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Record W1977425891 · doi:10.1159/000128470

Peroperative Myocardial Ischemia and Citrate Administration: Cardiovascular Adaptability in Conscious Dogs

2008· article· en· W1977425891 on OpenAlexaff
Lionel Dumont, Paul Stanley, C Chartrand

Bibliographic record

VenueEuropean Surgical Research · 2008
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineHemodynamicsIschemiaInotropeAnesthesiaCardiologyInternal medicineVasodilationAscending aortaAorta

Abstract

fetched live from OpenAlex

Since the hemodynamic response elicited by the administration of citrate is sensitive to alterations in the baseline cardiovascular status, we have investigated the consequences of peroperative myocardial ischemia upon this hemodynamic response. 19 dogs equipped with an electromagnetic flow probe positioned around the ascending aorta served as control (group I). 16 dogs were equipped similarly and in addition submitted to 1 h of myocardial ischemia combined with topical cardiac hypothermia (group II). Hemodynamic studies were carried out 3 h postoperatively and then daily for 1 month, before and during rapid intravenous administration of citrate. From baseline hemodynamic data, cardiac failure was only evident 3 h postoperatively in group II. Transient hypotension and myocardial depression resulted from administration of citrate in both groups with no evidence of peripheral vasodilation. Hypotension and the negative inotropic response were more pronounced in the presence of cardiac failure following peroperative myocardial ischemia. Long-term studies indicate that global myocardial ischemia did not interfere with the cardiovascular adaptability to this pharmacologic interference.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.105
GPT teacher head0.354
Teacher spread0.249 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2008
Admission routes1
Has abstractyes

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