Long-term neurogenic lower urinary tract dysfunction: A case of cardiovascular nightmares
Bibliographic record
Abstract
CONTEXT: Individuals with spinal cord injury (SCI) suffering from autonomic dysreflexia (AD) due to neurogenic detrusor overactivity (NDO) can effectively be treated with intradetrusor onabotulinumtoxinA. We present a complex case to highlight the treatment's potential limitations to ameliorate AD and improve lower urinary tract (LUT) function in this population. FINDINGS: A 46-year old man, who was relying on an indwelling urethral catheter for bladder emptying due to severely impaired hand function following a SCI (C5, AIS B) sustained 30 years ago, underwent intradetrusor onabotulinumtoxinA injections for treatment of refractory NDO and associated AD. Although LUT function slightly improved (i.e. cystometric capacity increased while detrusor pressure was reduced), severe bladder-related AD persisted post-treatment. CONCLUSIONS: This case raises awareness of serious considerations when treating NDO-related AD in individuals with longstanding neurogenic LUT dysfunction and compromised dexterity following SCI. Given the limited improvement in LUT function and persisting bladder-related AD following treatment, urinary diversion as advocated in the wider literature should be considered to protect an individual's urinary tract from further deterioration and thus eliminate bladder-related AD consequences long-term. Early treatment and management of NDO and AD is crucial to minimize complications associated with these two major health risks in this population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".