Monitoring Detrusor Oxygenation and Hemodynamics Noninvasively during Dysfunctional Voiding
Bibliographic record
Abstract
The current literature indicates that lower urinary tract symptoms (LUTSs) related to benign prostatic hyperplasia (BPH) have a heterogeneous pathophysiology. Pressure flow studies (UDSs) remain the gold standard evaluation methodology for such patients. However, as the function of the detrusor muscle depends on its vasculature and perfusion, the underlying causes of LUTS likely include abnormalities of detrusor oxygenation and hemodynamics, and available treatment options include agents thought to act on the detrusor smooth muscle and/or vasculature. Hence, near infrared spectroscopy (NIRS), an established optical methodology for monitoring changes in tissue oxygenation and hemodynamics, has relevance as a means of expanding knowledge related to the pathophysiology of BPH and potential treatment options. This methodological report describes how to conduct simultaneous NIRS monitoring of detrusor oxygenation and hemodynamics during UDS, outlines the clinical implications and practical applications of NIRS, explains the principles of physiologic interpretation of NIRS voiding data, and proposes an exploratory hypothesis that the pathophysiological causes underlying LUTS include detrusor dysfunction due to an abnormal hemodynamic response or the onset of oxygen debt during voiding.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".