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Record W2438002404

[Clinical outcome of patients after transmyocardial laser revascularization alone and combined with coronary artery bypass grafting].

2003· article· en· W2438002404 on OpenAlexaboutno aff
Mirosław Dziuk, Hany Eldeeb, K. E. Britton, Steve Edmondson, Wiktor Piechota, Marian Cholewa

Bibliographic record

VenuePubMed · 2003
Typearticle
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEjection fractionCanadian Cardiovascular SocietyCardiologyRadionuclide ventriculographyAnginaInternal medicineRevascularizationBypass graftingArteryHeart failureMyocardial infarction
DOInot available

Abstract

fetched live from OpenAlex

The aim of the study was to assess the effect of transmyocardial laser revascularization (TMLR) alone and in combination with coronary artery bypass grafting (CABG) on the angina score (CCS--Canadian Cardiovascular Society class), exercise tolerance and left ventricular function 6 months after the procedures. Sixty two patients were subjected to revascularization, 38 to sole TMLR procedure and 24 to combination CABG and TMLR (CABG/TMLR group). The angina score and exercise stress test together with radionuclide ventriculography were performed before and 6 months after the operation. The angina class and exercise tolerance were similar in both groups preoperatively. After the operation the improvement was seen in both groups with no statistical difference. The left ventricular ejection fraction were 61 +/- 8% and 54 +/- 8% (p < 0.05) before operation and after 6 months respectively. Transmyocardial laser revascularisation alone and in combination with coronary artery bypass grafting may relieve the angina and improve the exercise tolerance. However the left ventricular ejection fraction may drop significantly.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.234
Teacher spread0.216 · 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 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

Citations4
Published2003
Admission routes1
Has abstractyes

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