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Quantification by Magnetic Resonance Imaging (MRI) and Consequences of Post-Transfusionnal Iron Overload in Long Bone Marrow Transplant Survivors.

2005· article· en· W2559199601 on OpenAlexaff
Christian Rose, Olivier Ernst, B Hecquet, Pascale Renom, Marie Pierre Noel, Ibrahim Yakoub‐Agha, Emmanuelle Bourgeois, Nathalie Cambier, F Bauters, Jean Pierre Jouet

Bibliographic record

VenueBlood · 2005
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsMedicineGastroenterologyInternal medicineFerritinSiderosisPopulationLiver functionLiver function testsLiver diseaseTransplantation

Abstract

fetched live from OpenAlex

Abstract Introduction The exact biological and clinical complications related to iron overload in adult non thallassemic patients receiving blood units (BU) are not well known. This is mainly due to the many confounding factors both in the evaluation of iron overload (mainly estimated by ferritin measurement) and its consequences on liver dysfunction (hepatitis, GVH) and cardiac or pancreatic function (toxicity, ageing). Patients and Methods We prospectively evaluated biological (glycemia, liver function) and clinical (cardiomyopathy, arythmia) consequences of post-transfusionnal iron overload, as sole risk factors, in a very closely selected population of long term BM transplant survivors. We quantified liver iron content (LIC) by MRI and studied the relationship between the number of BU, LIC and liver dysfunction. Exclusion criteria were extremely strict: transplant performed after 1999, any form of GVH, hepatitis B or C, alcoholism (CAGE Questionnaire), any presence of hepatotoxic drug, requirement of BU after the one year period following transplant, inflammation, neoplastic diseases or relapse, homozygous for HFE mutation. Results 104/150 adult patients transplanted before December 1999 were enrolled. 39/104 were excluded: GVH n=11, viral hepatitis n=3, alcoholism n=1, hepatotoxic drug n=4, active bleeding n=2, neoplastic disease or relapse n=11, chronic inflammation n=7. 65 patients were analyzed (34M,31F). Median age at transplant was 36. Median follow up was 9 years. The median number of BU received was 18 (0–77) (definitive evaluation in 60/65 patients). The median ferritin was 532 ng/ml (42–4023). 27/65 pts had AST and or ALT above normal value. Hyperlycemia was present in 11 cases. There was a significant correlation between the number of BU and the ferritin value (r= 0.81) (p<10–3) as well as between the number of BU and LIC (r=0.84)(p<10–3).38/65 patients had ferritin above normal value; among them, 31/32 cases had LIC above normal value, median 117 micromoles/gdw (30->300). The group with ferritin above normal value (n=38) differed significantly from the group with ferritin of normal range in terms of number of BU transfused (p<10 −3), level of AST(p<0.017) and ALT (p<0.009). However, the risk of occurrence of liver dysfunction (AST or ALT above normal) was slightly different between the normal ferritin (8/27) and high ferritin (19/38) groups (chi 2 non-significant). In addition, in the group having received more than 20 BU (n=24) compared to the group having received less than 20 BU (n=36), there was no significant difference in the risk of occurrence of liver dysfunction but there was a significant difference between these two groups in terms of ferritin (p<10–3)(t-test) and LIC results (p=0.013)(t-test). There was no significant difference regarding glycemia. No patients had clinical cardiac disease or were arythmic. Conclusion The magnitude of persistent iron overload in long BM transplant survivors correlates closely to the number of BU received and is well quantified by MRI. In this group having no cofactor of iron toxicity, our results suggest that the impact in the medium term of post transfusionnal iron overload on liver dysfunction, diabetes mellitus and cardiac disease is moderate.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.005
GPT teacher head0.212
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2005
Admission routes1
Has abstractyes

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