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Record W2989474727 · doi:10.18535/jmscr/v7i11.17

Outcome & Effect of Coronary Artery Bypass Graft Surgery on Left Ventricular Systolic Function: A Descriptive Study

2019· article· en· W2989474727 on OpenAlexaboutno aff
Dr Nareshchand Hegde H

Bibliographic record

VenueJournal of Medical Science And clinical Research · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCardiologyInternal medicineArteryVentricular functionCoronary artery bypass surgeryBypass grafting

Abstract

fetched live from OpenAlex

Background and Objectives: Patients with low ejection fraction (EF) are at high risk for postoperative complication and mortality. Our Aim: outcome & effect of coronary artery bypass graft surgery on left ventricular systolic function. Materials and Methods: This is a descriptive study. Between January 2017 to August 2019, 51 consecutive patients underwent isolated CABG at the Rajarajeshwari medical college and Hospital. Of these, 51 had echocardiographic assessment of LV function, preoperatively with respect to patient characteristics, risk factors, and preoperative two dimension echocardiography (2D ECHO). Depending on findings of 2D ECHO patients were divided into three groups: in Group 1, we included patients with EF 30%-35%, Group 2 comprised patients with EF of 25%-30%, and Group 3 consisted of patients with EF. Appropriate investigations were done. Results: Hospital mortality rate in present series was 9.8%. Mean grafts were 3.02 per patient. Fourteen (40%) patient had a postoperative complication. EF improved in 78% of patients. Canadian Cardiovascular Society Angina class improved in 42% of patients. Conclusion: We have shown that cardiac surgery provides long-term cardiac-death-free survival benefit in patients of all subsets of LV function, including poor and very poor LV function.

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)0.059
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0590.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.158
GPT teacher head0.475
Teacher spread0.317 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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