Clinical Protocol for Identifying and Managing Bladder Dysfunction during Acute Care after Traumatic Spinal Cord Injury
Bibliographic record
Abstract
Bladder dysfunction is widespread following traumatic spinal cord injury (TSCI). Early diagnosis of bladder dysfunction is crucial in preventing complications, determining prognosis, and planning rehabilitation. We aim to suggest the first clinical protocol specifically designed to evaluate and manage bladder dysfunction in TSCI patients during acute care. A retrospective cohort study was conducted on 101 patients admitted for an acute TSCI between C1 and T12. Following spinal surgery, presence of voluntary anal contraction (VAC) was used as a criterion for removal of indwelling catheter and initiating trial of void (TOV). Absence of bladder dysfunction was determined from three consecutive post-void bladder scan residuals ≤200 mL without incontinence. All patients were reassessed 3 months post-injury using the Spinal Cord Independence Measure (SCIM). A total of 74.3% were diagnosed with bladder dysfunction during acute care, while 57.4% had a motor-complete TSCI. Three months later, 94.7% of them reported impaired bladder function. None of the patients discharged from acute care after a functional bladder was diagnosed reported impaired bladder function at the 3-month follow-up. A total of 95.7% patients without VAC had persisting impaired bladder function at follow-up. The proposed protocol is specifically adapted to the dynamic nature of neurogenic bladder function following TSCI. The assessment of VAC into the protocol provides major insight on the potential for reaching adequate bladder function during the subacute phase. Conducting TOV using bladder scan residuals in patients with VAC is a non-invasive and easy method to discriminate between a functional and an impaired bladder following acute TSCI.
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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 | 0.016 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.010 |
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".