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Record W2894562426 · doi:10.1111/ctr.13416

De novo donor‐specific HLA antibodies in heart transplantation: Do transient de novo DSA confer the same risk as persistent de novo DSA?

2018· article· en· W2894562426 on OpenAlexaffabout
Yasbanoo Moayedi, Chun‐Po Steve Fan, Kathryn Tinckam, Heather J. Ross, Jennifer A. McCaughan

Bibliographic record

VenueClinical Transplantation · 2018
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoTed Rogers Centre for Heart ResearchUniversity Health Network
Fundersnot available
KeywordsMedicineHeart transplantationHuman leukocyte antigenDonor specific antibodiesImmunosuppressionIncidence (geometry)TransplantationPopulationAntibodyInternal medicineImmunologyAntigen

Abstract

fetched live from OpenAlex

BACKGROUND: It is estimated that 25%-35% of heart transplant recipients develop de novo donor-specific antibodies (dnDSA). One factor that appears to play a role in clinical outcomes is DSA persistence. The objective of this study was to determine the incidence of transient and persistent dnDSA in a Canadian heart transplant population and to evaluate their impact on coronary allograft vasculopathy (CAV), graft function, and mortality. METHODS: A retrospective study of consecutive adult and transitioned pediatric heart transplant recipients (2008-2015) in Toronto was performed. Clinical demographics were collected prospectively. HLA antibody testing was performed using Luminex single antigen assays. In statistical analysis, dnDSA was modeled as a time dependent covariate. RESULTS: During a median follow-up of 4.1 years, dnDSA were detected in 42 (23%) with a median time to detection of 329 days (156-740); 27 (64%) developed persistent dnDSA. Persistent dnDSA conferred an increased risk of death with a HR 4.0 (95%CI 1.4-12.1) when adjusted recipient age, CAV, and cytomegalovirus status. CONCLUSIONS: Transient dnDSA were not associated with adverse outcomes after heart transplantation. This suggests that transient dnDSA may not require enhanced immunosuppression, increased HLA antibody monitoring, or additional physiological assessment. By knowing the transient dnDSA status, clinicians may minimize both recipient morbidity and cost without increasing harm.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.078
GPT teacher head0.405
Teacher spread0.327 · 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 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

Citations23
Published2018
Admission routes2
Has abstractyes

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