39. NERVE TRANSFERS CAN IMPROVE UPPER EXTREMITY FUNCTION IN CERVICAL SPINAL CORD INJURY: A PROSPECTIVE PROOF-OF-CONCEPT STUDY
Bibliographic record
Abstract
PURPOSE: Restoration of upper extremity (UE) function is important to people living with cervical spinal cord injury (SCI) and nerve transfer surgery (NT) is poised to change the treatment paradigm. In this proof-of-concept study, we hypothesized that NT can restore UE function with minimal peri-operative diminution of health-related quality of life (HRQoL). METHODS: A prospective single-arm pre/post comparative study design was used to evaluate function and HRQoL. Adults with mid-cervical level SCI undergoing UE NT surgery were recruited. Validated outcomes measures (Graded Redefined Assessment of Strength, Sensibility and Prehension (GRASSP); Spinal Cord Independence Measure (SCIM)) and qualitative semi-structured interview data were obtained and analyzed. RESULTS: Ten males (mean 36.9 years old; underwent 22 NTs to restore hand function at 5.2 years post-SCI) were followed for 25.9 months. SCIM and GRASSP post-scores significantly increased in all cases (p<0.01). Qualitative data showed that a majority thought the surgery was “worth it”; some had functional gains not reflected in the quantitative assessment scoring. One participant with minimal gains did not regret the surgery and was glad to “help progress the science”. CONCLUSION: In people with cervical SCI, NT can improve UE movement and significantly increase function and independence. Surgical reconstructions with NT presents a viable option for individuals who may not be candidates for or prefer to avoid the perioperative morbidity associated with tendon transfer surgery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 teacher head, 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".