Dyslipidemia in Muscular Dystrophy: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Muscular dystrophies (MDs) are characterized by chronic muscle wasting but also poorly understood metabolic co-morbidities. We have recently shown that Duchenne MD (DMD) patients, dogs and asymptomatic carriers are affected by a new form of dyslipidemia that may exacerbate muscle damage. OBJECTIVE: We aimed to perform a systematic review and meta-analysis for evidence that other types of MDs are associated with dyslipidemia compared to healthy controls. METHODS: Search was conducted using MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials for reports that compare plasma/serum lipids from MD patients and controls, and meta-analysis of cross-sectional studies quantifying total cholesterol, high-density lipoprotein, low density lipoprotein and triglycerides was performed. RESULTS: Out of 749 studies, 17 met our inclusion criteria for meta-analysis. 14 of the 17 studies (82%) included investigated myotonic dystrophy (DM); other studies were on pseudohypertrophic MD (PMD) or DMD. As a whole, MD individuals had significantly higher levels of circulating total cholesterol (Hedges' g with 95% confidence interval [CI], 0.80 [0.03 - 1.56]; p = 0.04) and triglycerides (Hedges' g with 95% confidence interval [CI], 2.28[0.63 - 3.92]; p = 0.01) compared to controls. Meta-regression analysis showed the percentage of male gender was significantly associated with the difference in total cholesterol (beta = 0.05; 95% CI, - 0.02 to 0.11; p = 0.043) and high-density lipoprotein (beta = - 9.38; 95% CI, - 16.26 to - 2.50; p = 0.028). CONCLUSIONS: MD is associated with significantly higher circulating levels of total cholesterol and triglycerides. However, caution on the interpretation of these findings is warranted and future longitudinal research is required to better understand this relationship.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.031 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".