Coronary artery bypass grafting in high-RISk patients randomised to off- or on-Pump surgery: a randomised controlled trial (the CRISP trial)
Bibliographic record
Abstract
BACKGROUND: Coronary artery bypass grafting (CABG) is the treatment of choice for patients with multivessel coronary artery disease (CAD). Evidence from randomised controlled trials (RCTs) in low-risk populations shows that 'off-pump' CABG is at least as safe as 'on-pump' CABG, but high-quality trial data in high-risk populations are lacking. OBJECTIVES: To test the hypothesis that, in high-risk patients, off-pump coronary artery bypass grafting (OPCABG) reduces mortality and morbidity without causing a higher risk of reintervention compared with on-pump coronary artery bypass grafting (ONCABG). DESIGN: Open parallel-group RCT with a 1 : 1 allocation ratio and expertise-based randomisation. SETTING: Eight specialist cardiac surgery centres in the UK and one specialist centre in Kolkata, India. PARTICIPANTS: Patients with an additive European system for cardiac operative risk evaluation score (EuroSCORE) of ≥ 5, undergoing non-emergency isolated CABG via a median sternotomy. INTERVENTIONS: CABG without cardiopulmonary bypass (CPB), i.e. OPCABG on the beating heart, or CABG with CPB, i.e. ONCABG on a chemically arrested heart. MAIN OUTCOME MEASURES: Primary outcome - a composite of death or serious morbidity [all-cause mortality, myocardial infarction (MI), stroke, prolonged initial ventilation, sternal wound dehiscence] within 30 days of surgery. Secondary outcomes - quality of life (QoL) [Rose Angina Questionnaire, Canadian Cardiovascular Society (CCS) angina class, European QoL-5 Dimensions (EQ-5D), Coronary Revascularisation Outcome Questionnaire (CROQ)] and resource utilisation. RESULTS: The organisation of a tertiary cardiac surgery service in the UK presented several barriers to recruitment. Referral information was often inadequate to confirm eligibility. Limited surgeon participation at a centre, the need to meet referral-to-treatment performance targets and complex referral pathways did not support an expertise-based allocation. Urgent patients waiting for surgery in local 'feeder' hospitals were often not transferred until late the night before surgery, which limited the time available to take consent and organise the surgery on an expertise basis. Several elective patients declined to take part because they wanted the surgeon they had met when the surgery was first discussed in clinic to operate. Several initiatives were explored to boost recruitment. After 10 months of recruitment, the trial design was modified to permit both within-surgeon and expertise-based randomisation within a centre. However, this did not have sufficient impact and the trial was stopped on the grounds of futility after 106 patients (< 2% of the target sample size) had been recruited in 18 months. Ninety-eight patients were included in the trial analyses, six patients were withdrawn and two died before surgery. In both groups, 6% of patients experienced the primary outcome [adjusted odds ratio (OR) (OPCABG to ONCABG) 1.07; 95% confidence interval (CI) 0.27 to 4.14]. QoL scores at 4-8 weeks post surgery were similar in the two groups. Patients randomised to OPCABG had a shorter stay in the intensive care unit and in hospital after surgery (median 26.0 vs. 27.7 hours in intensive care and 7 vs. 8 days in hospital). CONCLUSIONS: The Coronary artery bypass grafting in high-RISk patients randomised to off- or on-Pump surgery (CRISP) trial was not successful for a range of logistical reasons. However, the experience gained is of value for the design and conduct of future trials. The surgical community have polarised views. A qualitative evaluation of the reasons behind the views held by the advocates of the two techniques is an area for future research. TRIAL REGISTRATION: Current Controlled Trials ISRCTN29161170. FUNDING: This project was funded by the Medical Research Council/National Institute for Health Research (NIHR) Efficacy and Mechanism Evaluation programme and will be published in full in Health Technology Assessment; Vol. 18, No. 44. See the NIHR Journals Library website for further project information.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".