Improved Angina Symptoms Following Coronary Sinus Flow Reducer Implantation in a Patient with Refractory Angina and Chronic Total Occlusion: A Case Report
Bibliographic record
Abstract
Background: Due to the aging population and increased survival of the patients with coronary artery disease, there is an increasing number of patients with debilitating angina refractory to optimal medical treatment who are not candidates for revascularization. In case of low ischemic load, the treatment of stable refractory angina is aimed at symptom reduction. There are several new treatment methods targeting myocardial ischemia available, including coronary sinus flow reducer (CFR) implantation. Case Report: We report a case of a patient suffering from CCS class IV angina despite optimal medical therapy, with further revascualrization options exhausted, who was successfully treated with coronary sinus flow reducer (CFR). Besides technical skill to reach ostium of coronary sinus, the most important technical tip is precise positioning of the CFR. The reduction of angina symptoms started after epithelisation of CFR frame, usually 6 - 7 weeks after implantation. At 6-month follow-up, the patient reported a marked reduction of angina symptoms, with CCS grade improving by three classes (from IV to I). At 10-month follow-up, the sustainment of CCS grade I angina symptoms was reported by the patient. Conclusions: We conclude that CFR can be safely and successfully implanted in patients suffering from refractory angina. Considerable improvements in CCS grade may be experienced in certain cases.
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.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".