Student Competition (Knowledge Generation) ID 1984770
Bibliographic record
Abstract
Background Following a traumatic spinal cord injury (tSCI), patients prioritize being able to manage their bowels independently. A reduction of independence can impact an individual’s quality of life. The current study investigates the relationships between sphincter control, level of independence and quality of life. We hypothesized that sphincter control would relate strongly to levels of independence and quality of life. Methods Adults with tSCI who consented to participate in the Rick Hansen Spinal Cord Injury Registry at the Lyndhurst Rehabilitation Centre completed community follow-up interviews from 2014-2021. Data was collected at baseline, year 1, 2 and 5 (n = 330). Descriptive data and neurological level of injury (NLI) were collected, along with the Life Satisfaction Questionnaire (LiSAT-11), 36-item Short Form Survey Quality of Life measures (SF-36v2) and the Spinal Cord Independence Measure III (SCIM). Separate analyses were conducted for NLI C1-T10 (upper motor neuron [UMN] [n=280]), and T11-S5 (lower motor neuron [LMN] [n=50]). Associations between sphincter management and life satisfaction were calculated using Spearman’s correlation coefficient, adjusted for age and sex. Results SCIM had a moderate, yet significant relationship with LiSAT-11 (r 2 =0.48, p <0.001) for LMN, but no relationship for UMN (r 2 = 0.17, p <0.001). A weak relationship was observed between SCIM and SF-36v2 for LMN (r 2 =0.30, p =0.014) but no relationship for UMN (r 2 =0.01, p =0.59). Conclusion Sphincter management scores after rehabilitation discharge are not a strong predictor of life satisfaction following tSCI suggesting that a multifaceted approach is required to assess an individuals’ quality of life post 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.944 | 0.890 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".