National Survey of Bladder and Gastrointestinal Dysfunction in People with Spinal Cord Injury
Bibliographic record
Abstract
Small-scale studies indicate that spinal cord injury (SCI) may lead to significant gastrointestinal and bladder dysfunction. However, how the prevalence of chronic disease related to these dysfunctions compares with non-SCI individuals and whether there are robust relationships to level and severity of injury are still unclear. Here, our goal was to provide high-level evidence on the association between bladder and gastrointestinal dysfunction and SCI using population-level data from the Canadian Community Health Survey (CCHS) and the SCI Community Survey. Data from more than 60,000 individuals in the 2010 CCHS and 1500 individuals with SCI from the SCI Community Survey were analyzed. We used bi-variable and multi-variable logistic regression to examine relationships between explanatory and outcome variables. We found that SCI was associated with increased odds of urinary incontinence (adjusted odds ratio [aOR] = 5.0, 95% confidence interval [CI]: 3.4-7.1), bowel disorders (aOR = 2.3, CI: 1.5-3.4), as well as gastric ulcers (aOR: 3.3, CI: 2.1-4.8), even after adjusting for key confounding variables. Additionally, we found that complete SCI was associated with increased odds of urinary tract infections (aOR = 2.0, CI: 1.6-2.5) and bowel incontinence (aOR = 2.1, CI: 1.7-2.6). Individuals with SCI are at increased odds for having bladder and gastrointestinal dysfunction, certain aspects of which are dependent on the level and severity of injury. Targeted intervention and prevention strategies to manage bladder and bowel problems after SCI should be a priority for both caregivers and policy makers.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".