MétaCan
Menu
Back to cohort
Record W4383561170 · doi:10.14740/jh958

Sickle Cell Trait: Is It Always Benign?

2023· article· en· W4383561170 on OpenAlexvenueno aff
Tyiesha Brown, Rachaita Lakra, Samip Master, Poornima Ramadas

Bibliographic record

VenueJournal of Hematology · 2023
Typearticle
Languageen
FieldMedicine
TopicBone and Joint Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHemoglobinopathyHemoglobin electrophoresisAsymptomaticSickle cell traitSickle cell anemiaHemolysisDiseaseVaso-occlusive crisisInternal medicinePathologyAnemiaPediatricsSurgery

Abstract

fetched live from OpenAlex

Sickle cell disease is a well-known homozygous inherited hemoglobinopathy that causes vaso-occlusive phenomena and chronic hemolysis. Vaso-occlusion results in sickle cell crisis and can eventually lead to complications involving multiple organ systems. However, the heterozygous counterpart, sickle cell trait (SCT) has less clinical significance as these patients are generally asymptomatic. This case series examines three unrelated patients with SCT ranging from the age of 27 to 61 years, who presented with pain in multiple long bones. Hemoglobin electrophoresis confirmed a diagnosis of SCT. Radiographic images of the affected sites showed osteonecrosis (ON). Interventions included pain management and bilateral hip replacement in two of the patients. Historically, vaso-occlusive disease in patients with SCT with no evidence of hemolysis or other hallmark findings of sickle cell disease is rare. There are limited reported cases of ON in SCT patients. Clinicians should explore other hemoglobinopathies not tested on routine hemoglobin electrophoresis and alternative risk factors for ON in these 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 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)0.001
metaresearch head score (Gemma)0.012
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: Commentary · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.035
GPT teacher head0.312
Teacher spread0.277 · 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
GenreCommentary

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

Citations5
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of HematologySame topicBone and Joint DiseasesFrench-language works237,207