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Record W2053964318 · doi:10.1097/mot.0b013e3283574185

Who needs a transplant and when?

2012· review· en· W2053964318 on OpenAlexaff
Wan Xian Chan, Heather J. Ross

Bibliographic record

VenueCurrent Opinion in Organ Transplantation · 2012
Typereview
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsUniversity of TorontoToronto General HospitalUniversity Health Network
Fundersnot available
KeywordsMedicineComputer science

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Heart transplantation remains the treatment of choice for patients with advanced heart failure. We review the current definition of optimal therapy, prediction of prognosis and revisit contraindications for transplant. RECENT FINDINGS: Clinical trials of eplerenone and ivabradine were associated with improved prognosis, whereas others (nesiritide) were disappointing. Advances in cardiac resynchronization therapy and ventricular assist devices (VAD) have resulted in an expansion of their indications. Advances in catheter ablation for ventricular tachycardia have made this an uncommon indication for heart transplantation. Surgical ventricular reconstruction and mitral valve intervention have not resulted in survival benefit. Bypass surgery was associated with a lower mortality from cardiovascular causes. Prognostic risk scores have been developed in heart failure patients; however, ongoing refinements are needed. Selected patients with diabetes, HIV and pretransplant malignancy, now have favourable outcomes after heart transplantation. VAD as bridge to candidacy is an option in heart failure patients with 'fixed' pulmonary hypertension. Alternate listing strategies have also been studied to provide high-risk patients with an opportunity for heart transplantation. SUMMARY: Heart failure patients should be on current optimal medical and device therapy with a poor prognosis before consideration for heart transplantation. An individualized approach to heart transplantation assessment is recommended.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.899
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
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 head0.164
GPT teacher head0.427
Teacher spread0.263 · 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.

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

Citations0
Published2012
Admission routes1
Has abstractyes

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