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Record W2895700936 · doi:10.1097/hco.0000000000000565

The ROMA trial

2018· review· en· W2895700936 on OpenAlexaff
Mario Gaudino, David P. Taggart, Stephen E. Fremes

Bibliographic record

VenueCurrent Opinion in Cardiology · 2018
Typereview
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineObservational studyRandomized controlled trialConfoundingInterim analysisClinical trialCoronary artery bypass surgeryArteryRadial arteryInternal medicineCardiologyIntensive care medicineSurgery

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: We herein summarize the current evidence on the clinical outcome associated with the use of single and multiple arterial grafts for coronary bypass surgery and the role and importance of the Randomized comparison of the clinical Outcome of single versus Multiple Arterial grafts (ROMA) trial. RECENT FINDINGS: Observational evidence suggests that the use of multiple arterial grafts is associated with better clinical outcomes compared to the use of a single arterial graft. Randomized evidence is inconclusive; the 5-year interim analysis of the largest randomized trial on the topic did not show any clinical benefit associated with the use of bilateral versus single internal thoracic arteries, whereas a pooled analysis of the trials comparing the radial artery and the saphenous vein as a second graft showed a significant reduction in follow-up cardiac events using the radial artery. Hidden confounders and treatment allocation biases as well as methodological flaws are the most likely explanation of this contradiction. SUMMARY: ROMA was conceived based on the lessons learned from a critical analysis of the existing randomized and observational evidence with the aim to provide a definitive answer to the question of the potential clinical benefit of multiple arterial grafts for coronary bypass.

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 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 score0.892
Threshold uncertainty score0.854

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.152
GPT teacher head0.444
Teacher spread0.292 · 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 teacher head, 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

Citations25
Published2018
Admission routes1
Has abstractyes

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