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Explantation of a Mechanical Assist Device:. Assessment of Myocardial Recovery

2004· article· en· W1540305987 on OpenAlexaff
Diego Delgado, Vivek Rao, Santiago Miriuka, Abdurrahman Al-Hesayen, Jane McIver, Christopher M. Feindel, Robert J. Cusimano, Heather J. Ross

Bibliographic record

VenueJournal of Cardiac Surgery · 2004
Typearticle
Languageen
FieldMedicine
TopicCardiac Structural Anomalies and Repair
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsMedicineVentricular assist deviceCardiologyDobutamineHemodynamicsMyocarditisHeart failureInternal medicineRefractory (planetary science)

Abstract

fetched live from OpenAlex

Reliable predictors of myocardial recovery post-mechanical assist device implantation are not well defined. We report the case of a 29-year-old woman with refractory congestive heart failure due to acute myocarditis of unknown etiology. The patient was supported with a HeartMate (Thoratec Corp., Woburn, MI) left ventricular assist device for 100 days showing improvement in clinical status. Hemodynamic monitoring, dobutamine stress echocardiography, and cardiopulmonary testing were performed to identify myocardial recovery. Improvements in myocardial reserve, hemodynamic parameters, and myocardial oxygen consumption were identified prior to explantation. The patient was successfully explanted. This case confirms that myocardial recovery is feasible with the use of a mechanical assist device. This article describes our current left ventricular assist device weaning protocol.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.295
Teacher spread0.277 · 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 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

Citations11
Published2004
Admission routes1
Has abstractyes

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