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Record W4402940992 · doi:10.1186/s13023-024-03372-x

Predictors of cardiac disease in duchenne muscular dystrophy: a systematic review and evidence grading

2024· review· en· W4402940992 on OpenAlexafffund
Erik Landfeldt, Alberto Alemán, Sophia Abner, Rongrong Zhang, Christian Werner, Ioannis Tomazos, Hanns Lochmüller, Rosaline C. M. Quinlivan, Karim Wahbi

Bibliographic record

VenueOrphanet Journal of Rare Diseases · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsOttawa HospitalChildren's Hospital of Eastern OntarioUniversity of Ottawa
FundersCanadian Institutes of Health ResearchPTC TherapeuticsCanada Research ChairsCanada First Research Excellence FundEuropean CommissionGovernment of Canada
KeywordsMedicineEjection fractionInternal medicineCardiologyDuchenne muscular dystrophyCardiomyopathyHeart failure

Abstract

fetched live from OpenAlex

BACKGROUND: Duchenne muscular dystrophy (DMD) is a rare disease that causes progressive muscle degeneration resulting in life-threatening cardiac complications. The objective of this systematic literature review was to describe and grade the published evidence of predictors of cardiac disease in DMD. METHODS: The review encompassed searches of Embase, MEDLINE ALL, and the Cochrane Database of Systematic Reviews from January 1, 2000, to December 31, 2022, for predictors of cardiac disease in DMD. The certainty of evidence (i.e., very low to high) was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework. RESULTS: We included 33 publications encompassing 9,232 patients with DMD. We found moderate- to high-quality evidence that cardiac medication (i.e., ACE inhibitors [enalapril and perindopril], β-blockers [carvedilol], and mineralocorticoid receptor antagonists [eplerenone]) are significantly associated with preserved left ventricular ejection fraction (LVEF), left ventricular end-systolic volume (LVESV), and left ventricular circumferential strain (LVCS). DMD mutations in exons 51 and 52 were found to be significantly associated with lower risk of cardiomyopathy; deletions treatable by exon 53 skipping and mutations in the Dp116 coding region with improved LVEF and prolonged cardiac dysfunction-free survival; and exons 45-50 and 52 with early left ventricular systolic dysfunction (low/very low-quality evidence). We found high-quality evidence that glucocorticoids (deflazacort) are significantly associated with preserved LVEF and improved fractional shortening (FS), and low-quality evidence that glucocorticoids (deflazacort, prednisone, and/or prednisolone) are associated with improved ejection fraction (EF) and lower risk of cardiomyopathy, ventricular dysfunction, and heart failure-related mortality. Full-time mechanical ventilation was found to be significantly correlated with LVEF (low-quality evidence), muscle strength with FS (low-quality evidence), and genetic modifiers (i.e., LTBP4 rs10880 and ACTN3) with LVEF, lower risk of cardiomyopathy and left ventricular dilation (low-quality evidence). CONCLUSION: Several sources of cardiac disease heterogeneity are well-studied in patients with DMD. Yet, the certainty of evidence is generally low, and little is known of the contribution of non-pharmacological interventions, as well as the impact of different criteria for initiation of specific treatments. Our findings help raise awareness of prevailing unmet needs, shape expectations of treatment outcomes, and inform the design of future research.

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)0.022
metaresearch head score (Gemma)0.102
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.102
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0130.011
Bibliometrics0.0210.016
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.292
Teacher spread0.276 · 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 designSystematic review
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

Citations12
Published2024
Admission routes2
Has abstractyes

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