The Evolution of Wireless near Infrared Spectroscopy Applications in Urology and Rationale for Clinical Use
Bibliographic record
Abstract
Near infrared (NIR) spectroscopy is an established non-invasive optical technique for measuring changes in haemoglobin concentration occurring in the microcirculation in real time. NIR spectroscopy parameters reflect change in tissue haemodynamics and oxygenation and can contribute important physiologic insights when used alone or interpreted in parallel with other conventional measurements. The broad use of NIR spectroscopy in research is not matched by clinical applications; reasons include limitations inherent to the technique, using instruments designed for research at the bedside, ambiguity regarding what NIR spectroscopy measures, deficiencies of early algorithms, and understandable expectations by clinicians that NIR spectroscopy data are reproducible and specific enough for clinical decision making. Such issues could be addressed by appropriate collaboration where clinicians drive the questions which NIR spectroscopy is to answer, researchers contribute to monitoring methodology, device design and data analysis/algorithms and both groups utilise physiologic knowledge and practical lessons learned from prior NIR spectroscopy studies when interpreting data. NIR spectroscopy applications in urology are recent and offer clear opportunities for clinicians and researchers to collaborate. Urology is a field where current clinical investigations are limited in terms of the physiologic information they provide and because the principal test used for evaluation of the many people who have problematic lower urinary tract dysfunction is invasive in nature. Hence the rationale for non-invasive transcutaneous optical monitoring of the bladder during voiding as, when the organ contracts, changes in oxygenated and deoxygenated haemoglobin occur which allow haemodynamic variations and alterations in oxygen supply and demand to be inferred. Different patterns of change are evident in healthy and diseased tissue; these patterns reflect the effects of physiologic events observed using NIR spectroscopy to study other tissues and provide novel insights into the causation of voiding dysfunction. This review of the evolution of a wireless methodology for bladder studies includes examples of effective clinician researcher collaboration, reveals how miniature NIR spectroscopy devices make monitoring in ambulant subjects straightforward and makes possible studies in special populations such as children and patients with spinal cord injury. Hence, such wireless devices represent an advance of relevance in urology and an opportunity to expand research in other fields and progress with translation of NIR spectroscopy into other relevant clinical arenas.
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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 | 0.040 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".