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Record W4389489734 · doi:10.1182/hematology.2023000425

Planning GvHD preemptive therapy: risk factors, biomarkers, and prognostic scores

2023· article· en· W4389489734 on OpenAlexaff
Jacob Rozmus, John E. Levine, Kirk R. Schultz

Bibliographic record

VenueHematology · 2023
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineGraft-versus-host diseaseHematopoietic cellHematopoietic stem cell transplantationBiomarkerIntensive care medicineDiseaseClinical trialOncologyTransplantationImmunologyInternal medicineHaematopoiesisStem cell

Abstract

fetched live from OpenAlex

Prevention of acute and chronic graft-versus-host disease (aGvHD and cGvHD) is an important objective of allogeneic hematopoietic cell transplantation (HCT). While there is has been significant progress in preventative approaches in the peritransplant period to minimize development of GvHD, no preventative approach has completely eliminated development of either aGvHD or cGvHD. Recently, posttransplant immune biomarker profiling early post-HCT by the Mount Sinai Acute GvHD International Consortium group has resulted in a validated risk assignment algorithm and development of preemptive approaches to decrease aGvHD and mortality in high-risk patients. cGvHD risk assignment algorithms have been developed based on measurements at day 100 and may be used for future preemptive intervention trials to minimize cGvHD. This article discusses the current state of the art in aGvHD and cGvHD preemptive algorithms and therapeutic interventions and what is needed to move these into validated approaches.

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)0.000
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 score0.010
Threshold uncertainty score0.512

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.041
GPT teacher head0.306
Teacher spread0.265 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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