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Record W2767327591 · doi:10.3233/jnd-170280

Clinical Outcomes in Duchenne Muscular Dystrophy: A Study of 5345 Patients from the TREAT-NMD DMD Global Database

2017· article· en· W2767327591 on OpenAlexaff
Zaïda Koeks, Catherine L. Bladen, David Salgado, Erik W. van Zwet, Oksana Pogoryelova, Grace McMacken, Soledad Monges, María Eugenia Foncuberta, Kyriaki Kekou, Konstantina Kosma, Hugh Dawkins, Leanne Lamont, M. Bellgard, Anna J. Roy, Teodora Chamova, Velina Guergueltcheva, H.S. Chan, Lawrence Korngut, Craig Campbell, Yi Dai, Jen Wang, Nina Barišić, Petr Brabec, Jaana Lähdetie, Maggie C. Walter, Olivia Schreiber‐Katz, Veronika Karcagi, Ágnes Herczegfalvi, Venkatarman Viswanathan, Farhad Bayat, Filippo Buccella, Alessandra Ferlini, En Kimura, J.C. van den Bergen, Miriam Rodrigues, Richard Roxburgh, Anna Łusakowska, Anna Kostera‐Pruszczyk, Rosário Santos, Elena Neagu, Svetlana Artemieva, Vedrana Milić Rašić, Dina Vojinović, Manuel Posada de la Paz, Clemens Bloetzer, Andrea Klein, Jordi Díaz‐Manera, Eduard Gallardo, Aynur Ayşe Karaduman, Tunca Oznur, Haluk Topaloğlu, Rasha El Sherif, Angela Stringer, Andriy Shatillo, Ann Martin, Holly L. Peay, Janbernd Kirschner, Kevin M. Flanigan, Volker Straub, Kate Bushby, Christophe Béroud, Jan J.G.M. Verschuuren, Hanns Lochmüller

Bibliographic record

VenueJournal of Neuromuscular Diseases · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsWestern UniversitySouth Health CampusUniversity of Calgary
FundersMedical Research CouncilEuropean Commission
KeywordsDuchenne muscular dystrophyMedicineMuscular dystrophyPediatricsInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Recent short-term clinical trials in patients with Duchenne Muscular Dystrophy (DMD) have indicated greater disease variability in terms of progression than expected. In addition, as average life-expectancy increases, reliable data is required on clinical progression in the older DMD population. OBJECTIVE: To determine the effects of corticosteroids on major clinical outcomes of DMD in a large multinational cohort of genetically confirmed DMD patients. METHODS: In this cross-sectional study we analysed clinical data from 5345 genetically confirmed DMD patients from 31 countries held within the TREAT-NMD global DMD database. For analysis patients were categorised by corticosteroid background and further stratified by age. RESULTS: Loss of ambulation in non-steroid treated patients was 10 years and in corticosteroid treated patients 13 years old (p = 0.0001). Corticosteroid treated patients were less likely to need scoliosis surgery (p < 0.001) or ventilatory support (p < 0.001) and there was a mild cardioprotective effect of corticosteroids in the patient population aged 20 years and older (p = 0.0035). Patients with a single deletion of exon 45 showed an increased survival in contrast to other single exon deletions. CONCLUSIONS: This study provides data on clinical outcomes of DMD across many healthcare settings and including a sizeable cohort of older patients. Our data confirm the benefits of corticosteroid treatment on ambulation, need for scoliosis surgery, ventilation and, to a lesser extent, cardiomyopathy. This study underlines the importance of data collection via patient registries and the critical role of multi-centre collaboration in the rare disease field.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.330
Teacher spread0.309 · 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

Citations182
Published2017
Admission routes1
Has abstractyes

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