Alternate day versus daily atorvastatin in low-density lipoprotein cholesterol reduction: A meta-analysis
Bibliographic record
Abstract
Statins are the mainstay treatment for hyperlipidemia.They are hydroxymethylglutaryl-CoA inhibitors and cause reduction in low-density lipoprotein cholesterol (LDL-c) levels.Atorvastatin is one of the most commonly used statins.These drugs are usually prescribed in a daily dose regimen.Due to the long duration of action and prolonged effect on hepatocytes, alternate day atorvastatin therapy is theoretically as effective as daily dose atorvastatin.Several studies have compared the efficacy of alternate day and daily atorvastatin in LDL-c reduction.The authors performed a metaanalysis on these studies to find evidence for alternate day atorvastatin use in LDL-c reduction.The studies comparing alternate day and daily atorvastatin regimens were selected after a literature search.LDL-c reduction in both the alternate and daily groups were calculated from the data provided in the individual studies.The mean difference in LDL-c reduction was compared between the alternate day and daily atorvastatin groups.Metaanalysis performed on the studies revealed that the mean difference in LDL-c reduction among the alternate day and daily groups was only 8.36 mg/dL (95% CI -0.49 to 17.20).This difference was statistically not significant but trends toward a daily regimen.Further subgroup analysis suggested that the difference in LDL-c reduction is smaller in an atorvastatin-naive patient population (mean difference 0.92 mg/dL [95% CI -13.55 to 15.39 mg/dL]) and also in populations with fewer risk factors for cardiovascular disease (mean difference 3.79 mg/dL (95% CI -6.40 to 13.98 mg/dL]).In conclusion, the use of alternate day atorvastatin can reduce the cost by one-half and possibly offset many of its side effects.However, long-term studies with large sample sizes are required to evaluate its effect on cardiovascular events and mortality. Key Words: Alternate day atorvastatin; Alternate day statin; Alternate and
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.060 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".