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Ventricular interaction and external constraint account for decreased stroke work during volume loading in CHF

2001· article· en· W2148255927 on OpenAlexaff
Thomas Moore, Michael Frenneaux, Rozsa Sas, J. Atherton, Jayne Morris‐Thurgood, Eldon R. Smith, John V. Tyberg, Israel Belenkie

Bibliographic record

VenueAmerican Journal of Physiology-Heart and Circulatory Physiology · 2001
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPreloadContractilityCardiologyInternal medicineMedicineVentricular pressureStroke volumeHemodynamicsHeart failureEnd-diastolic volumeAnesthesiaEjection fraction

Abstract

fetched live from OpenAlex

The slope of the stroke work (SW)-pulmonary capillary wedge pressure (PCWP) relation may be negative in congestive heart failure (CHF), implying decreased contractility based on the premise that PCWP is simply related to left ventricular (LV) end-diastolic volume. We hypothesized that the negative slope is explained by decreased transmural LV end-diastolic pressure (LVEDP), despite the increased LVEDP, and that contractility remains unchanged. Rapid pacing produced CHF in six dogs. Hemodynamic and dimension changes were then measured under anesthesia during volume manipulation. Volume loading increased pericardial pressure and LVEDP but decreased transmural LVEDP and SW. Right ventricular diameter increased and septum-to-LV free wall diameter decreased. Although the slopes of the SW-LVEDP relations were negative, the SW-transmural LVEDP relations remained positive, indicating unchanged contractility. Similarly, the SW-segment length relations suggested unchanged contractility. Pressure surrounding the LV must be subtracted from LVEDP to calculate transmural LVEDP accurately. When this was done in this model, the apparent decrease in contractility was no longer evident. Despite the increased LVEDP during volume loading, transmural LVEDP and therefore SW decreased and contractility remained unchanged.

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 score0.849
Threshold uncertainty score0.621

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.248
Teacher spread0.238 · 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

Citations80
Published2001
Admission routes1
Has abstractyes

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