Vascular Assessment in Patients With a Lower Limb Wound: A Correlational Study of Photoplethysmography and Laser Doppler Flowmetry Toe Pressure Techniques
Bibliographic record
Abstract
Background: Vascular assessment of the lower limbs is essential in patients with diabetes. In the presence of noncompressible arteries, the ankle brachial index (ABI) can either be inconclusive or provide false-positive results. Toe pressure measurement has been suggested as an alternative as a noninvasive method for detecting peripheral arterial disease (PAD). Toe pressure measurement can be performed either by photoplethysmography (PPG) or by Laser Doppler flowmetry (LDF). The aim of this study was to determine correlations between the two techniques in order to promote the use of PPG in clinical practice. Methods: This was a prospective correlational study of 108 consecutive recruited adult patients, with and without diabetes, with at least one lower limb wound from a University-affiliated hospital wound care clinic. Toe pressure measurements were both performed with PPG and LDF devices. Results: Mean toe pressure values for PPG and LDF were, respectively, 83.7 (SD 35.4) and 79.5 (SD 32.0) mmHg (with a paired t-test 3.969, P < 0.01). In patients with at least one lower limb wound, a strong linear relation was found between PPG and LDF toe pressure techniques with a Pearson’s r correlation coefficient of 0.920 ( P < 0.001). Conclusions: PPG and LDF toe pressure techniques are equivalent in patients with at least one lower limb wound, irrespective of the presence of diabetes. Therefore, in the presence of an ABI with inconclusive results, such as in a patient with noncompressible vessels, both toe pressure techniques can be used for assessing the vascular supply of the lower limb with a wound.
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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 | 0.012 |
| 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 | 0.001 |
| 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".