Quality of Life and Health Utility Scores Among Canadians Living With Traumatic Spinal Cord Injury - A National Cross-Sectional Study
Bibliographic record
Abstract
STUDY DESIGN: National, multicenter, cross-sectional study. OBJECTIVE: The goal of this study was to provide overall quality of life (QOL) and health utility (HU) values for patients with traumatic spinal cord injury (SCI) stratified by injury level and neurological status. SUMMARY OF BACKGROUND DATA: Traumatic SCI is a leading cause of disability. Varying injury level and severity generate a spectrum of neurological dysfunction and reduction in long-term QOL. METHODS: The Canadian SCI Community Survey was sent to Canadians living in the community after SCI. The impact of demographics, complications, and SCI classification on QOL was assessed using Analysis of variance, multiple linear regressions and ordinal logistic regression analyses. RESULTS: There were 1109 respondents with traumatic SCI. american spinal injury association impairment scale (AIS) grade was reported to be cervical motor complete in 20%, cervical motor incomplete in 28%, thoracolumbar motor complete in 32%, thoracolumbar motor incomplete in 16%, and normal (any level) in 1%. Injury level or AIS grade had no impact on either HU or QOL. The physical component of health-related quality of life (HRQOL) was significantly affected by the neurological level, but not the social or mental components. With a mean health utility score of 0.64 ± 0.12, SCI patients living in the community reported having HRQOL similar to patients after total knee arthroplasty or lumbar spinal stenosis decompression. CONCLUSION: QOL or HU measured by generic HRQOL outcome tools should not be used as outcomes to assess the effectiveness of interventions targeting neurological function in traumatic SCI. A disease-specific instrument that captures the nuances specific to spinal cord injury patients is required. LEVEL OF EVIDENCE: 1.
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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 | 0.001 |
| 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".