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Record W2001351900 · doi:10.1196/annals.1345.031

Single and Combination Drug Therapy for Fetal Hemoglobin Augmentation in Hemoglobin E‐β<sup>0</sup>‐Thalassemia: Considerations for Treatment

2005· article· en· W2001351900 on OpenAlexaff
Sylvia T. Singer, Frans A. Kuypers, Nancy F. Olivieri, D. J. Weatherall, Robert Mignacca, Thomas D. Coates, Sally C. Davies, Nancy Sweeters, Elliott Vichinsky

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2005
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsUniversity of Toronto
FundersNational Center for Research ResourcesNational Heart, Lung, and Blood Institute
KeywordsFetal hemoglobinThalassemiaHemoglobinHemoglobinopathyMedicineDrugHemoglobin ABeta thalassemiaHemoglobin A2FetusInternal medicinePharmacologyHemolytic anemiaPregnancyBiologyGenetics

Abstract

fetched live from OpenAlex

Patients with hemoglobin E (Hb E)-beta 0-thalassemia, one of the most common hemoglobinopathies worldwide, could benefit from drugs that increase fetal and total hemoglobin levels and thereby decrease the need for transfusions. The long-term clinical outcome of such therapy, its hematologic effects, and which patients are likely to benefit from treatment are unknown. Consequently, the use of such drugs for Hb E-beta 0-thalassemia is limited, and countries where resources for safe and regular transfusion are scarce cannot benefit from them. In a multicenter trial of 42 patients treated with hydroxyurea for two years, almost half the patients demonstrated a significant increase in steady-state hemoglobin level. Drug toxicity was minimal. Combined treatment of hydroxyurea with erythropoietin benefited selected patients, but the addition of sodium phenyl butyrate was ineffective. After 5 years of follow-up, a subset of patients remained off transfusions. Hydroxyurea should be considered for a subset of Hb E-beta 0-thalassemia patients.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.073
GPT teacher head0.340
Teacher spread0.266 · 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 designBench or experimental
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

Citations14
Published2005
Admission routes1
Has abstractyes

Explore more

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