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Record W1231259303 · doi:10.3390/medicina44110106

Return to work after coronary artery bypass surgery

2008· article· en· W1231259303 on OpenAlexaboutno aff
Donatas Antanas Vasiliauskas, Rasa Raugalienė, Vytautas Grižas, Jolanta Elena Marcinkevičienė, Lina Jasiukevičienė, Raimondas Kubilius, Vygantas Barsys

Bibliographic record

VenueMedicina · 2008
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAnginaCoronary artery bypass surgeryBypass surgeryArteryCoronary artery diseaseLogistic regressionSurgeryCanadian Cardiovascular SocietyRevascularizationCardiologyInternal medicineMyocardial infarction

Abstract

fetched live from OpenAlex

The aim of this study was to assess the possible reasons for not returning to work after coronary artery bypass surgery. A total of 134 patients (aged 65 years and younger) who underwent coronary bypass surgery in 2003 were examined. The analysis was performed in three groups of the patients: Group I, patients who were employed before surgery and returned to work after it (n=51); Group II, patients who were employed before surgery but did not return to work after surgery (n=55); and Group III, patients who were unemployed before and remained unemployed after surgery due to health problems (n=28). Number of injured coronary arteries, the extent of operation, postoperative complications, risk factors for ischemic heart disease, clinical status of patients (angina pain and heart failure), physical tolerance, and return to work within one year after coronary bypass surgery were analyzed. It was found that 48.1% of patients who were employed before surgery returned to work after myocardial revascularization. About 30% of patients experienced recurrent symptoms of angina after 12 months. Logistic regression analysis revealed that return to work was significantly influenced by female gender, physical pattern of work, age, and severity of heart failure.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.041
GPT teacher head0.346
Teacher spread0.306 · 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

Citations10
Published2008
Admission routes1
Has abstractyes

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