Statin Safety in Chinese: A Population-Based Study of Older Adults
Bibliographic record
Abstract
BACKGROUND: Compared to Caucasians, Chinese achieve a higher blood concentration of statin for a given dose. It remains unknown whether this translates to increased risk of serious statin-associated adverse events amongst Chinese patients. METHODS: We conducted a population-based retrospective cohort study of older adults (mean age, 74 years) newly prescribed a statin in Ontario, Canada between 2002 and 2013, where 19,033 Chinese (assessed through a validated surname algorithm) were matched (1:3) by propensity score to 57,099 non-Chinese. This study used linked healthcare databases. FINDINGS: The follow-up observation period (mean 1.1, maximum 10.8 years) was similar between groups, as were the reasons for censoring the observation period (end of follow-up, death, or statin discontinuation). Forty-seven percent (47%) of Chinese were initiated on a higher than recommended statin dose. Compared to non-Chinese, Chinese ethnicity did not associate with any of the four serious statin-associated adverse events assessed in this study [rhabdomyolysis hazard ratio (HR) 0.61 (95% CI 0.28 to 1.34), incident diabetes HR 1.02 (95% CI 0.80 to 1.30), acute kidney injury HR 0.90 (95% CI 0.72 to 1.13), or all-cause mortality HR 0.88 (95% CI 0.74 to 1.05)]. Similar results were observed in subgroups defined by statin type and dose. CONCLUSIONS: We observed no higher risk of serious statin toxicity in Chinese than matched non-Chinese older adults with similar indicators of baseline health. Regulatory agencies should review available data, including findings from our study, to decide if a change in their statin dosing recommendations for people of Chinese ethnicity is warranted.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".