca.2014.03.010

Central Blood Pressure as an Index of Antihypertensive Control: Determinants and Potential Value

2014· review· en· W1966324100 on OpenAlexaffvenue
Luc Trudeau

Bibliographic record

VenueCanadian Journal of Cardiology · 2014
Typereview
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsMedicineBlood pressureAortic pressureCardiologyPulse wave velocityInternal medicinePulse pressureArterial stiffnessAortaPeripheralPulse Wave Analysis

Abstract

fetched live from OpenAlex

The measurement of central blood pressure has generated interest as a tool in predicting cardiovascular events. The purpose of this article is to review the meaning and measurement of the central blood pressure and consider its potential value as an index of the antihypertensive response. Indirect estimation of central aortic pressures is obtained by the study of the radial pulse wave compared with a central pulse wave contour measured at the carotid or femoral artery level. The sum of the forward pressure wave created by ventricular contraction and of the reflected pressure wave from the peripheral arterial system produce the peak systolic blood pressure in the aorta. Measurement of the peripheral reflected-wave contribution to aortic blood pressure can be quantified as the augmentation index. Also, the increase in the rapidity of this travelling wave can be measured as the pulse wave velocity. These 2 parameters are considered to be valid indices of the peripheral arterial stiffness. Along with the calculation of systolic and diastolic aortic pressures, these measurements can give a better understanding of the actual central blood pressure to which core organs like heart, brain, and kidneys are submitted. There is tantalizing evidence for the potential value of central blood pressure as a useful index of antihypertensive action, but until clear evidence is obtained, its use should continue to be considered exploratory.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.946
Threshold uncertainty score0.908

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
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)0.0000.000

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 head0.013
GPT teacher head0.287
Teacher spread0.274 · 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 designOther design
Domainnot available
GenreReview

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

Citations51
Published2014
Admission routes2
Has abstractyes

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