Editorials Statins: the high risks of discontinuation and large benefits of continuation
Bibliographic record
Abstract
In their mini-review/short communication in this issue of the Archives of Medical Science, Dr. Paraskevas et al. [1] draw proper attention to the consequences of statin discontinuation.They focus primarily on the cerebrovascular disease but their conclusion that absolute benefits of discontinuation are small and the absolute risks are high is consistent with a large and robust totality of evidence.The Cholesterol Treatment Trialist's Collaboration [2, 3] published two worldwide and comprehensive meta-analyses of randomized data.The first, among about 90,000 participants in 14 randomized trials, showed that statin therapy produced statistically significant and clinically important reductions in myocardial infarction, stroke, cardiovascular death and total mortality and a remarkable safety profile.The second, among 170,000 participants in 26 randomized trials, showed that further reductions by statins in low density lipoprotein (LDL) cholesterol safely produce definite further reductions in the incidence of myocardial infarction, stroke and revascularization.Specifically, each 1.0 mmol/l reduction in LDL cholesterol produces a statistically significant and clinically important reduction in the annual rate of these major vascular events by just over 20%.There was no evidence of any threshold within the cholesterol range studied, suggesting that reduction of LDL cholesterol by 2-3 mmol/l would reduce risk by about 40-50%.Thus, the recent randomized trials of statins using higher doses against lower doses as the active comparator arm have contributed importantly relevant information to two long standing hypotheses [4].The first is that lower is better and the prior totality of evidence included basic research and observational epidemiological studies, including in rural China where the average total cholesterol is less than 3.7 mmol/l and those with total cholesterol levels that are 10% lower had significantly decreased risks of occlusive vascular events [5].The second is that there is no threshold and the meta analysis of the data from randomized trials with active comparators in secondary prevention contribute importantly relevant data to this hypothesis.In terms of primary prevention the JUPITER trial also contributes the most importantly relevant data as the randomized population had no prior events and a 10 year risk of a first CHD event of 16-18% [6].Further, at baseline the LDL was about 3.0 and subjects assigned to 20 mg rosuvastatin achieved a greater than
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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 | 0.010 | 0.052 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".