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Record W1991643906 · doi:10.1055/s-0032-1304553

Use of Impella 5L for Acute Allograft Rejection Postcardiac Transplant

2012· article· en· W1991643906 on OpenAlexaff
Rahul Chandola, Robert J. Cusimano, Mark Osten, Eric Horlick

Bibliographic record

VenueThe Thoracic and Cardiovascular Surgeon · 2012
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsImpellaMedicineIntensive care medicineInternal medicineVentricular assist deviceHeart failure

Abstract

fetched live from OpenAlex

The contribution of acute allograft rejection to posttransplant mortality has decreased over time primarily due to improvements in maintenance immunosuppression and in the diagnosis and treatment of rejection. Nevertheless, acute heart allograft rejection remains an important clinical problem.2 In the setting of an acute allograft rejection, mechanical circulatory support has been provided by a variety of devices, ranging from intra-aortic balloon pumps (IABP) to extracorporeal membrane oxygenators (ECMO), left ventricular assist devices (LVADs) and biventricular assist devices (BIVADs).2 We present a 45-year-old patient with cardiogenic shock secondary to acute allograft rejection after orthotopic heart transplantation. Patient continued to have poor hemodynamics and low cardiac output despite being on high doses of inotropes and an aggressive immunosuppression. Hence, a decision was made to support the hemodynamics with an Impella LP 5.0 (Abiomed Inc, Danvers, MA) left ventricular assist device (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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.042
GPT teacher head0.327
Teacher spread0.285 · 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 designCase report
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

Citations6
Published2012
Admission routes1
Has abstractyes

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