Effects of Natural Health Products on Blood Pressure
Bibliographic record
Abstract
OBJECTIVE: To review the scientific literature to identify reports of the effects of natural health products (NHPs) on blood pressure. DATA SOURCES: Electronic databases (MEDLINE [1965-May 2004] via PubMed, the Cochrane Library [1995-May 2004], International Pharmaceutical Abstracts [1970-May 2004], Iowa Drug Information Services [1965-May 2004]) were searched using the key words medicine, herbal plants, medicinal plant preparations, phytotherapy, angiosperms/therapeutic use, gymnosperms/therapeutic use, ethnopharmacology, pharmacognosy, blood pressure, hypertension, hypotension, and diuretic. Searches were not limited by date, language, or publication type. Review articles and texts, as well as reference lists of relevant articles, were used to identify additional reports. STUDY SELECTION AND DATA EXTRACTION: Articles (English-language after 1980) were assigned to the following categories: human study, case report, animal study, in vitro study, or theoretical prediction based on chemical constituents. Discussions of mechanisms of action were noted. DATA SYNTHESIS: A comprehensive search of the scientific literature identified NHPs capable of affecting blood pressure. Case reports and clearly defined mechanisms of action provided strong evidence for the ability of ephedra and licorice to increase blood pressure. Coenzyme Q(10) was reported to decrease systolic and diastolic blood pressure, although the mechanism is unclear. The clinical significance of the blood pressure effects of other NHPs is unclear due to lack of conclusive in vivo data, as well as substantial variability in the chemical content of preparations of NHPs. CONCLUSIONS: Among published information, there is little definitive evidence with regard to the impact of NHPs on blood pressure. Additionally, effects may vary in a given patient with the formulation and standardization of a particular product. Until research better characterizes the effect of NHPs on blood pressure, patients should be encouraged to talk with their healthcare provider before starting or stopping any herbal product.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".