Prediction and impact of failure of transradial approach for primary percutaneous coronary intervention
Bibliographic record
Abstract
OBJECTIVES: To determine predictors of failure of transradial approach (TRA) in patients with ST elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI), and develop a novel score specific for this population. METHODS: Consecutive patients with STEMI undergoing primary PCI in a tertiary care high-volume radial centre were included. TRA-PCI failure was categorised as primary (primary transfemoral approach (TFA)) or crossover (from TRA to TFA). Multivariate analysis was performed to determine independent predictors of TRA-PCI failure, and an integer risk score was developed. Clinical outcomes up to 1 year were assessed. RESULTS: From January 2006 to January 2011, 2020 patients were studied. Primary TRA-PCI failure occurred in 111 (5%) patients and crossover to TFA in 44 (2.2%) patients. Independent predictors of TRA-PCI failure were: weight ≤65 kg (OR: 3.0; 95% CI 1.9 to 4.8, p<0.0001), physician with ≤5% TFA conversion (OR: 0.45; 95% CI 0.2 to 0.9, p=0.033), and physician with ≥10% conversion to TFA (OR: 2.2; 95% CI 1.2 to 3.7, p=0.005), intra-aortic balloon pump (OR: 2.0; 95% CI 0.9 to 4.3, p=0.066), cardiogenic shock (OR: 2.8; 95% CI 1.4 to 5.6, p=0.0035), endotracheal intubation (OR: 107; 95% CI 42 to 339, p<0.0001), creatinine >133 μmol/L (OR: 3.6; 95% CI 1.9 to 6.8, p<0.0001), age ≥75 (OR: 1.7; 95% CI 1.0 to 2.9, p=0.031), prior PCI (OR: 2.6; 95% CI 1.5 to 4.5, p=0.0009), hypertension (OR: 1.8; 95% CI 1.2 to 2.9, p=0.009). An integer risk score ranging from -1 to 12 was developed, and predicted TRA-PCI failure from 0% to 100% (c-statistic of 0.868; 95% CI 0.866 to 0.869). Mortality at 1 year remained significantly higher after TRA-PCI failure (adjusted OR 2.2; 95% CI 1.2 to 3.9, p=0.011). CONCLUSIONS: In a high-volume radial centre, the incidence of TRA-PCI failure is low and can be accurately predicted using a 9-variables risk score. Since outcomes after TRA-PCI failure remained inferior, further effort to maximise the use of radial approach for primary PCI should be investigated.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".