Tolerability of statin-based management of patients with a history of statin-associated muscle symptoms: protocol for a systematic review
Bibliographic record
Abstract
Introduction Statin-associated muscle symptoms (SAMSs) are a major clinical issue in the primary and secondary prevention of cardiovascular events. Current guidelines advise various approaches mainly based on expert opinion. We will lead a systematic review and meta-analysis to explore the tolerability and acceptability and effectiveness of statin-based therapy management of patients with a history of SAMS. We aim to provide evidence on the tolerability and different strategies of statin-based management of patients with a history of SAMS. Methods and analysis We will conduct a systematic review of randomised controlled trials (RCTs) and non-randomised studies with a control group. We will search in Data sources MEDLINE, EMBASE, Cochrane Central Register of Controlled Clinical Trials, Scopus, Clinicaltrials.gov and Proquest from inception until April 2021. Two independent reviewers will carry out the study selection based on eligibility criteria. We will extract data following a standard data collection form. The reviewers will use the Cochrane Collaboration’s tools and Newcastle-Ottawa Scale to appraise the study risk of bias. Our primary outcome will be tolerability and our secondary outcomes will be acceptability and effectiveness. We will conduct a qualitative analysis of all included studies. In addition, if sufficient and homogeneous data are available, we will conduct quantitative analysis. We will synthesise dichotomous data using OR with 95% CI and continuous outcomes by using mean difference or standardised mean difference (with 95% CI). We will determine heterogeneity visually with forest plots and quantitatively with I 2 and Q-test. We will summarise the confidence in the quantitative estimate by using Grading of Recommendations Assessment, Development and Evaluation approach. Ethics and dissemination As a systematic review of literature without collection of new clinical data, there will be no requirement for ethical approval. We will disseminate findings through peer-reviewed publications. PROSPERO registration number CRD42020202619.
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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 | 0.060 | 0.070 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.018 | 0.023 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.060 | 0.008 |
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".