Assessment of Disability in Patients with Acute Traumatic Spinal Cord Injury: A Systematic Review of the Literature
Bibliographic record
Abstract
Given the importance of accurately and reliably assessing disability in future clinical trials, which will test therapeutic strategies in acute spinal cord injury (SCI), we sought to appraise comprehensively studies that focused on the psychometric properties (i.e., reliability, validity, and responsiveness) of all previously used outcome measures in the SCI population. The search strategy included Medline, CINAHL, EMBASE, and Cochrane databases. Two reviewers independently assessed each study regarding eligibility, level of evidence (using Sackett's criteria), and quality. Of 363 abstracts captured in our search, 36 full articles fulfilled the inclusion and exclusion criteria. Eight different outcome measures were used to assess disability in the SCI population, including Functional Independence Measure (FIM), Spinal cord Injury Measure (SCIM), Walking Index for Spinal Cord Injury (WISCI), Quadriplegia Index of Function (QIF), Modified Barthel Index (MBI), Timed Up & Go (TUG), 6-min walk test (6MWT), and 10-m walk test (10MWT). While 19 of 36 studies provided level-4 evidence, the remaining 17 articles were classified as level-2b evidence. Most of the instruments showed convergent construct validity in the SCI population, but criterion validity was not examined due to the lack a gold standard for assessment of disability. All instruments were tested in the rehabilitation and/or community setting, but only FIM was examined in the acute care setting. Based on our results of quality assessment, the SCIM has the most appropriate performance regarding the instrument's psychometric properties. Nonetheless, further investigations are required to confirm the adequate performance of the SCIM as a comprehensive measure of functional recovery in patients with SCI in rehabilitative care. The expert panel of the Spinal Cord Injury Solutions Network (SCISN) that participated in the modified Delphi process endorsed these conclusions.
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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 | 0.011 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".