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Post-Coronary Artery Bypass Graft Surgery and Associated Rehabilitation

2019· review· en· W2982469886 on OpenAlexaffabout
Nisarg Radadia, Vivek Patel

Bibliographic record

VenueCritical Reviews in Physical and Rehabilitation Medicine · 2019
Typereview
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineRehabilitationIntensive care unitQuality of life (healthcare)ArteryRandomized controlled trialCoronary artery bypass surgeryBlood pressurePhysical therapyCardiac surgeryHeart rateSurgeryIntensive care medicineInternal medicineNursing

Abstract

fetched live from OpenAlex

Coronary artery bypass graft (CABG) surgery is one of the most common cardiac surgeries performed in Canada and the United States. Every year, nearly 500,000 CABG surgeries are performed in the USA. After surgery, patients are in the intensive care unit for 2-3 days, where blood pressure, heart rate, oxygen levels, and pulmonary function are constantly monitored. In some instances, an exercise protocol (called phase I) may be implemented in the ICU; however, its effectiveness is not certain. In phase II, rehabilitation consists of medically supervised exercises and education on stress reduction and healthy living. In this review, randomized clinical trial studies in the last 10 years will be analyzed to determine (1) optimal exercises in phase I and phase II to improve physical function capacity, (2) medications to help reduce postoperative complications and manage comorbidities, (3) management of psychological function to increase health-related quality of life, and (4) comparing home-based to supervised hospital treatment.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.050
GPT teacher head0.424
Teacher spread0.374 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2019
Admission routes2
Has abstractyes

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