The use of urologic investigations among patients with traumatic spinal cord injuries
Bibliographic record
Abstract
OBJECTIVE: To assess the use of urologic investigations among traumatic spinal cord injury (TSCI) patients. METHODS: This is a retrospective cohort study from Ontario, Canada. We included all adult TSCI patients injured between 2002 and 2012. The primary outcome was the frequency of urodynamic testing, renal imaging, and cystoscopy. Primary exposure was the year of injury. The impact of age, sex, comorbidity, socioeconomic status, and lesion level was assessed with Cox regression models. RESULTS: One thousand five hundred and fifty one incident TSCI patients were discharged from a rehabilitation hospital. The median follow-up time of this cohort was 5.0 years (interquartile range =2.9-7.5). At least one urodynamics, renal imaging, or cystoscopy was performed during follow-up for 50%, 80%, and 48% of the cohort, respectively. The overall rate of these tests was 0.22, 0.60, and 0.22 per person-year of follow-up. The proportion of patients who had regular, yearly urodynamics (<2%), renal imaging (6%), or cystoscopy (<2%) was low. There were no significant linear trends in the use of these tests over the 10-year study period. Urodynamics were significantly less likely to be performed in patients over 65 years of age (hazard ratio [HR] =0.63, P<0.01) and those with a higher level of comorbidity (HR =0.72, P<0.01). Patients with quadriplegia were significantly less likely to receive any of the investigations compared to those with paraplegia. CONCLUSION: Renal imaging is done at least once for the majority of patients with TSCI; however, only half undergo urodynamics or cystoscopy. Few patients have regular urologic testing. The reality of urologic testing after TSCI is very different from urologist's ideals and practice guidelines.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".