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Record W2084093283 · doi:10.1542/peds.2007-3415

Clinical and Genetic Analysis of Unclassifiable Inherited Bone Marrow Failure Syndromes

2008· article· en· W2084093283 on OpenAlexaffabout
Juliana Teo, Robert J. Klaassen, Conrad V. Fernandez, Rochelle Yanofsky, John K. Wu, Josette Champagne, Mariana Silva, Jeffrey H. Lipton, Jossee Brossard, Yvan Samson, Sharon Abish, MacGregor Steele, Kaiser Ali, Uma H. Athale, Lawrence Jardine, John P. Hand, Elena Tsangaris, Isaac Odame, Joseph Beyene, Yigal Dror

Bibliographic record

VenuePEDIATRICS · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBlood disorders and treatments
Canadian institutionsJaneway Children's Health and Rehabilitation CentreMcMaster UniversityMcMaster Children's HospitalCentre Hospitalier Universitaire de SherbrookeQueen's UniversityHealth Sciences CentreCancerCare ManitobaPopulation Health Research InstituteChildren's Hospital of Western OntarioChildren's Hospital of Eastern OntarioBC Children's HospitalMontreal Children's HospitalUniversity of TorontoSickKids FoundationCentre hospitalier universitaire de QuébecAlberta Children's HospitalIzaak Walton Killam Health CentreUniversity of SaskatchewanHospital for Sick Children
FundersCSIR-Central Institute of Mining and Fuel Research
KeywordsMedicineBone marrow failureBone marrowCytopeniaAplastic anemiaBone marrow examinationPathologyInternal medicineHaematopoiesisGeneticsStem cell

Abstract

fetched live from OpenAlex

OBJECTIVE: Unclassified inherited bone marrow failure syndromes are a heterogeneous group of genetic disorders that represent either new syndromes or atypical clinical courses of known inherited bone marrow failure syndromes. The relative prevalence of the unclassified inherited bone marrow failure syndromes and their characteristics and the clinical and economic challenges that they create have never been studied. METHODS: We analyzed cases of inherited bone marrow failure syndrome in the Canadian Inherited Marrow Failure Registry that were deemed unclassifiable at study entry. RESULTS: From October 2001 to March 2006, 39 of the 162 patients enrolled in the Canadian Inherited Marrow Failure Registry were registered as having unclassified inherited bone marrow failure syndromes. These patients presented at a significantly older age (median: 9 months) than the patients with classified inherited bone marrow failure syndrome (median: 1 month) and had substantial variation in the clinical presentations. The hematologic phenotype, however, was similar to the classified inherited bone marrow failure syndromes and included single- or multiple-lineage cytopenia, severe aplastic anemia, myelodysplasia, and malignancy. Grouping patients according to the affected blood cell lineage(s) and to the presence of associated physical malformations was not always sufficient to characterize a condition, because affected members from several families fit into different phenotypic groups. Compared with the classified inherited bone marrow failure syndromes, the patients with unclassified inherited bone marrow failure syndromes had 3.2 more specific diagnostic tests at 4.5 times higher cost per evaluated patient to attempt to categorize their syndrome. At last follow-up, only 20% of the unclassified inherited bone marrow failure syndromes were ultimately diagnosed with a specific syndrome on the basis of the development of new clinical findings or positive genetic tests. CONCLUSIONS: Unclassified inherited bone marrow failure syndromes are relatively common among the inherited bone marrow failure syndromes and present a major diagnostic and therapeutic dilemma.

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)0.003
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 score0.221
Threshold uncertainty score0.439

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.263
Teacher spread0.245 · 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".

Quick stats

Citations44
Published2008
Admission routes2
Has abstractyes

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