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Record W4416087587 · doi:10.1177/22143602251391258

Onasemnogene abeparvovec gene therapy for treatment of patients with spinal muscular atrophy: Updated real-world practical considerations

2025· review· en· W4416087587 on OpenAlexaff
Crystal M. Proud, Elizabeth Kichula, Susan Matesanz, Ashutosh Kumar, Kayoko Saito, Chamindra G. Laverty, Michelle A. Farrar, Diana Bharucha‐Goebel, Jana Haberlová, Vivek Mundada, Jennifer M. Kwon, Hugh J. McMillan

Bibliographic record

VenueJournal of Neuromuscular Diseases · 2025
Typereview
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsSpinal muscular atrophySMA*Neuromuscular diseaseGenetic enhancementClinical trialDiseaseMotor neuronDosing

Abstract

fetched live from OpenAlex

Spinal muscular atrophy (SMA) is an autosomal recessive neuromuscular disease resulting from biallelic pathogenic variants of the survival motor neuron 1 ( SMN1 ) gene that leads to motor neuron degeneration, progressive muscle atrophy, and weakness. In its most severe form and without timely initiation of treatment, SMA can be fatal or lead to a requirement for permanent ventilation by 2 years of age. Approved treatments for SMA target an increase in SMN protein production. These include nusinersen and risdiplam, which modify splicing of the SMN2 pre-mRNA, and onasemnogene abeparvovec, a viral-mediated gene therapy. In 2020, an expert panel provided recommendations and practical considerations regarding onasemnogene abeparvovec administration. As more countries have approved onasemnogene abeparvovec and new data have emerged from clinical trials and real-world use, a similar expert panel provides updated recommendations along with additional guidance. Specific recommendations are centered around family preparation prior to and immediately following dosing to minimize risk of infectious illness, timing of anti–adeno-associated virus serotype 9 antibody titer testing for those patients with exclusionary titers, modifying immunization schedules, avoiding potential complications with long-term corticosteroid administration, safety monitoring, considerations for combination therapy, implementing newborn screening, and emphasizing the need for ongoing multidisciplinary care and adherence to standard-of-care guidelines.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.910
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.062
GPT teacher head0.404
Teacher spread0.342 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2025
Admission routes1
Has abstractyes

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