The pattern of urologic care among traumatic spinal cord injured patients
Bibliographic record
Abstract
INTRODUCTON: We assessed the urologic care patterns of traumatic spinal cord injury (TSCI) patients. METHODS: This was a retrospective cohort study of adult TSCI patients injured between 2002 and 2012. The primary outcome was urologic consultation. The primary exposure was the year of injury. Measured covariates included lesion level, age, gender, comorbidity burden, and socioeconomic status. RESULTS: We identified 1551 incident TSCI patients who were discharged from a rehabilitation hospital in Ontario between 2002 and 2012. The median follow-up time of this cohort was 5.0 (inter-quartile range [IQR] 2.9-7.5) years. Within this cohort, 74% were male, and the mean age was 48 (IQR 33-63) years. In total, 66% of patients (1022/1551) were seen by a urologist in a median of 0.7 (IQR 0.2-3.0) years after the SCI. Over the study period, there was no change in the proportion of TSCI patients being assessed by a urologist within 1 year of their initial injury (median 55.1%, p = 0.92 for the trend). An adjusted Cox proportional hazards model demonstrated that TSCI patients who were female (hazard ratio [HR] 0.77, 95% confidence interval [CI] 0.66-0.92) or over 65 years of age (HR 0.70, 95% CI 0.57-0.85) were significantly less likely to be referred to a urologist. CONCLUSIONS: Urologists are often not involved in the care of TSCI patients, and this has not changed significantly over the last 10 years. Females and older patients are significantly less likely to be referred to a urologist.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".