Dynamic vascular optical spectroscopy for monitoring peripheral arterial disease patients undergoing a surgical intervention
Bibliographic record
Abstract
Peripheral arterial disease (PAD) patients experience a reduction in blood supply to the extremities caused by an accumulation of plaque in their arterial system. In advanced stages of PAD, surgical intervention is often required to reopen arteries and restore limb perfusion to avoid necrosis and amputations. To determine the success of an intervention, it is necessary to confirm that reperfusion was achieved after the intervention in areas of the foot that lacked perfusion before the intervention. The standard procedure to obtain this information is to perform repeated X-ray angiography. However, this approach requires a relatively high radiation dose and the extensive use of contrast agents. To overcome these issues, our lab has developed a system that uses dynamic vascular optical spectroscopy (DVOS) to monitor perfusion in the foot in real-time before, during, and after an intervention. In the explorative study presented in this paper, we monitored ten patients undergoing revascularization surgery. We found that there is a clear change in the DVOS signal in cases when reperfusion to affected areas in the foot is established. It was also possible to assess the effects that balloon inflations and deflations and contrast agent injections had on the downstream vasculature of the patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".