Real-Time Quantitative Measurements of Foot Perfusion in Patients With Critical Limb Ischemia
Bibliographic record
Abstract
INTRODUCTION: Current methods of evaluating adequacy of endovascular procedures are imperfect and do not always predict which patients will do well. The purpose of this study was to evaluate the role of real-time quantitative measurements of perfusion among patients with critical limb ischemia. MATERIALS AND METHODS: Thirty-four patients with critical limb ischemia undergoing endovascular treatment were recruited. Perfusion Images of the foot were obtained pre and post successful angioplasty using an SPY Elite System (Novadaq Technologies, Ontario, Canada). Patients were followed for 6 months. Subsequently a logistic regression was performed to determine whether intraprocedural perfusion parameters predicted the odds of wound healing. RESULTS: Twenty-nine patients had successful angioplasty. Median age was 69.5% ± 8.3; 75% were men and 64% were diabetic. Rutherford stages were (4%-39%, 5%-57%, 6%-4%), and the average target limb ankle-brachial index (ABI) was 0.58 (SD 2.24). There was no significant correlation between the ABI and perfusion parameters. Inflow perfusion rate correlated significantly with Rutherford stage (Spearman rho 0.398, P = .036). After successful angioplasty 39% had a decrease in inflow rate and 57% had a decreased total inflow. In all, 25 patients completed 6 months of follow-up. Resolution of rest pain and/or healing of the ischemic wound occurred in 10 (40%) patients at 1 month, 4 (16%) at 3 months, and 2 (8%) at 6 months. One patient underwent a major amputation at 2 months. Eight (32%) patients never healed or had persistent rest pain. None of the real-time perfusion variables were significant predictors of wound healing. CONCLUSION: Many patients experience a paradoxical decrease in perfusion following successful angioplasty suggesting perfusion may not correlate with angiographic outcome, possibly due to microemboli, microvascular disease, or vasospasm. Real-time perfusion imaging following intra-arterial infusion of indocyanine green does not predict the odds of wound healing.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".