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Left Ventricular Function Declines with Increasing Myocardial Ferritin Iron in Thalassemia Major.

2005· article· en· W2550066585 on OpenAlexaff
Sujit Sheth, Haiying Tang, Jens H. Jensen, Karen Altmann, Ashwin Prakash, Beth F. Printz, Anthony L. Brown, Allan J. Hordof, Christina L. Tosti, Andjela Azabagic, Srirama V. Swaminathan, Truman R. Brown, Nancy F. Olivieri, Gary M. Brittenham

Bibliographic record

VenueBlood · 2005
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHemosiderinFerritinChemistryThalassemiaNuclear magnetic resonanceInternal medicineCardiologyMedicinePathologyBiochemistryPhysics

Abstract

fetched live from OpenAlex

Abstract Using a new magnetic resonance method that separately estimates the two principal forms of storage iron, ferritin and hemosiderin, in the heart, we examined the relationship between myocardial storage iron fractions and left ventricular function in thalassemia major. In patients with iron overload, the amount of iron in functional and transport pools changes only slightly. Virtually all of the excess is sequestered in storage forms of iron, as ferritin, a diffuse, soluble fraction, and as hemosiderin, an aggregate, insoluble fraction. The two storage forms of iron strongly affect signal intensity in both T2 and T2* weighted images but influence MRI signal decay through different means because of their differences in solubility and in intracellular distribution (Magn Reson Med2002; 47:1131–8). Separate estimates of the iron concentrations of the two forms of storage iron may be obtained by measuring two distinct relaxation parameters, the “ferritin iron index” (“reduced” transverse relaxation rate) RR2, and the “hemosiderin iron index”, A. We studied 14 patients with thalassemia major, all being treated with subcutaneous deferoxamine. Study participants were examined with a Philips 1.5 T Intera scanner using three Carr-Purcell-Meiboom-Gill (CPMG)-like multi-echo spin echo sequences with varied inter-echo times, using electrocardiographic triggering and respiratory navigator gating to estimate RR2 and A. The left ventricular shortening fraction was measured using standard echocardiographic methods. The Figure shows the relationship (R=0.91, p<0.0001) between the ferritin index, RR2, and the left ventricular shortening fraction. Figure Figure Overall, variation in the ferritin index explained more than 80% of the variation in ventricular function. For comparison, variation in the hemosiderin index, A, accounted for only about 33% of the variation in shortening fraction. Using an empirical calibration to estimate iron concentrations, variation in total (ferritin + hemosiderin) iron accounted for only about 40% of the variation in ventricular function. In patients with thalassemia major, the concentration of ferritin iron may provide a better indicator of the magnitude of the toxic iron pool than the total storage iron concentration. Magnetic resonance determinations of the partition of storage iron between ferritin and hemosiderin may be clinically valuable in evaluating tissue iron toxicity in patients with transfusional iron overload.

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 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 head0.214
Teacher spread0.209 · 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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