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Opening the pericardium during pulmonary artery constriction improves cardiac function

2004· article· en· W1989647055 on OpenAlexaff
Israel Belenkie, Rozsa Sas, Jamie R. Mitchell, Eldon R. Smith, John V. Tyberg

Bibliographic record

VenueJournal of Applied Physiology · 2004
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineCardiologyPericardiumInternal medicineVentricleStroke volumeConstrictionContractilityPulmonary arteryCardiac function curveHeart failureHeart rateBlood pressure

Abstract

fetched live from OpenAlex

During acute pulmonary hypertension, both the pericardium and the right ventricle (RV) constrain left ventricular (LV) filling; therefore, pericardiotomy should improve LV function. LV, RV, and pericardial pressures and RV and LV dimensions and LV stroke volume (SV) were measured in six anesthetized dogs. The pericardium was closed, the chest was left open, and the lungs were held away from the heart. Data were collected at baseline, during pulmonary artery constriction (PAC), and after pericardiotomy with PAC maintained. PAC decreased SV by one-half. RV diameter increased, and septum-to-LV free wall diameter and LV area (our index of LV end-diastolic volume) decreased. Compared with during PAC, pericardiotomy increased LV area and SV increased 35%. LV and RV compliance (pressure-dimension relations) and LV contractility (stroke work-LV area relations) were unchanged. Although series interaction accounts for much of the decreased cardiac output during acute pulmonary hypertension, pericardial constraint and leftward septal shift are also important. Pericardiotomy can improve LV function in the absence of other sources of external constraint to LV filling.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.967
Threshold uncertainty score0.273

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.011
GPT teacher head0.241
Teacher spread0.231 · 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 designBench or experimental
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

Citations50
Published2004
Admission routes1
Has abstractyes

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