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Record W4385442110 · doi:10.1002/clc.24094

LVAD therapy as a catalyst to heart failure remission and myocardial recovery

2023· review· en· W4385442110 on OpenAlexaff
Eman Hamad, Mirnela Byku, Sharon B. Larson, Filio Billia

Bibliographic record

VenueClinical Cardiology · 2023
Typereview
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicineVentricular assist deviceHeart failureGuidelineHemodynamicsCardiologyMedical therapyExplant cultureIntensive care medicineInternal medicineSurgeryPathology

Abstract

fetched live from OpenAlex

The management of chronic heart failure over the past decade has witnessed tremendous strides in medical optimization and device therapy including the use of left ventricular assist devices (LVAD). What we once thought of as irreversible damage to the myocardium is now demonstrating signs of reverse remodeling and recovery. Myocardial recovery on the structural, molecular, and hemodynamic level is necessary for sufficient recovery to withstand explant and achieve sustained recovery post-LVAD. Guideline-directed medical therapy and unloading have been shown to aid in recovery with the potential to successfully explant the LVAD. This review will summarize medical optimization, assessment for recovery, explant methodologies and outcomes post-recovery with explant of durable LVAD.

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)0.001
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.114
GPT teacher head0.391
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 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

Citations13
Published2023
Admission routes1
Has abstractyes

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