COMPARATIVE ANALYSIS OF OUTCOME AFTER MEDICAL THERAPY ALONE VERSUS INCOMPLETE REVASCULARIZATION ALONG WITH MEDICAL THERAPY IN PATIENTS WITH MULTI-VESSEL CORONARY ARTERY DISEASE
Bibliographic record
Abstract
The retrospective study was conducted in the Department of Cardiology, Chaudhry Pervez Elahi Institute of Cardiology, Multan, from 29-Jan-2022 to 28-Jul-2022 to compare the frequency of relief from angina after medical therapy alone versus incomplete revascularization along with medical therapy in local patients with multi-vessel coronary artery disease. A total of 60 patients were enrolled and randomly divided into groups I and II. Group I received standard medical therapy as per the operational definition. Group II underwent incomplete coronary artery re-vascularization – stent placement through PCI in the fluoroscopy suite. Post-IR, these patients also received standard medical therapy. All the patients were called for monthly follow-up. Patients having symptomatic relief from angina were placed in functional class II. Results showed that pain relief from angina was observed in 10 (16.67%) patients and not in 50 (83.33%). A group comparison of symptomatic relief from angina showed that relief was observed in 02 (6.70%) patients in group I and 08 (26.70%) patients in group II. This result was statistically significant, with a p-value of 0.038. Stratification was performed based on age, gender, diabetes, hypertension, smoking, and obesity. There was no association between these variables and angina relief in either group. It can be concluded that in multi-vessel coronary artery disease, incomplete revascularization and medical therapy are superior to medical therapy alone.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".