Risk of new onset diabetes mellitus with pitavastatin as compared to atorvastatin and rosuvastatin: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Statins are linked to the risk of new-onset diabetes mellitus (NODM). While atorvastatin and rosuvastatin are often associated with NODM, pitavastatin may carry a lower risk. This systematic review and meta-analysis (SRMA) evaluated the impact of pitavastatin on NODM compared to atorvastatin and rosuvastatin.Methods We conducted a systematic literature search using PubMed, CENTRAL, EMBASE, and ClinicalTrials.gov. Two authors independently screened studies, assessed the risk of bias using Joanna Briggs Institute, Newcastle-Ottawa, and Scottish Intercollegiate Guidelines Network checklists, and extracted data. The analysis was performed using RevMan 5.4.1, and results were represented as risk ratios (RR) with 95% confidence intervals (CI) and heterogeneity was evaluated using the I2 statistic.Results Of 517 records screened, 13 studies were included, comprising observational studies, and randomized controlled trials. Most of the studies showed pitavastatin to be associated with a lower or no risk of NODM. Meta-analysis revealed that pitavastatin had a lower risk of NODM compared to atorvastatin (RR = 0.86, 95% CI = 0.79–0.93, p = 0.0002) and rosuvastatin (RR = 0.77, 95% CI = 0.71–0.84, p < 0.00001).Conclusion Pitavastatin poses a lower risk of NODM than other statins, making it a potentially safer option for patients requiring long-term statin therapy.Protocol registration www.crd.york.ac.uk/prospero identifier is CRD42022371741.
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 | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.049 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".