MétaCan
Menu
Back to cohort
Record W1972401706 · doi:10.1155/2012/210210

Antibody-Mediated Rejection: An Evolving Entity in Heart Transplantation

2012· article· en· W1972401706 on OpenAlexafffund
Sharon Chih, Andrzej Chruscinski, Heather J. Ross, Kathryn Tinckam, Jagdish Butany, Vivek Rao

Bibliographic record

VenueJournal of Transplantation · 2012
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsToronto General HospitalUniversity Health Network
FundersCanadian Institutes of Health ResearchHeart and Stroke Foundation of Canada
KeywordsMedicineHeart transplantationTransplantationComplement systemPathogenesisAntibodyImmune systemImmunologyHistopathologyComplicationComplement (music)ImmunopathologyHeart failurePathologyInternal medicineGene

Abstract

fetched live from OpenAlex

Antibody-mediated rejection (AMR) is gaining increasing recognition as a major complication after heart transplantation, posing a significant risk for allograft failure, cardiac allograft vasculopathy, and poor survival. AMR results from activation of the humoral immune arm and the production of donor-specific antibodies (DSA) that bind to the cardiac allograft causing myocardial injury predominantly through complement activation. The diagnosis of AMR has evolved from a clinical diagnosis involving allograft dysfunction and the presence of DSA to a primarily pathologic diagnosis based on histopathology and immunopathology. Treatment for AMR is multifaceted, targeting inhibition of the humoral immune system at different levels with emerging agents including proteasome and complement inhibitors showing particular promise. While there have been significant advances in our current understanding of the pathogenesis, diagnosis, and treatment of AMR, further research is required to determine optimal diagnostic tools, therapeutic agents, and timing of treatment.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
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 head0.029
GPT teacher head0.362
Teacher spread0.332 · 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 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

Citations48
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueJournal of TransplantationSame topicTransplantation: Methods and OutcomesFrench-language works237,207