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Record W4395033842 · doi:10.3233/jnd-230220

Predictors of Loss of Ambulation in Duchenne Muscular Dystrophy: A Systematic Review and Meta-Analysis

2024· review· en· W4395033842 on OpenAlexaffabout
Erik Landfeldt, Alicia Alemán, Sophia Abner, Rongrong Zhang, Christian Werner, Ioannis Tomazos, Nermina Ferizović, Hanns Lochmüller, Janbernd Kirschner

Bibliographic record

VenueJournal of Neuromuscular Diseases · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsOttawa HospitalChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsDuchenne muscular dystrophyMeta-analysisMedicinePhysical medicine and rehabilitationMuscular dystrophyPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

Objective: The objective of this study was to describe predictors of loss of ambulation in Duchenne muscular dystrophy (DMD). Methods: This systematic review and meta-analysis included searches of MEDLINE ALL, Embase, and the Cochrane Database of Systematic Reviews from January 1, 2000, to December 31, 2022, for predictors of loss of ambulation in DMD. Search terms included "Duchenne muscular dystrophy" as a Medical Subject Heading or free text term, in combination with variations of the term "predictor". Risk of bias was assessed using the Newcastle-Ottawa Scale. We performed meta-analysis pooling of hazard ratios of the effects of glucocorticoids (vs. no glucocorticoid therapy) by fitting a common-effect inverse-variance model. Results: The bibliographic searches resulted in the inclusion of 45 studies of children and adults with DMD from 17 countries across Europe, Asia, and North America. Glucocorticoid therapy was associated with delayed loss of ambulation (overall meta-analysis HR deflazacort/prednisone/prednisolone: 0.44 [95% CI: 0.40-0.48]) (n = 25 studies). Earlier onset of first signs or symptoms, earlier loss of developmental milestones, lower baseline 6MWT (i.e.,<350 vs. ≥350 metres and <330 vs. ≥330 metres), and lower baseline NSAA were associated with earlier loss of ambulation (n = 5 studies). Deletion of exons 3-7, proximal mutations (upstream intron 44), single exon 45 deletions, and mutations amenable of skipping exon 8, exon 44, and exon 53, were associated with prolonged ambulation; distal mutations (intron 44 and downstream), deletion of exons 49-50, and mutations amenable of skipping exon 45, and exon 51 were associated with earlier loss of ambulation (n = 13 studies). Specific single-nucleotide polymorphisms in CD40 gene rs1883832, LTBP4 gene rs10880, SPP1 gene rs2835709 and rs11730582, and TCTEX1D1 gene rs1060575 (n = 7 studies), as well as race/ethnicity and level of family/patient deprivation (n = 3 studies), were associated with loss of ambulation. Treatment with ataluren (n = 2 studies) and eteplirsen (n = 3 studies) were associated with prolonged ambulation. Magnetic resonance biomarkers (MRI and MRS) were identified as significant predictors of loss of ambulation (n = 6 studies). In total, 33% of studies exhibited some risk of bias. Conclusion: Our synthesis of predictors of loss of ambulation in DMD contributes to the understanding the natural history of disease and informs the design of new trials of novel therapies targeting this heavily burdened patient population.

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)0.017
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.042
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0220.044
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.312
Teacher spread0.285 · 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 designMeta-analysis
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

Citations19
Published2024
Admission routes2
Has abstractyes

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