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Record W4390545916 · doi:10.1016/j.blre.2023.101165

Αlpha-thalassemia: A practical overview

2024· review· en· W4390545916 on OpenAlexaff
Khaled M. Musallam, Maria Domenica Cappellini, Thomas D. Coates, Kevin H.M. Kuo, Hanny Al‐Samkari, Sujit Sheth, Vip Viprakasit, Alì Taher

Bibliographic record

VenueBlood Reviews · 2024
Typereview
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsUniversity of Toronto
FundersAgios Pharmaceuticals
KeywordsIneffective erythropoiesisThalassemiaMedicineAnemiaErythropoiesisDiseaseHemolytic anemiaTransfusion therapyBlood transfusionChelation therapyHematologySickle cell anemiaAnemia of chronic diseaseIntensive care medicineImmunologyInternal medicineHepcidin

Abstract

fetched live from OpenAlex

α-Thalassemia is an inherited blood disorder characterized by decreased synthesis of α-globin chains that results in an imbalance of α and β globin and thus varying degrees of ineffective erythropoiesis, decreased red blood cell (RBC) survival, chronic hemolytic anemia, and subsequent comorbidities. Clinical presentation varies depending on the genotype, ranging from a silent or mild carrier state to severe, transfusion-dependent or lethal disease. Management of patients with α-thalassemia is primarily supportive, addressing either symptoms (eg, RBC transfusions for anemia), complications of the disease, or its transfusion-dependence (eg, chelation therapy for iron overload). Several novel therapies are also in development, including curative gene manipulation techniques and disease modifying agents that target ineffective erythropoiesis and chronic hemolytic anemia. This review of α-thalassemia and its various manifestations provides practical information for clinicians who practice beyond those regions where it is found with high frequency.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.128
GPT teacher head0.436
Teacher spread0.308 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations74
Published2024
Admission routes1
Has abstractyes

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