Minimal Clinically Important Difference of Graded Redefined Assessment of Strength, Sensibility, and Prehension Version 1 in Acute Cervical Traumatic Spinal Cord Injury
Bibliographic record
Abstract
The Graded Redefined Assessment of Strength, Sensibility, and Prehension Version 1 (GRASSP v1) is a validated measure of upper extremity impairment shown to be sensitive and responsive for traumatic cervical spinal cord injury (SCI) in both North American (NA) and European (EU) cohorts. The minimal clinically important difference (MCID) is the quantitative change in an assessment scale that patients perceive as being beneficial. Our aim was to establish the MCID of all subtests of the GRASSP v1 for cervical SCI. We prospectively analyzed 127 patients from NA and EU for up to six months after motor complete and incomplete cervical SCI using the GRASSP v1, Spinal Cord Independence Measure, and International Standards of Neurological Classification of Spinal Cord Injury. We used a patient global rating of change and the anchor-based method to calculate MCID of GRASSP v1 at six months post-injury. The MCID was established for the whole group, dividing the sample by "better" and "much better." Improvement in GRASSP v1 Strength and Prehension Performance scores of 13 and 3 are the MCID for the better category, and 19 and 7 are the MCID for the much better category, respectively. The MCID was also established for the motor complete and incomplete groups. Improvement in GRASSP v1 Strength and Prehension Performance scores of 12 and 6 are the MCID for the motor complete group, and 17 and 12 are the MCID for the motor incomplete group, respectively. The GRASSP v1 Strength subscore is the most sensitive for detecting meaningful clinical change in patients and is most closely related to measures of independence. Thus, use of GRASSP v1 Strength and Prehension Performance as measures of change is substantiated by this study.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".