Spinal cord stimulation for refractory angina pectoris: a case series
Bibliographic record
Abstract
Background: Refractory angina pectoris significantly reduces the length and quality of life. One of the methods to control symptoms and improve the quality of life of patients with refractory angina pectoris is spinal cord stimulation.Objective: To evaluate the effectiveness of spinal cord stimulation in controlling anginal pain in the long-term period over a long follow-up (>7 years).Methods: We retrospectively studied treatment results of 9 patients (6 men and 3 women) in the long-term follow-up from October 2012 to November 2022. Anginal pain and patients' quality of life were assessed using the visual analog scale and the Seattle Angina Questionnaire, respectively.Results: The mean follow-up was 7.33 ± 1.11 years. In the long-term postoperative period, regression of pain according to the visual analog scale was 52.3% (P = .0025). The Seattle Angina Questionnaire showed an improvement of the quality of life by 52.2% (P = .0993).Conclusion: Spinal cord stimulation allows to make control of chronic anginal pain more efficient, improve patients’ length and quality of life, and reduce the frequency and severity of disability. Received 8 December 2022. Revised 17 July 2023. Accepted 18 July 2023. Informed consent: The patient’s informed consent to use the records for medical purposes is obtained. Funding: The study did not have sponsorship. Conflict of interest: The authors declare no conflict of interest. Contribution of the authors: The authors contributed equally to this article.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| 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".