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Record W2802781269 · doi:10.1111/ajt.14876

Pediatric heart transplantation across a positive crossmatch: First year results from the CTOTC-04 multi-institutional study

2018· article· en· W2802781269 on OpenAlexaff
Steven A. Webber, Adriana Zeevi, Kristen Mason, Linda J. Addonizio, Elizabeth D. Blume, Anne I. Dipchand, Robert E. Shaddy, Brian Feingold, Charles E. Canter, Daphne T. Hsu, William T. Mahle, Brian Armstrong, Yvonne Morrison, David Iklé, Helena Diop, Jonah Odim

Bibliographic record

VenueAmerican Journal of Transplantation · 2018
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsHospital for Sick Children
FundersNational Institute of Allergy and Infectious Diseases
KeywordsMedicineImmunosuppressionPanel reactive antibodyClinical endpointIncidence (geometry)Donor specific antibodiesTransplantationHeart transplantationInternal medicineSensitizationSurgeryGastroenterologyUrologyImmunologyKidney transplantationClinical trial

Abstract

fetched live from OpenAlex

Sensitization is common in pediatric heart transplant candidates and waitlist mortality is high. Transplantation across a positive crossmatch may reduce wait time, but is considered high risk. We prospectively recruited consecutive candidates at eight North American centers. At transplantation, subjects were categorized as nonsensitized or sensitized (presence of ≥1 HLA antibody with MFI ≥1000 using single antigen beads). Sensitized subjects were further classified as complement-dependent cytotoxicity crossmatch (CDC-crossmatch) positive or negative and as donor-specific antibodies (DSA) positive or negative. Immunosuppression was standardized. CDC-crossmatch–positive subjects also received perioperative antibody removal, maintenance corticosteroids, and intravenous immunoglobulin. The primary endpoint was the 1 year incidence rate of a composite of death, retransplantation, or rejection with hemodynamic compromise. 317 subjects were screened, 290 enrolled and 240 transplanted (51 with pretransplant DSA, 11 with positive CDC-crossmatch). The incidence rates of the primary endpoint did not differ statistically between groups; nonsensitized 6.7% (CI: 2.7%, 13.3%), sensitized crossmatch positive 18.2% (CI: 2.3%, 51.8%), sensitized crossmatch negative 10.7% (CI: 5.7%, 18.0%), P = .2354. The primary endpoint also did not differ by DSA status. Freedom from antibody-mediated and cellular rejection was lower in the crossmatch positive group and/or in the presence of DSA. Follow-up will determine if acceptable outcomes can be achieved long-term. Sensitization is common in pediatric heart transplant candidates and waitlist mortality is high. Transplantation across a positive crossmatch may reduce wait time, but is considered high risk. We prospectively recruited consecutive candidates at eight North American centers. At transplantation, subjects were categorized as nonsensitized or sensitized (presence of ≥1 HLA antibody with MFI ≥1000 using single antigen beads). Sensitized subjects were further classified as complement-dependent cytotoxicity crossmatch (CDC-crossmatch) positive or negative and as donor-specific antibodies (DSA) positive or negative. Immunosuppression was standardized. CDC-crossmatch–positive subjects also received perioperative antibody removal, maintenance corticosteroids, and intravenous immunoglobulin. The primary endpoint was the 1 year incidence rate of a composite of death, retransplantation, or rejection with hemodynamic compromise. 317 subjects were screened, 290 enrolled and 240 transplanted (51 with pretransplant DSA, 11 with positive CDC-crossmatch). The incidence rates of the primary endpoint did not differ statistically between groups; nonsensitized 6.7% (CI: 2.7%, 13.3%), sensitized crossmatch positive 18.2% (CI: 2.3%, 51.8%), sensitized crossmatch negative 10.7% (CI: 5.7%, 18.0%), P = .2354. The primary endpoint also did not differ by DSA status. Freedom from antibody-mediated and cellular rejection was lower in the crossmatch positive group and/or in the presence of DSA. Follow-up will determine if acceptable outcomes can be achieved long-term.

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 score0.132
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.031
GPT teacher head0.353
Teacher spread0.322 · 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".

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Citations49
Published2018
Admission routes1
Has abstractyes

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