Risks and benefits of optimised medical and revascularisation therapy in elderly patients with angina ? on-treatment analysis of the TIME trial
Bibliographic record
Abstract
AIM: To assess treatment effects of optimised medical therapy and PCI or CABG surgery on one-year outcome in patients 75 years old with chronic angina. METHODS AND RESULTS: On-treatment analysis of the TIME data: all re-vascularised patients (REVASC n=174: 112 randomised to revascularisation and 62 to drugs with late revascularisation) were compared to all patients on continued drug therapy (MED n=127: 86 randomised to drugs and 41 to revascularisation only). Baseline characteristics of both groups were similar (age 80 +/- 4 years). Risk of death at one year (adjusted hazard ratio (HR)=1.31; 95%-CI: 0.58-2.99; P=0.52) and of death/infarction (adjusted hazard RATIO=1.77; 95%-CI 0.91-3.41; P=0.09) were comparable between REVASC and MED patients. Furthermore, the risk of death within 30 days was even slightly lower among REVASC patients (unadjusted hazard RATIO=0.73; 95%-CI: 0.21-2.53; P=0.98). Overall, REVASC patients had greater improvements in symptoms and well-being than MED patients (P<0.01). Surgical patients had similar mortality rates as angioplasty patients, but they also had greater symptomatic improvements (P<0.01). CONCLUSION: Treated medically, elderly patients with chronic angina have a similarly high 30-day and one-year mortality as patients of the same age being re-vascularised; however, they can expect lower improvements in symptoms and well being.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".