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The use of stimulated granulocyte transfusions to prevent recurrence of past severe infections after allogeneic stem cell transplantation

2003· article· en· W1980318916 on OpenAlexfundno aff
Jonathan P. Kerr, Effie Liakopolou, J Brown, Jacqueline Cornish, David Fleming, Edwin Massey, A Oakhill, Derwood Pamphilon, Stephen Robinson, April Totem, Alexandra M. P. I. Valencia, David I. Marks

Bibliographic record

VenueBritish Journal of Haematology · 2003
Typearticle
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsnot available
FundersHospital for Sick Children
KeywordsMedicineNeutropeniaGranulocyteTransplantationSurgeryAspergillosisIncidence (geometry)Granulocyte colony-stimulating factorInternal medicineAutologous stem-cell transplantationStem cellHematopoietic stem cell transplantationChemotherapyToxicityGastroenterologyImmunology

Abstract

fetched live from OpenAlex

The predictable neutropenia that follows allogeneic stem cell transplantation (ASCT) may be associated with recurrence of previous life-threatening infection. We describe nine patients with either previous invasive aspergillosis (IA) or considered to be at high risk of developing IA who underwent ASCT with prophylactic granulocyte transfusions. The study group, when compared with a control group, had a significant reduction in the incidence and duration of fevers (P < 0.05) and maximum C-reactive protein (P < 0.05). There were significantly fewer days of neutropenia (P < 0.05). There was also radiological improvement of pulmonary infiltrates in four out of seven assessable patients. No serious toxicity was encountered in donors or recipients. We conclude that prophylactic granulocyte donations can be given safely, and that they significantly reduce the number of days of neutropenia. Further investigation is warranted to determine whether granulocyte donations can prevent the recurrence of IA in patients at risk of fungal infection.

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 score0.141
Threshold uncertainty score0.308

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 head0.022
GPT teacher head0.263
Teacher spread0.241 · 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

Citations63
Published2003
Admission routes1
Has abstractyes

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