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Record W4309159596 · doi:10.1111/petr.14393

Clinical approach to acute cellular rejection from the pediatric heart transplant society

2022· article· en· W4309159596 on OpenAlexaff
Neha Bansal, Melanie D. Everitt, Deipanjan Nandi, Joseph A. Spinner, Jennifer Conway, Defne Magnetta, E. Profita, Madeleine Townsend, Juan Alejos, Shriprasad R. Deshpande

Bibliographic record

VenuePediatric Transplantation · 2022
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsStollery Children's HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicineImmunosuppressionAsymptomaticIntensive care medicineHeart transplantationHeart transplantsTransplantationGraft rejectionComplicationSurgeryImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Early detection of cardiac allograft rejection is crucial for post-transplant graft survival. Despite the progress made in immunosuppression strategies, acute cellular rejection remains a serious complication during and after the first post-transplant year, and there is a continued lack of consensus regarding its treatment, especially in pediatric transplant patients. METHODS: An open request was placed via the listserv to the membership of the Pediatric Heart Transplant Society (PHTS). Along with a broad literature search, numerous institutional protocols were pooled, analyzed and consolidated. A clinical approach document was generated highlighting areas of consensus and practice variation. RESULTS: The clinical approach document divides cellular rejection by International Society for Heart and Lung Transplantation grades and provides management strategies for each, including persistent cellular rejection. CONCLUSIONS: Cellular rejection treatment can be tailored to the clinical status, graft function, and the grade of cellular rejection. A case of mild and asymptomatic rejection may not require treatment, whereas a higher-grade rejection or rejection with graft dysfunction or hemodynamic compromise may require aggressive intravenous therapies, changes to maintenance immunosuppression therapy and augmented surveillance.

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 score0.078
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.037
GPT teacher head0.323
Teacher spread0.286 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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