Remote ischaemic preconditioning protects against cardiopulmonary bypass-induced tissue injury: a preclinical study
Bibliographic record
Abstract
OBJECTIVES: To test the hypothesis that remote ischaemic preconditioning (rIPC) reduces injury after cardiopulmonary bypass (CPB). DESIGN: Randomised study with an experimental model of CPB (3 h CPB with 2 h of cardioplegic arrest). Twelve 15 kg pigs were randomly assigned to control or rIPC before CPB and followed up for 6 h. INTERVENTION: rIPC was induced by four 5 min cycles of lower limb ischaemia before CPB. MAIN OUTCOME MEASURES: Troponin I, glial protein S-100B, lactate concentrations, load-independent indices (conductance catheter) of systolic and diastolic function, and pulmonary resistance and compliance were measured before and for 6 h after CPB. RESULTS: Troponin I increased after CPB in both groups but during reperfusion the rIPC group had lower concentrations than controls (mean area under the curve -57.3 (SEM 7.3) v 89.0 (11.6) ng.h/ml, p = 0.02). Lactate increased after CPB in both groups but during reperfusion the control group had significantly more prolonged hyperlactataemia (p = 0.04). S-100B did not differ between groups. Indices of ventricular function did not differ. There was a tendency to improved lung compliance (p = 0.07), and pulmonary resistance changed less in the rIPC than in the control group during reperfusion (p = 0.02). Subsequently, peak inspiratory pressure was lower (p = 0.001). CONCLUSION: rIPC significantly attenuated clinically relevant markers of myocardial and pulmonary injury after CPB. Transient limb ischaemia as an rIPC stimulus has potentially important clinical applications.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".