Correlations Between the Ankle-Brachial Index, Percentage of Mean Arterial Pressure, and Upstroke Time for Endovascular Treatment
Bibliographic record
Abstract
BACKGROUND: The ankle-brachial index (ABI), percentage of mean arterial pressure (%MAP), and upstroke time (UT) are indicators to diagnose lower-extremity peripheral artery disease (PAD). However, the respective relationship between these parameters is unknown. In this study, we analyzed the correlations between ABI, %MAP, and UT and examined their clinical usefulness for endovascular treatment (EVT). METHODS: Sixty-three consecutive subjects who underwent successful EVT for aortoiliac to femoropopliteal artery diseases were analyzed. The ABI, %MAP, and UT were measured using an automated oscillometric device. RESULTS: There were significant correlations between the ABI and %MAP (r = -0.425, P < 0.001), the ABI and UT (r = -0.304, P = 0.017), and %MAP and UT (r = 0.368, P = 0.003). In terms of lesion length, there was a significant difference in %MAP after EVT (focal, 42.6%; short, 44.5%; intermediate, 47.1%; long, 49.1%; P = 0.015). There was minimal %MAP improvement in the case of a long lesion length (focal, -8.83%; short, -5.10%; intermediate, -3.00%; long, -1.50%; P = 0.006). Excessive lesion calcification also hindered %MAP improvement (grade 0, -7.16%; grade 1, -5.52%; grade 2, -4.71%; grade 3, -2.80%; grade 4, -1.00%; P = 0.049). Patients who underwent re-EVT (an average of 10.1 months after initial EVT) had minimal %MAP improvement (-2.76% vs. -5.95%, P = 0.035) at the first outpatient visit (an average of 3.3 weeks after EVT). CONCLUSIONS: In conclusion, the ABI, %MAP, and UT are correlated with each other. If the length of the lesion is long and there is excessive calcification, %MAP improvement is minimal. Moreover, minimal %MAP improvement may be an indicator of future restenosis.
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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 | 0.004 |
| 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".