Percutaneous coronary intervention provided better long term results than optimal medical therapy alone in patients with chronic total occlusion: A meta-analysis
Bibliographic record
Abstract
Studies comparing the outcome of percutaneous coronary intervention (PCI) along with optimal medical therapy (OMT) versus OMT alone in treatment of chronic total occlusion (CTO) are limited by observational design, variable follow-up period, diverse clinical outcomes, high drop-out and cross-over rates. This study aims to conduct a meta-analysis of published data of observational as well as randomized studies comparing long term outcomes of PCI+OMT versus OMT alone. PubMed, Embase and Cochrane databases were systematically reviewed. 15 studies meeting criteria were included in the meta-analysis. The New-castle Ottawa scale was used to appraise the overall quality of the studies. Random-effects model with inverse variance method was undertaken. Major adverse cardiovascular events (MACE) which comprises of cardiac death, myocardial infarction, stroke, and un-planned revascularization were significantly lower in the PCI+OMT group (RR:0.76; 95% CI:0.61 to 0.95; P=<0.00001; I2 = 85%). All-cause mortality and cardiac death were significantly lower in the PCI+OMT group (P=<0.00001 in both). Myocardial infarction and stroke rates were lower in the PCI+OMT group, however they did not reach statistical significance (P = 0.24, P = 0.15 respectively). Unplanned revascularizations (of any vessel) were also similar in both the groups (P = 0.78, I2 = 88%). PCI of CTO is rewarded with better long term outcome, in terms of MACE, all-cause mortality and cardiac death with similar rates of un-planned revascularization.
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.068 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".