Remote ischemic conditioning: from experimental observation to clinical application: report from the 8th Biennial Hatter Cardiovascular Institute Workshop
Bibliographic record
Abstract
In 1993, Przyklenk and colleagues made the intriguing experimental observation that 'brief ischemia in one vascular bed also protects remote, virgin myocardium from subsequent sustained coronary artery occlusion' and that this effect'... may be mediated by factor(s) activated, produced, or transported throughout the heart during brief ischemia/reperfusion'. This seminal study laid the foundation for the discovery of 'remote ischemic conditioning' (RIC), a phenomenon in which the heart is protected from the detrimental effects of acute ischemia/reperfusion injury (IRI), by applying cycles of brief ischemia and reperfusion to an organ or tissue remote from the heart. The concept of RIC quickly evolved to extend beyond the heart, encompassing inter-organ protection against acute IRI. The crucial discovery that the protective RIC stimulus could be applied non-invasively, by simply inflating and deflating a blood pressure cuff placed on the upper arm to induce cycles of brief ischemia and reperfusion, has facilitated the translation of RIC into the clinical setting. Despite intensive investigation over the last 20 years, the underlying mechanisms continue to elude researchers. In the 8th Biennial Hatter Cardiovascular Institute Workshop, recent developments in the field of RIC were discussed with a focus on new insights into the underlying mechanisms, the diversity of non-cardiac protection, new clinical applications, and large outcome studies. The scientific advances made in this field of research highlight the journey that RIC has made from being an intriguing experimental observation to a clinical application with patient benefit.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".