Prevalence and predictors of complementary and alternative medicine modalities in patients with chronic hepatitis B
Bibliographic record
Abstract
BACKGROUND & AIMS: The use of complementary and alternative medicine (CAM) in patients with chronic hepatitis B (CHB) can interact with antiviral treatment or influence health-seeking behaviour. We aimed to study the use of individual CAM modalities in CHB and explore determinants of use, particularly migration-related, socio-economic and clinical factors. METHODS: A total of 436 CHB outpatients who attended the Toronto Centre for Liver Disease in 2015-2016 were included in this cross-sectional study. Using the comprehensive I-CAM questionnaire and health records, data were collected on socio-demographic and clinical variables and on usage of 16 CAM modalities in the last year. RESULTS: Sixty percent of patients were male, 74% were Asian and 46% were using antiviral treatment. Three-hundred and nine (71%) patients used CAM. Vitamin/mineral preparations (45% of patients) were most commonly used. Overall CAM use and the specific use of potentially injurious CAM, such as green tea extract (9.2%) and St. John's wort (0.2%), were not associated with liver disease severity. Female sex, family history of CHB, lower serum HBV DNA, and higher socio-economic status were independently associated with bio-holistic CAM use, the clinically most-relevant CAM group (P < 0.05); ethnicity, antiviral therapy use and liver disease severity were not. CONCLUSIONS: CAM use among CHB patients was extensive, especially use of vitamin and mineral preparations, but without direct influence on liver disease severity. Bio-holistic CAM use appeared to be associated with socio-economic status rather than with ethnicity or liver disease severity. Despite the rare use of hepatotoxins, physicians should actively inquire about it.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".