The association of aging and the efficacy of PCI in stable coronary artery disease. A secondary analysis of ORBITA-2.
Bibliographic record
Abstract
Abstract Background Percutaneous coronary intervention (PCI) is recommended for symptom relief in patients with angina and stable coronary artery disease. ORBITA-2 was the first randomized, placebo-controlled trial to assess its efficacy in patients with stable angina, single or multivessel coronary artery disease, without a background of antianginal medication. Whether the effect is consistent across age groups remains unknown. Purpose To evaluate the efficacy of PCI across age groups on the ORBITA-2 primary and secondary endpoints, including angina episodes, quality of life, and treadmill exercise time. Methods All patients from the primary ORBITA-2 analysis contributed data to this analysis. Age was added as an interacting factor with treatment arm to the original models. For the daily symptoms, a Bayesian longitudinal Markov model was constructed; for the treadmill exercise time and questionnaires, a Bayesian ordinal proportional odds model including the pre-randomization and treatment arm, which was allowed to interact with age. Results The median age was 64±9 years. PCI reduced the number of angina episodes more in older (OR=2.0, 95%CrI 1.7 to 2.4, Pr=0.99) than in younger patients (OR=1.7, 95%CrI 1.7 to 2.1, Pr=0.99; Pr(Interaction)=0.99). PCI led to an improvement in Seattle Angina Questionnaire angina frequency, irrespective of age Pr(Interaction)=0.524. In contrast, the effect of PCI on treadmill exercise time was greater in younger than in older patients (125s 95%CrI 35.8 to 215, Pr=0.997 vs 31.9s 95%CrI 78.3 to -12.6, Pr=0.918; Pr(Interaction)=0.962). The effect of PCI in patients with Rose Angina was consistent across all age groups Pr(Interaction)=0.488. Conclusion PCI was effective across all ages in reducing the frequency of angina. However, the treadmill exercise time in older patients did not improve with PCI. To ensure the generalisability of results in all ages, these data should inform the choice of endpoints for cardiovascular clinical trials.Age adjusted PCI efficacy
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".