Comparing surgeries to restore upper extremity function in tetraplegia: Impact on function during the perioperative period
Bibliographic record
Abstract
CONTEXT/OBJECTIVE: To assess short-term changes in health outcomes in people with cervical-level spinal cord injury (SCI) who underwent upper extremity (UE) reconstruction via either novel nerve transfer (NT) or traditional tendon transfer (TT) surgery with individuals who did not undergo UE surgical reconstruction. DESIGN: Prospective, comparative cohort pilot study. PARTICIPANTS: 34 participants with cervical SCI met the following inclusion criteria: age 18 or older, greater than 6 months post-injury, and mid-cervical level SCI American Spinal Injury Association Impairment Scale (AIS) A, B or C. SETTING: Two tertiary academic hospitals and their affiliated veterans' hospitals. METHODS: Health outcomes were assessed using two previously validated measures, the Spinal Cord Independence Measure (SCIM) and Short-Form Health Survey (SF-36). Demographic, surgical, and survey data were collected at the initial evaluation and one month postoperatively/post-baseline. RESULTS: = 8). The TT group had a decline in SCIM and SF-36 scores whereas the NT and no surgery groups experienced little change in independence or health status in the immediate perioperative period. CONCLUSIONS: Surgeons and rehabilitation providers must recognize differences in the perioperative needs of people with cervical SCI who chose to have restorative UE surgery. Future work should focus on further investigation of health outcomes, change in function, and improving preoperative counseling and cross-disciplinary management.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".