Case Report of a Remote Ischemic Preconditioning Intervention during Aerobic Exercise in a 44-year-old Amateur Triathlete Male with a History of Acute Myocardial Infarction
Bibliographic record
Abstract
Over the years, exercise has become increasingly important in patients with acute myocardial infarction (AMI). However, AMI patients need to be closely monitored since they maintain cardiovascular disease risks, such as ventricular repolarization abnormalities in electrocardiograms during exercise and rest. A recent study showed the need to focus on the different potential mechanisms and the applicability of remote ischemic preconditioning (RIPC) for cardiac patients engaged in exercise rehabilitation. This is the first case report that explores the effectiveness of an RIPC intervention in a 44-year-old amateur triathlete male with a history of AMI during a moderate (75% of gas exchange threshold) and high (115% of gas exchange threshold) intensity steady-state cycling aerobic exercise. Prior to aerobic exercise, the participant was allocated to either RIPC intervention or CTL (control) with four cycles of five minutes of ischemia followed by five minutes of reperfusion. ECG was continuously recorded during the protocol. These findings showed that RIPC improved participant's oxygen uptake response and shortened his ventricular repolarization during steady-state aerobic exercises. By measuring the physiological and electrophysical parameters, this case report adds new evidence for the benefits of RIPC. This study also demonstrates the safety of the intervention for cardiac patients in addition to showing that the intervention is not dangerous or harmful. This provides a new approach to cardiac rehabilitation programs. Future studies with cardiac patients are needed to provide a safe, standardized exercise intervention in cardiac rehabilitation.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".