The effect of ischemia-reperfusion injury on measures of vascular function
Bibliographic record
Abstract
BACKGROUND: Ischemia-reperfusion injury results in conduit vessel endothelial dysfunction as assessed by flow-mediated dilatation (FMD). The effect on the potentially more important microvascular circulation has not been well studied. The objective of our study was to assess the effect of ischemia-reperfusion injury on microvascular function including peripheral arterial tonometry (PAT) hyperemic index. METHODS: 45 healthy volunteers free of cardiovascular disease were recruited (mean age 35 ± 14 yrs, 29 men). Using ultrasound, the flow-mediated dilation (FMD) and hyperemic velocity (VTI) of the brachial artery were measured following a 5-minute forearm cuff occlusion. Simultaneously, the PAT hyperemic index was measured. Ischemia was then induced by a 15-minute upper arm occlusion and within 15 minutes of recovery the vascular measures were repeated. RESULTS: Ischemia caused a significant reduction in FMD (7.9 ± 4.0 to 4.7 ± 3.5, p = 0.0001). The hyperemic VTI, a measure of microvascular function, was unaffected following ischemia-reperfusion (92 ± 30 vs. 97 ± 37 cm, p = 0.236). Finally, PAT index was also unchanged by the intervention (2.07 ± 0.8 vs. 2.04 ± 0.7, p = 0.742). CONCLUSIONS AND DISCUSSIONS: Ischemia-reperfusion caused conduit and not resistance vessel endothelial dysfunction. The PAT-index was unchanged suggesting that this measure is more closely aligned with resistance than conduit vessel function. This has implications for its use as a measure of vascular function in clinical research.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".