Abstract 156: Statins are Effective in Lowering LDL-C in High-Risk Patients with Mitochondrial Disease
Bibliographic record
Abstract
Background Mitochondrial dysfunction affects multiple organs with varying severity and can be either primary or secondary to other diseases (e.g.: Alzheimer’s disease) or medications. Statins may be beneficial in patients with mitochondrial disease (mitoD) who have a higher prevalence of cardiac risk factors including diabetes and sedentary lifestyle. Therefore, it would be useful to know if statins are effective in patients with mitoD for prevention of cardiovascular disease. Methods We identified adult patients with confirmed mitoD in our clinic. Clinical and laboratory parameters were compared between the statin and non-statin groups. Results 56 patients had confirmed mitoD, 8 of which were on statins (average of 2 year, equivalent 20 mg daily atorvastatin) for secondary prevention. The statin group had a higher risk of cardiovascular disease (5 High, 3 Moderate Framingham risk score), including higher age (mean, years = 67 (SD 15) vs. 53 (SD 15), p<0.05) and comorbidities, such as coronary heart disease (50 vs. 15%, p<0.019), obesity (33 vs. 2%, p<0.008), diabetes mellitus (38 vs. 15%, p<0.11) and hypertension (50 vs. 40%, p<0.58). At two years, the mean reduction in LDL-C was 39.8% (SD 17%, measured in 7/8). None had myopathy with an elevated CK more than x10 the upper limit of normal (ULN), or AST more than x3 ULN, either at baseline or after the initiation of statins. Conclusion Our study suggests that high-risk patients with mitoD may benefit from statins, if indicated for the prevention of cardiovascular disease. The fact that the lowering of LDL-C in mitoD patients was of the same magnitude as expected in the general population suggests that there is no difference in statin metabolism in these individuals.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".