Statin Discontinuation in High-Risk Patients: A Systematic Review of the Evidence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Hypercholesterolemia is a major risk factor for cardiovascular disease (CVD), the leading cause of death worldwide. Since the late 1980s, statins have emerged as effective lipid-lowering therapies and are now widely used to protect against and slow the progression of CVD and cerebrovascular disease. However, there is a significant gap between disease improvement in clinical trials and daily practice possibly attributable to poor adherence with statin therapy. High discontinuation rates were reported in primary and secondary prevention. This systematic review aims to summarize the current literature regarding the association between statin therapy discontinuation and cardiovascular and cerebrovascular events and all-cause mortality in high-risk patients. Available English literature was reviewed using Medline, Embase, Web of Sciences and the Cochrane Library; 39 studies were identified. In primary and secondary prevention, as well as perioperatively, non-adherence or discontinuation of statin therapy was associated with detrimental effects on cardiovascular and cerebrovascular outcomes, including disease severity and mortality. Importantly, some studies reported that very low adherence and discontinuation was associated with worse outcomes than never using statins. In conclusion, non-adherence and discontinuation of statin therapy significantly increased the incidence of cardiovascular and cerebrovascular events as well as all-cause mortality in high-risk patients. Patients would therefore benefit from closer adherence assessment and education programs aimed at increasing awareness of the risk associated with discontinuation of statin therapy.
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.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it