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Record W2122153475 · doi:10.1056/nejmoa1401177

Transplantation Outcomes for Severe Combined Immunodeficiency, 2000–2009

2014· article· en· W2122153475 on OpenAlexaff
Sung‐Yun Pai, Brent R. Logan, Linda M. Griffith, Rebecca H. Buckley, Roberta Parrott, Christopher C. Dvorak, Neena Kapoor, I. Celine Hanson, Alexandra H. Filipovich, Soma Jyonouchi, Kathleen E. Sullivan, Trudy N. Small, Lauri M. Burroughs, Suzanne Skoda‐Smith, Ann E. Haight, Audrey Grizzle, Michael A. Pulsipher, Ka Wah Chan, Ramsay Fuleihan, Élie Haddad, Brett Loechelt, Victor M. Aquino, Alfred P. Gillio, Jeffrey Davis, Alan P. Knutsen, Angela R. Smith, Theodore B. Moore, Marlis L. Schroeder, Frederick D. Goldman, James A. Connelly, Matthew H. Porteus, Qun Xiang, William T. Shearer, Thomas A. Fleisher, Donald B. Kohn, Jennifer M. Puck, Luigi D. Notarangelo, Morton J. Cowan, Richard J. O’Reilly

Bibliographic record

VenueNew England Journal of Medicine · 2014
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsBC Children's HospitalUniversité de MontréalUniversity of ManitobaCentre Hospitalier Universitaire Sainte-Justine
FundersNational Institute of Allergy and Infectious DiseasesNational Cancer InstituteNational Heart, Lung, and Blood Institute
KeywordsMedicineSevere combined immunodeficiencyTransplantationSiblingImmunodeficiencyHematopoietic stem cell transplantationImmunologyPediatricsT cellImmune systemInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The Primary Immune Deficiency Treatment Consortium was formed to analyze the results of hematopoietic-cell transplantation in children with severe combined immunodeficiency (SCID) and other primary immunodeficiencies. Factors associated with a good transplantation outcome need to be identified in order to design safer and more effective curative therapy, particularly for children with SCID diagnosed at birth. METHODS: We collected data retrospectively from 240 infants with SCID who had received transplants at 25 centers during a 10-year period (2000 through 2009). RESULTS: Survival at 5 years, freedom from immunoglobulin substitution, and CD3+ T-cell and IgA recovery were more likely among recipients of grafts from matched sibling donors than among recipients of grafts from alternative donors. However, the survival rate was high regardless of donor type among infants who received transplants at 3.5 months of age or younger (94%) and among older infants without prior infection (90%) or with infection that had resolved (82%). Among actively infected infants without a matched sibling donor, survival was best among recipients of haploidentical T-cell-depleted transplants in the absence of any pretransplantation conditioning. Among survivors, reduced-intensity or myeloablative pretransplantation conditioning was associated with an increased likelihood of a CD3+ T-cell count of more than 1000 per cubic millimeter, freedom from immunoglobulin substitution, and IgA recovery but did not significantly affect CD4+ T-cell recovery or recovery of phytohemagglutinin-induced T-cell proliferation. The genetic subtype of SCID affected the quality of CD3+ T-cell recovery but not survival. CONCLUSIONS: Transplants from donors other than matched siblings were associated with excellent survival among infants with SCID identified before the onset of infection. All available graft sources are expected to lead to excellent survival among asymptomatic infants. (Funded by the National Institute of Allergy and Infectious Diseases and others.).

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.241
Teacher spread0.232 · 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

Citations771
Published2014
Admission routes1
Has abstractyes

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