Letter to the Editor From Modarressi and Derakhshan: “Effects of Coenzyme Q10 Supplementation on Lipid Profiles in Adults: A Meta-analysis of Randomized Controlled Trials”
Bibliographic record
Abstract
We applaud Liu and colleagues for their thorough meta-analysis of the effects of coenzyme Q10 supplementation on lipid profiles (1). However, we believe the impact of their findings is misstated. The authors cite the 2005 Cholesterol Treatment Trialists’ (CTT) Collaboration data (2) and state “reducing [low-density lipoprotein cholesterol] LDL-C by 3.03 mg/dL [0.078 mmol/L] might lower coronary mortality by 1.49%”. However, the CTT data cited shows a 19% relative risk reduction in coronary heart disease-specific mortality for every 1 mmol/L reduction in LDL-C, not absolute risk reduction (which was 1%). This is a critical distinction: a 1.49% relative risk reduction would be among the weakest and most insignificant cardiovascular interventions available, dwarfed by many possible intensive lifestyle and pharmacologic interventions. As the CTT investigators themselves say, the absolute benefit relates to an individual's absolute risk and absolute reduction in LDL-C. Therefore, we propose this meta-analysis better highlights that there is no role for coenzyme Q10 supplementation for the sole and direct purpose of reduction of LDL-C, and the data presented does not justify the authors’ comment that supplementation may be helpful for “early prevention of cardiovascular diseases.”
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Editorial About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.014 | 0.098 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.016 | 0.020 |
| Insufficient payload (model declined to judge) | 0.009 | 0.008 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".