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Record W2434285670

Evidence for left ventricular constraint during open heart surgery.

2002· article· en· W2434285670 on OpenAlexaff
Israel Belenkie, Teresa M. Kieser, Rozsa Sas, Eldon R. Smith, John V. Tyberg

Bibliographic record

VenuePubMed · 2002
Typearticle
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPreloadMedicineCardiologyPulmonary wedge pressureInternal medicineHemodynamicsCardiac indexCardiopulmonary bypassCardiac output
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: The degree to which the lungs and other mediastinal structures constrain the heart during cardiac surgery is uncertain. OBJECTIVES: To assess the degree of constraint to left ventricular (LV) filling that is present during cardiac surgery. PATIENTS AND METHODS: Central venous (CVP) and pulmonary capillary wedge pressures (PCWP), and an index of LV end-diastolic volume (LVEDV) - LV area, transesophageal echocardiography - were measured before and after sternotomy, after volume loading, after pericardiotomy, and before and after sternal closure following the clinically indicated procedure in 12 patients undergoing cardiac surgery. PCWP and estimated transmural LVEDP (PCWP-CVP) were plotted against the LV area. RESULTS: In all patients, the difference between PCWP and estimated transmural LVEDP-LV area relations over the full range of LV areas was substantial, indicating the presence of important constraint to filling. Even at small LV areas, when transmural LVEDP approached zero, PCWP was almost always greater than 10 mmHg. Because transmural LVEDP approached zero when areas were smallest, transmural LVEDP-LV area relations were judged to be more plausible than the corresponding PCWP-LV area relations. CONCLUSIONS: Considerable constraint to cardiac filling is effected by the lungs and other mediastinal structures. This constraint must be considered when assessing LV filling pressure - PCWP is not a reliable measure of LV preload in these circumstances.

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)0.001
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 score0.549
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.114
GPT teacher head0.292
Teacher spread0.178 · 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

Citations20
Published2002
Admission routes1
Has abstractyes

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