Bibliographic record
Abstract
The Scalpel Cannot SeeFigureI have long held the notion that while sharps debridement is a necessary and time-honored technique to clear a wound of necrotic and nonviable tissue, the method is blunt and imprecise. It invariably removes viable tissue and may even leave biofilm on the wound. If the debridement technique is macroscopic, then how do we magnify our visualization to differentiate viable tissue from ischemic, necrotic, and nonviable skin, and subcutaneous, muscle, and extracellular matrices, in chronic or nonhealing wounds? To widen our lenses in the evaluation of the pathophysiologic determinants of an acute or chronic wound healing, we strive to develop advanced measurement systems. These technologies should have the ability to measure neurohumor, arteries, veins, endocrine, and lymphatics (NAVEL is a helpful mnemonic) dynamically and in real time. Toward this goal, significant advancements have taken place in “mapping out” or visualizing these systems, again perhaps macroscopically through the use of neurography, venography, lymphography, and angiography, in real time. Angiography has been especially useful in mapping out peripheral arterial disease and cardiac and cerebral obstructions. Imaging of human blood vessels was achieved almost 120 years ago in 1896. This was coincidental to the announcement of Roentgen’s (X-ray) discovery, when Haschek and Lindenthal injected “Teichmann’s mixture,” composed mainly of calcium carbonate, into the blood vessels of an amputated hand, outlining and imaging the vessels.1,2 In the intervening nearly century and a quarter, significant advances are allowing clinicians to identify vascularization, tissue perfusion, and viability of the tissues. One of the most noteworthy advancements in visualization of “real-time” blood flow in the tissues of the eye was the concept of dyeing or tagging the blood with a fluorescein dye. The dye is in the form of acid fluorochrome; the sodium salt is used in solution to reveal corneal lesions, as a test of circulation in the retina, and even the extremities. Two medical students at Indiana University are credited for the discovery of the use of fluorescein angiography for retinal imaging in 1960.3 These historical underpinnings for the use of real-time evaluation techniques using fluorescein angiography are relevant to the modern practice of wound care because of the macrostructures and microstructures of interest. Advancing the Scalpel’s Vision Increasingly, wound care practitioners, especially in wound centers, have access to infrared and near-infrared light with various applications for wound assessment (see page 37) and laser Dopplers to measure blood flow by measuring red blood cells as they move through the arterial system using the “Doppler effect.” A newer technology combining real-time fluorescence imaging to assess perfusion of viable tissue and the delineation of necrotic tissue for more precise identification for debridement is now available.4,5 Applications of intravascular injection of indocyanine green (ICG) for evaluation of peripheral blood circulation in patients with peripheral arterial disease have been evaluated and found to be effective in delineating ischemic and nonviable tissue in skin flap viability.4,5 Advanced technology adds laser-induced fluorescence of ICG as a new method for evaluating skin perfusion, which is superior to conventional fluorescein angiography. The advantage of using fluorescein angiography with ICG is the mitigation of ionizing radiation and nephrotoxicity associated with other radiopaque dyes used in radiologic imaging. One such device is the LUNA Fluorescence Microangiography System (Novadaq Technologies, Inc, Mississauga, Ontario, Canada), a novel tool that brings this imaging technology to the clinic and the bedside.6,7 The system is dubbed the “LUNA” System because it illuminates and differentiates viable tissue from necrotic tissue in real time, allowing the wound care practitioner to visualize the area of interest displayed from a mobile platform and monitor. Recently, the Centers for Medicare & Medicaid Services established vascular angiography as a new reimbursable service under the Hospital Outpatient Prospective Payment System through Ambulatory Payment Classification 0397, Vascular Imaging. The rapid tempo of technological advancements enhancing wound evaluation is exemplified by Moore’s Law. In 1965, Gordon Moore, cofounder of Intel Corporation, Santa Clara, California, predicted that computer processor speeds and power would double every 18 months9; similarly, our power to visualize tissues of interest in the wound bed and the periphery has advanced exponentially and is now ready for use in the clinic. “We only see what we know.” — Johann Wolfgang von Goethe (1749–1832)FigureRichard “Sal” Salcido, MD, EdD
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 0.010 |
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".