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Record W4210585634 · doi:10.1002/ajmg.a.62672

Diagnostic outcomes for molecular genetic testing in children with suspected Ehlers–Danlos syndrome

2022· article· en· W4210585634 on OpenAlexaff
Nadirah Damseh, Lucie Dupuis, Constance M. O’Connor, Rachel Youjin Oh, Yi Wen Wang, Dimitri J. Stavropoulos, Sarah Schwartz, Roberto Mendoza‐Londono

Bibliographic record

VenueAmerican Journal of Medical Genetics Part A · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective tissue disorders research
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsEhlers–Danlos syndromeGenetic testingJoint hypermobilityMedicineExome sequencingCohortGenetic counselingGenetic heterogeneityInternal medicineGenetic diagnosisMolecular geneticsPediatricsDermatologyGeneticsPhysical therapyMutationBiologyPhenotypeGene

Abstract

fetched live from OpenAlex

Ehlers-Danlos syndrome (EDS) is a heterogeneous group of connective tissue disorders characterized by hyperextensible skin, hypermobile joints, easy bruisability, and fragility of the connective tissues. The diagnosis is based on clinical assessment and phenotype-guided genetic testing. Most EDS subtypes can be confirmed by genetic testing except for hypermobile EDS. This study explored the utility of applying the 2017 EDS classification criteria and molecular genetic testing in establishing an EDS diagnosis in children. In this retrospective study, we reviewed 72 patients referred to a tertiary care center for evaluation of EDS who underwent one or more forms of genetic testing. Eighteen patients (18/72, 25%) met the clinical criteria for one of the EDS subtypes and of these, 15 (15/18, 83%) were confirmed molecularly. Fifty-four patients (54/72, 75%) had features that overlapped EDS and other syndromes associated with joint hypermobility but did not fully meet clinical criteria. Twelve of them (12/54, 22%) were later shown to have a positive molecular genetic diagnosis of EDS. Different molecular genetic tests were performed on the cohort of 72 patients (EDS panel, n = 44; microarray, n = 25; whole exome sequencing [WES], n = 9; single gene sequencing, n = 3; familial variant testing, n = 10; other genetic panels n = 3). EDS panel was completed in 44 patients (61%), and a molecular diagnosis was confirmed in nine of the patients who satisfied criteria for one of the EDS subtypes (9/12, 75%) and in nine of the patients who did not fully meet criteria (9/32, 28%). We observed a correlation between generalized joint hypermobility, poor healing, easy bruising, atrophic scars, skin hyperextensibility, and developmental dysplasia of the hip with a positive molecular result. This study provides guidance for the use of molecular genetic testing in combination with the 2017 clinical diagnostic criteria in children presenting with EDS characteristics.

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)0.002
metaresearch head score (Gemma)0.019
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.013
GPT teacher head0.296
Teacher spread0.283 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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