Urinary tract infections, urologic surgery, and renal dysfunction in a contemporary cohort of traumatic spinal cord injured patients
Bibliographic record
Abstract
AIMS: The objective of this study was to measure the incidence of urinary tract infections (UTIs), urologic reconstruction/urinary diversion, and renal dysfunction after a traumatic spinal cord injury (TSCI). METHODS: Retrospective cohort study using administrative data from Ontario, Canada. All incident adult TSCI patients (2002-2013) admitted to a rehabilitation center were included. The impact of lesion level on each outcome was assessed. The rate of outcomes was further compared to an age and sex matched sample from the general population. RESULTS: A total of 2,023 incident TSCI patients were identified (median follow-up of 4.8 years). Most patients (73%) were male and median age was 50 years. Lesion level included cervical (39%), thoracolumbar (44%), and unknown (17%). The incidence of serious UTIs (requiring emergency room visit or hospital admission) was 40%. Thoracolumbar lesion TSCI patients had significantly greater risk of serious UTIs (HR 1.3, 95%CI 1.1-1.7, P < 0.01) compared to those with a cervical lesion. Urologic reconstruction/urinary diversion was carried out on 2.4% of patients. New onset renal dysfunction was identified in 4.2% (84) TSCI patients. The rate ratios for serious UTIs (10.59, 95%CI 8.71-12.89), urologic reconstruction/urinary diversion (6.48, 95%CI 3.07-13.68), and renal dysfunction (2.55, 95%CI 1.70-3.83) were significantly increased among TSCI patients compared to matched controls. CONCLUSIONS: Urologic disease is still an important source of morbidity for contemporary TSCI patients, and is more common compared to the general population. Neurourol. Urodynam. 36:640-647, 2017. © 2016 Wiley Periodicals, Inc.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| 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".