Developing new ways to assess neural control of pelvic organ function in spinal conditions: ICI‐RS 2023
Bibliographic record
Abstract
OBJECTIVES: Several central nervous system (CNS) centers affect muscle groups of the lower urinary tract (LUT) and anorectal tract (ART) via autonomic and somatic pathways, working in different modes (storage or expulsion). Hence spinal cord dysfunction can affect the LUT and ART by several possible mechanisms. METHODS: This review reports the discussions of a workshop at the 2023 meeting of the International Consultation on Incontinence Research Society, which reviewed uncertainties and research priorities of spinal dysfunction. RESULTS: Discussion focussed on the levator ani nerve, mechanisms underpinning sensory function and sensation, functional imaging, dyssynergia, and experimental models. The following key research questions were identified. (1) Clinically, how can we evaluate the levator ani muscle to support assessment and identify prognosis for effective treatment selection? (2) How can we reliably measure levator ani tone? (3) How can we evaluate sensory information and sensation for the LUT and the ART? (4) What is the role of functional CNS imaging in development of scientific insights and clinical evaluation? (5) What is the relationship of detrusor sphincter dyssynergia to renal failure? CONCLUSIONS: Spinal cord dysfunction can fundamentally disrupt LUT and ART function, with considerable clinical impact. The evaluation needs to reflect the full scope of potential problems, and new clinical and diagnostic approaches are needed, for prognosis and treatment. The preclinical science evaluating spinal cord function in both LUT and ART storage and elimination remains a major priority, even though it is a challenging experimental context. Without this underpinning evidence, development of new clinical evidence may be held back.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".