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Record W2100083745 · doi:10.1002/ajh.24089

Liver iron concentration measurements by MRI in chronically transfused children with sickle cell anemia: baseline results from the TWiTCH trial

2015· article· en· W2100083745 on OpenAlexaff
John C. Wood, Sara Pressel, Zora R. Rogers, Isaac Odame, Janet L. Kwiatkowski, Margaret T. Lee, William Owen, Alan R. Cohen, Timothy G. St. Pierre, Matthew M. Heeney, William H. Schultz, Barry R. Davis, Russell E. Ware

Bibliographic record

VenueAmerican Journal of Hematology · 2015
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsUniversity of Toronto
FundersNational Center for Advancing Translational SciencesNational Heart, Lung, and Blood Institute
KeywordsMedicineMagnetic resonance imagingAnemiaSickle cell anemiaTranscranial DopplerStroke (engine)Clinical trialInternal medicineRadiology

Abstract

fetched live from OpenAlex

Noninvasive, quantitative, and accurate assessment of liver iron concentration (LIC) by MRI is useful for patients receiving transfusions, but R2 and R2* MRI techniques have not been systematically compared in sickle cell anemia (SCA). We report baseline LIC results from the TWiTCH trial, which compares hydroxyurea with blood transfusion treatment for primary stroke prophylaxis assessed by transcranial Doppler sonography in pediatric SCA patients. Liver R2 was collected and processed using a FDA-approved commercial process (FerriScan®), while liver R2* quality control and processing were performed by a Core Laboratory blinded to clinical site and patient data. Baseline LIC studies using both MRI techniques were available for 120 participants. LICR2* and LICR2 results were highly correlated (r(2) = 0.93). A proportional bias of LIC(R2*)/LIC(R2), decreasing with average LIC, was observed. Systematic differences between LICR2* and LICR2 were also observed by MRI manufacturer. Importantly, LICR2* and LICR2 estimates had broad 95% limits of agreement with respect to each other. We recommend LICR2 and LICR2* not be used interchangeably in SCA patients to follow individual patient trends in iron burden.

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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score0.352

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 integrity0.0000.001
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 head0.014
GPT teacher head0.243
Teacher spread0.229 · 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 designRandomized trial
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

Citations24
Published2015
Admission routes1
Has abstractyes

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