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Record W2049468925 · doi:10.1152/ajpheart.00505.2002

Direct and series transmission of left atrial pressure perturbations to the pulmonary artery: a study using wave-intensity analysis

2004· article· en· W2049468925 on OpenAlexaff
Ellen Herdis Hollander, Gary Dobson, Jiun‐Jr Wang, Kim H. Parker, John V. Tyberg

Bibliographic record

VenueAmerican Journal of Physiology-Heart and Circulatory Physiology · 2004
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsCalgary General HospitalUniversity of Calgary
Fundersnot available
KeywordsPreloadCardiologySystoleInternal medicineDiastolePulmonary arteryMedicineCardiac cycleBalloonBlood pressureVentricular pressureIntensity (physics)HemodynamicsPhysics

Abstract

fetched live from OpenAlex

Pressure waves are thought to travel from the left atrium (LA) to the pulmonary artery (PA) only retrogradely, via the vasculature. In seven anesthetized open-chest dogs, a balloon was placed in the LA, which was rapidly inflated and deflated during diastole, early systole, and late systole. High-fidelity pressures were measured within and around the heart. Measurements were made at low volume [LoV; left ventricular end-diastolic pressure (LVEDP) = 5-9 mmHg], high volume (HiV; LVEDP = 16-19 mmHg), and HiV with the pericardium removed. Wave-intensity analysis demonstrated that, except during late systole, balloon inflation created forward-going PA compression waves that were transmitted directly through the heart without measurable delay; backward PA compression waves were transmitted in-series through the pulmonary vasculature and arrived after delays of 90 +/- 3 ms (HiV) and 103 +/- 5 ms (LoV; P < 0.05). Direct transmission was greater during diastole, and both direct and series transmission increased with volume loading. Pressure waves from the LA arrive in the PA by two distinct routes: rapidly and directly through the heart and delayed and in-series through the pulmonary vasculature.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.971
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.015
GPT teacher head0.251
Teacher spread0.236 · 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".

Quick stats

Citations31
Published2004
Admission routes1
Has abstractyes

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