Relationships Between Specific Functional Abilities and Health-Related Quality of Life in Chronic Traumatic Spinal Cord Injury
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to explore the relationships between specific functional abilities assessed from the third version of the Spinal Cord Injury Measure and health-related quality of life after a traumatic spinal cord injury. DESIGN: A prospective cohort of 195 patients who had sustained a traumatic spinal cord injury from C1 to L1 and consecutively admitted to a single level 1 spinal cord injury-specialized trauma center between April 2010 and September 2016 was studied. Correlation coefficients were calculated between Spinal Cord Injury Measure scores and Short Form 36 version 2 summary scores (physical component score; mental component score). RESULTS: The total Spinal Cord Injury Measure score correlated moderately with the physical component score in the entire cohort, correlated strongly with physical component score in tetraplegics, did not correlate with physical component score in paraplegics, and did not correlate with mental component score. Mobility subgroup and individual items scores showed the strongest correlations with the physical component score in the entire cohort, followed by self-care and sphincter management. CONCLUSIONS: This work is significant being the first to determine which specific functional abilities are mostly related to health-related quality of life and highlights the differences between tetraplegic and paraplegic patients. Our findings could help clinicians to guide rehabilitation plan based on importance of specific functional abilities in relationship with the health-related quality of life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".