P.127 Preventing C5 palsy after cervical decompression by nerve root untethering and intraforaminal ligament release
Bibliographic record
Abstract
Background: Postoperative C5 palsy (C5P) is a common complication after cervical decompression, potentially related to nerve root tethering. To our knowledge, this is the first study to investigate this hypothesis by comparing C5/C6 root translation and tension before and after root untethering by cutting cervical intraforaminal ligaments (IFL). Methods: Six cadaveric dissections were performed. Nerve roots were exposed and translation and tension measured after the roots and spinal-cord were dorsally displaced 5mm before and after IFL cutting. These were also measured during shoulder depression to simulate intraoperative positioning. Clinical feasibility of IFL release was examined by comparing standard and extended foraminotomies to compare resultant root translation. Results: IFL-cutting increased translation at both C5/C6 roots (P=0.001). There was no difference between root levels (P=0.33). IFL-cutting increased translation upon shoulder depression at both C5/C6 roots (P=0.003) with a difference also being found between root levels (P=0.02). An extended cervical foraminotomy was technically feasible which enabled complete IFL release and root untethering, whereas a standard foraminotomy did not. Conclusions: IFL-cutting increases root translation, suggesting they are either protective (preventing peripheral nerve strain from being transmitted to the spinal-cord) or harmful (by tethering intraforaminal nerve roots and potentially contributing to postoperative C5P) depending on the clinical context.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".