The safety of rosuvastatin in comparison with other statins in over 25 000 statin users in the Saskatchewan Health Databases
Bibliographic record
Abstract
PURPOSE: To compare mortality and the incidence of hospitalization for myopathy, rhabdomyolysis, acute renal failure and acute liver injury in patients receiving rosuvastatin and those taking other statins. METHODS: Patients prescribed a statin that they had not used before were selected from the Saskatchewan Health Databases (SHD) and followed up from 1 July 2003 until 31 March 2005. RESULTS: We studied 10,384 patients on rosuvastatin and 14,854 taking other statins. Two cases of myopathy were identified (one on rosuvastatin, one on another statin). The relative risk (RR) of myopathy in patients currently taking rosuvastatin compared with other statins was 1.31 (95% confidence interval [CI]: 0.13-13.41). Two cases of rhabdomyolysis were detected among current rosuvastatin users (incidence: 2.9 [95% CI: 0.8-10.7] per 10 000 person-years). No cases of acute liver injury occurred among rosuvastatin patients. Seventeen cases of acute renal failure were identified (five among rosuvastatin users, 12 taking other statins). The RR of acute renal failure in current rosuvastatin users compared with other statins was 0.49 (95% CI: 0.16-1.50). We identified 285 deaths during the study period (87 among rosuvastatin users, 198 taking other statins). The RR of death in current rosuvastatin users compared with other statins was 0.42 (95% CI: 0.32-0.57). CONCLUSIONS: We found no evidence that patients prescribed rosuvastatin were at greater risk of the study outcomes than patients prescribed other statins. There was no evidence of increased mortality among patients taking rosuvastatin, even after allowing for age, sex and prior statin use.
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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".