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A non‐invasive oral rinse assay predicts bone marrow engraftment and 6 months prognosis following allogeneic hematopoietic stem cell transplantation

2011· article· en· W1492942437 on OpenAlexafffund
Carol Forster, Guy M. Aboodi, Jeff H. Lipton, Michael Glogauer

Bibliographic record

VenueJournal of Oral Pathology and Medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicOral health in cancer treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsStem cellMedicineHematopoietic stem cell transplantationHaematopoiesisTransplantationBone marrowBone marrow transplantationHematopoietic cellHematopoietic stem cellPathologyImmunologyInternal medicineBiology

Abstract

fetched live from OpenAlex

BACKGROUND: We have previously shown in a pediatric Hematopoietic stem cell transplant (HSCT) population that a non-invasive oral rinse can be used to monitor engraftment, neutrophil tissue delivery and susceptibility to infection post-HSCT. METHODS: Using the same oral rinse protocol, we studied neutrophil tissue delivery kinetics and its relationship to clinical parameters and outcomes following HSCT in 29 adult patients. Oral neutrophil counts were compared to circulating neutrophil levels, oral mucositis scores and patient health status at 6 months post-HSCT. RESULTS: Neutrophils were detected on average 8.4 ± 3.4 SD days earlier in the oral tissues than in the blood circulation, enabling us to confirm successful engraftment more than one week earlier than when using blood neutrophil counts alone. As well, in this population the time-span between oral engraftment (OE) and blood engraftment (BE) was a consistent predictor of treatment outcome at 6 months following HSCT where a BE-OE of <6 days resulted in 100% of patients having a negative outcome. CONCLUSION: We conclude that monitoring the timing of neutrophil delivery to the oral tissues with a non-invasive oral rinse has the potential to allow the physician to identify those patients who are at a high risk of HSCT failure within just a few weeks of the initiation 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 score0.046
Threshold uncertainty score0.679

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.042
GPT teacher head0.303
Teacher spread0.261 · 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

Citations10
Published2011
Admission routes2
Has abstractyes

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