The Effects of L-Carnitine Supplementation on Serum Lipids: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
BACKGROUND: The findings of trials investigating the effects of L-carnitine administration on serum lipids are inconsistent. This meta-analysis of randomized controlled trials (RCTs) was performed to summarize the effects of L-carnitine intake on serum lipids in patients and healthy individuals. METHODS: Two authors independently searched electronic databases including MEDLINE, EMBASE, Cochrane Library, Web of Science, PubMed and Google Scholar from 1990 until August 1, 2019, in order to find relevant RCTs. The quality of selected RCTs was evaluated using the Cochrane Collaboration risk of bias tool. Cochrane's Q test and I-square (I2) statistic were used to determine the heterogeneity across included trials. Weight mean difference (SMD) and 95% CI between the two intervention groups were used to determine pooled effect sizes. Subgroup analyses were performed to evaluate the source of heterogeneity based on suspected variables such as, participant's health conditions, age, dosage of L-carnitine, duration of study, sample size, and study location between primary RCTs. RESULTS: Out of 3460 potential papers selected based on keywords search, 67 studies met the inclusion criteria and were eligible for the meta-analysis. The pooled results indicated that L-carnitine administration led to a significant decrease in triglycerides (WMD: -10.35; 95% CI: -16.43, -4.27), total cholesterol (WMD: -9.47; 95% CI: - 13.23, -5.70) and LDL-cholesterol (LDL-C) concentrations (WMD: -6.25; 95% CI: -9.30, -3.21), and a significant increase in HDL-cholesterol (HDL-C) levels (WMD: 1.39; 95% CI: 0.21, 2.57). L-carnitine supplementation did not influence VLDL-cholesterol concentrations. When we stratified studies for the predefined factors such as dosage, and age, no significant effects of the intervention on triglycerides, LDL-C, and HDL-C levels were found. CONCLUSION: This meta-analysis demonstrated that L-carnitine administration significantly reduced triglycerides, total cholesterol and LDL-cholesterol levels, and significantly increased HDL-cholesterol levels in the pooled analyses, but did not affect VLDL-cholesterol levels; however, these findings were not confirmed in our subgroup analyses by participant's health conditions, age, dosage of L-carnitine, duration of study, sample size, and study location.
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 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 | 0.035 | 0.079 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.030 | 0.044 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".