Urodynamic findings and urologic management of central cord syndrome
Bibliographic record
Abstract
Purpose: Central cord syndrome is the most common incomplete spinal cord injury, although urodynamic data on this subset of patients is lacking. We aim to determine the typical urodynamic features associated with this condition. Methods Consecutive patients undergoing urodynamic studies in a tertiary spinal cord unit between 2014 and 2018 were retrospectively reviewed to identify those with central cord syndrome. Charts were evaluated for demographics, spinal cord injury classification, symptoms, urodynamic parameters and treatment. Data were analysed using descriptive statistics. Results: A total of 131 consecutive patients undergoing urodynamic studies were reviewed and 33 were identified with central cord syndrome. Mean age was 46 years and 91% were male. The predominant spinal cord injury classification was American Spinal Injury Association D (52%). Overall, 94% (31/33) reported volitional voiding and normal bladder sensation. Video-urodynamics demonstrated neurogenic detrusor overactivity in 70% (23/33) of patients, with 15% (5/33) demonstrating leakage with neurogenic detrusor overactivity and 21% (7/33) having reflex emptying. In total, 94% (31/33) of patients had normal compliance, 42% (14/33) of patients had detrusor sphincter or bladder neck dyssynergia and 60% (20/33) had an alteration to their management plan following urodynamic study. Conclusion: There is discordance between subjective patient-reported symptoms and objective urodynamic findings. About two-fifths of patients may have a potentially unsafe urodynamic bladder profile and urodynamics studies resulted in a change in bladder management in the majority of patients. Urodynamic assessment of patients with central cord syndrome is essential to determine which patients require further intervention. Level of evidence: Not applicable for this multicentre audit.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".