Chinese Medicine as an Alternative Treatment for Adults with Hypercholesterolemia: A Systematic Review
Bibliographic record
Abstract
Introduction: Understanding whether Chinese medicine is an effective treatment for hyperlipidemia could potentially open doors to finding new lipid-lowering drugs with fewer adverse effects. This systematic review attempts to combine the available research on Chinese medicine and hyperlipidemia. Methods: Using keywords from the research question, 604 records were identified on the MEDLINE (Ovid) database. After assigning limits and screening articles based on the set criteria, the six remaining articles are read in full and narrative synthesis is done. Results: The six chosen articles are appraised using the Jadad score, and all are included in the review to give critical insights into different Chinese herbs. Studies from 2676 human and rat subjects in clinical settings were analyzed, and only Palmiwon, Lingzhi, Xuezhikang, and Daming capsules showed some positive effects on hypercholesterolemia. However, this is inconclusive as individual studies were small and possessed biases in random allocation sequence generation, allocation concealment, blinding of participants, incomplete outcome data, and selective outcome reporting. Discussion: This systematic review finds that some Chinese medicine has positive effects on treating hypercholesterolemia. However, there is not enough evidence to support their clinical use compared to HMG-CoA reductase inhibitors (stains). This is likely due to the limited use of Chinese medicine in Western medicine, resulting in a lack of peer-reviewed research. Conclusion: Some Chinese medicine has the potential to manage hypercholesterolemia in comparison with standard pharmacological treatment. However, further research is needed before establishing its clinical usage.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".