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Record W1769201899

IS O REALLY THE UNIVERSAL DONOR

2015· dissertation· en· W1769201899 on OpenAlexfundno aff
Rebecca Barty

Bibliographic record

VenueMacSphere (McMaster University) · 2015
Typedissertation
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsnot available
FundersHealth CanadaCanadian Blood ServicesMcMaster University
KeywordsComputer science
DOInot available

Abstract

fetched live from OpenAlex

An association between compatible but ABO non-identical red blood cell (RBC) transfusions and increased in-hospital mortality was identified in an observational study. A review of the literature was performed to explore plausible biological mechanisms and inflammation was chosen. This thesis describes a body of work that was performed to develop a PICOT research question and design a pilot feasibility randomized crossover trial in patients with myelodysplastic syndrome (MDS) to determine whether there is evidence of an inflammatory response resulting from transfusion of ABO non-identical RBCs compared with the transfusion of ABO identical RBCs. The work undertaken as part of this thesis included: identifying a theoretical framework to guide the selection of outcome measures that would detect inflammation; identifying an appropriate and feasible population to study; designing the feasibility pilot study to answer the research question that was developed; and a discussion of ethical issues that were considered as the design of the pilot study was developed. The work that was done to develop the elements of PICOT resulted in the following research question: Is it feasible to perform a randomized crossover trial in chronically transfused blood group A patients with myelodysplastic syndrome (MDS), that looks for laboratory evidence of inflammation (in vitro biomarkers measured at baseline and pre-specified times between 1 and 96 hours post transfusion), following the transfusion of group O RBCs (ABO non-identical) compared to transfusion of group A (ABO identical) RBCs?

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.901
Threshold uncertainty score1.000

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0540.000

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 head0.015
GPT teacher head0.226
Teacher spread0.211 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2015
Admission routes1
Has abstractyes

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