Real-world data from the use of ranolazine in patients with stable angina pectoris: the RANGER study
Bibliographic record
Abstract
Abstract Background Although ranolazine is available since years as a second-line treatment to reduce angina attacks in patients with stable angina pectoris, real-world data on effectiveness, tolerability and safety of ranolazine are limited. Methods A non-interventional, prospective study conducted to assess the effectiveness and safety of ranolazine. Patients eligible for enrolment had a baseline assessment between one and fourteen days after initiating ranolazine for the first time and a follow-up visit three months later. Primary endpoints comprised the weekly frequency of angina attacks, total adverse events and ranolazine discontinuation rate. Secondary endpoints included the use of short-acting nitrates, changes on the Canadian Cardiovascular Society (CCS) angina classification score and quality of life scale score (QoL). Results In total, 1,101 patients were enrolled in 214 sites. Mean weekly angina attacks were reduced from 3.6±2.9 to 0.4±0.9 (p<0.0001) and the mean weekly consumption of short-acting nitrates decreased by 1.7±2.2 (p<0.0001). CCS class and QoL were also improved (p<0.0001). Adverse events were reported by 11 (1%) patients totally, while 2 of them (0.2%) were characterized as serious. Treatment was discontinued for any reason in 23 patients (2.1%) after the follow-up period. Ranolazine treatment was equally effective in all subgroups tested, with larger benefits observed in patients with more frequent angina and CCS angina class III and IV. Up-titration of ranolazine during the study improved the outcomes. Conclusion Ranolazine was well-tolerated and effectively reduced angina attacks with simultaneous improvement of CCS class and QoL score in patients with stable angina. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): The study was sponsored by Menarini Hellas. The study sponsor was involved in the study concept and design and in the interpretation of the data included in this publication, but not in the data collection and analysis. Menarini Hellas also funded the medical writing support for this publication.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".