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Record W2559834900 · doi:10.1186/s13223-016-0169-2

Comprehensive genetic testing for primary immunodeficiency disorders in a tertiary hospital: 10-year experience in Auckland, New Zealand

2016· article· en· W2559834900 on OpenAlexvenueno aff
See‐Tarn Woon, Rohan Ameratunga

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsnot available
FundersAuckland District Health Board
KeywordsPrimary immunodeficiencyMedical diagnosisMedicineGenetic testingPediatricsGenetic heterogeneityPopulationImmunodeficiencyGenetic counselingLocus (genetics)ImmunologyInternal medicineImmune systemGeneticsPathologyBiologyGenePhenotype

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: New Zealand is a developed geographically isolated country in the South Pacific with a population of 4.4 million. Genetic diagnosis is the standard of care for most patients with primary immunodeficiency disorders (PIDs). METHODS: Since 2005, we have offered a comprehensive genetic testing service for PIDs and other immune-related disorders with a published sequence. Here we present results for this program, over the first decade, between 2005 and 2014. RESULTS: We undertook testing in 228 index cases and 32 carriers during this time. The three most common test requests were for X-linked lymphoproliferative (XLP), tumour necrosis factor receptor associated periodic syndrome (TRAPS) and haemophagocytic lymphohistiocytosis (HLH). Of the 32 suspected XLP cases, positive diagnoses were established in only 2 patients. In contrast, genetic defects in 8 of 11 patients with suspected X-linked agammaglobulinemia (XLA) were confirmed. Most XLA patients were initially identified from absence of B cells. Overall, positive diagnoses were made in about 23% of all tests requested. The diagnostic rate was lowest for several conditions with locus heterogeneity. CONCLUSIONS: Thorough clinical characterisation of patients can assist in prioritising which genes should be tested. The clinician-driven customised comprehensive genetic service has worked effectively for New Zealand. Next generation sequencing will play an increasing role in disorders with locus heterogeneity.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.275
Teacher spread0.260 · 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 teacher head, not a consensus.

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

Citations13
Published2016
Admission routes1
Has abstractyes

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