Incidence, predictors and longer‐term impact of troponin elevation following hybrid chronic total occlusion percutaneous coronary intervention
Bibliographic record
Abstract
OBJECTIVES: We examined the incidence of periprocedural cardiac enzyme rise (PCER) [troponin T (TnT) or high-sensivity (hs)TnT >5× the upper limit of normal (ULN)] and periprocedural myocardial infarction (PMI), predictors of PCER and impact of PCER on the longer-term major adverse cardiac events (MACE) following hybrid chronic total occlusion (CTO) percutaneous coronary intervention (PCI). BACKGROUND: PCER and PMI after CTO PCI, risk factors for PCER and its impact on longer-term MACE are not fully understood. METHODS: Among 469 CTO PCI cases performed between 01/2010 and 12/2015, next-day TnT or hsTnT was measured in 455 (97%). We examined the incidence of PCER and PMI (with clinical context or TnT ≥70× ULN). In 269 successful cases who had TnT measured, longer-term MACE (death, MI or target-vessel revascularisation/re-occlusion) were assessed. RESULTS: Overall, 420 CTOs (92.3%) were treated successfully. PCER was documented in 34%, while PMI in 2.9%. By multivariable analyses, higher J-CTO score (OR = 1.3 per point; P = 0.002), lower creatinine clearance (OR = 1.01 per each cc/min decrease; P < 0.0001) and recent MI (OR = 2.4; P = 0.007) were independent pre-PCI risk factors for PCER. Among procedural variables, retrograde approach (OR = 1.9; P = 0.014) and procedure duration (OR = 1.2 per 30 min; P = 0.007) were associated with PCER. At a median follow-up of 396 days following successful CTO PCI, PCER was not associated with higher MACE (9.3% vs. 8.1%; P = 0.60), and was not a predictor of MACE in multivariable analysis. CONCLUSIONS: PCER following hybrid CTO PCI is detected in 1/3 of patients. However, true PMI occurs in 2.9%. PCER does not predict adverse long-term outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".