Variation in the use of stress testing and outcomes in patients with non-ST-elevation acute coronary syndromes: insights from GUSTO IIb
Bibliographic record
Abstract
AIMS: Non-invasive risk stratification of low- and intermediate-risk non-ST-elevation acute coronary syndromes (NSTE ACS) patients has been recommended, but limited data exist about the variation in clinical practice of stress testing in these patients and the impact of such testing on their outcomes. METHODS AND RESULTS: Patients with NSTE ACS enrolled in the GUSTO IIb (Global Use of Strategies To Open occluded coronary arteries in acute coronary syndromes-IIb) trial (n = 8011) were analysed to evaluate patterns of stress testing in US and non-US patients and to further evaluate the clinical characteristics, procedure use, and outcomes of patients who underwent stress testing compared with those who did not. Stress testing was performed in 1878 (24%) patients. Compared with patients not undergoing stress testing, those undergoing stress testing had low-risk characteristics and significantly lower death (0.6% vs. 4.8%), and death or myocardial infarction (MI, 3.9% vs. 11%) rates at 30 days. Stress testing was performed as often after as before coronary angiography. Importantly, stress testing was helpful in stratifying patients into low (equivocal or negative test) or high (positive test) risk groups (30 day death 3.1% vs. 5%). Stress testing was performed more often in non-US than US patients, and US patients were 3.5 times more likely to undergo imaging as part of stress testing. However, the risks of 30-day death or MI; 6-month death, MI or revascularization; and 1-year death did not differ between US and non-US patients. CONCLUSION: Stress testing is commonly performed in low-risk NSTE ACS patients and provides modest additional prognostic information in this cohort. Significant geographical variation exists in the use of stress testing. Therefore, in the current practice environment where cardiac catheterization is often the first diagnostic modality used in patients with NSTE ACS, the role of non-invasive testing both before and after invasive procedure is in need of further study.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".