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Record W4310099962 · doi:10.1016/j.jaci.2022.10.022

The diagnosis of severe combined immunodeficiency (SCID): The Primary Immune Deficiency Treatment Consortium (PIDTC) 2022 Definitions

2022· article· en· W4310099962 on OpenAlexaff
Christopher C. Dvorak, Élie Haddad, Jennifer Heimall, Elizabeth Dunn, Rebecca H. Buckley, Donald B. Kohn, Morton J. Cowan, Sung‐Yun Pai, Linda M. Griffith, Geoff D.E. Cuvelier, Hesham Eissa, Ami J. Shah, Richard J. O’Reilly, Michael A. Pulsipher, Nicola Wright, Roshini S. Abraham, Lisa Forbes Satter, Luigi D. Notarangelo, Jennifer M. Puck

Bibliographic record

VenueJournal of Allergy and Clinical Immunology · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsAlberta Children's HospitalCancerCare ManitobaUniversity of CalgaryUniversité de MontréalUniversity of ManitobaCentre Hospitalier Universitaire Sainte-Justine
FundersNHLBI Division of Intramural ResearchNational Institute of Neurological Disorders and StrokeNational Institute of Allergy and Infectious DiseasesNational Heart, Lung, and Blood InstituteOffice of Naval ResearchNational Center for Advancing Translational SciencesHealth Resources and Services AdministrationSt. Baldrick's FoundationCSL BehringCalifornia Institute of Regenerative MedicineInvitaeNational Cancer InstituteU.S. Department of Health and Human ServicesNational Institutes of HealthGrifols
KeywordsSevere combined immunodeficiencyPrimary immunodeficiencyImmunologyImmune systemT cellHepatosplenomegalyMedicineImmunodeficiencyStem cellGenetic enhancementBiologyPathology

Abstract

fetched live from OpenAlex

Severe combined immunodeficiency (SCID) results from defects in the differentiation of hematopoietic stem cells into mature T lymphocytes, with additional lymphoid lineages affected in particular genotypes. In 2014, the Primary Immune Deficiency Treatment Consortium published criteria for diagnosing SCID, which are now revised to incorporate contemporary approaches. Patients with typical SCID must have less than 0.05 × 10 9 autologous T cells/L on repetitive testing, with either pathogenic variant(s) in a SCID-associated gene, very low/undetectable T-cell receptor excision circles or less than 20% of CD4 T cells expressing naive markers, and/or transplacental maternally engrafted T cells. Patients with less profoundly impaired autologous T-cell differentiation are designated as having leaky/atypical SCID, with 2 or more of these: low T-cell numbers, oligoclonal T cells, low T-cell receptor excision circles, and less than 20% of CD4 T cells expressing naive markers. These patients must also have either pathogenic variant(s) in a SCID-associated gene or reduced T-cell proliferation to certain mitogens. Omenn syndrome requires a generalized erythematous rash, absent transplacentally acquired maternal engraftment, and 2 or more of these: eosinophilia, elevated IgE, lymphadenopathy, hepatosplenomegaly. Thymic stromal defects and other causes of secondary T-cell deficiency are excluded from the definition of SCID. Application of these revised Primary Immune Deficiency Treatment Consortium 2022 Definitions permits precise categorization of patients with T-cell defects but does not imply a preferred treatment strategy.

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)0.003
metaresearch head score (Gemma)0.005
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.024
GPT teacher head0.268
Teacher spread0.244 · 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
GenreMethods

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

Citations125
Published2022
Admission routes1
Has abstractyes

Explore more

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