Reliability of intraoperative electrophysiological monitoring in selective posterior rhizotomy
Bibliographic record
Abstract
OBJECT: Selective posterior rhizotomy is a well-established treatment for spasticity associated with cerebral palsy. At most medical centers, responses of dorsal rootlets to electrical stimulation are used to determine ablation sites; however, there has been some controversy regarding the reliability of intraoperative stimulation. The authors analyzed data obtained from the McGill Rhizotomy Database to determine whether motor responses to dorsal root stimulation were reproducible. METHODS: A series of 77 patients underwent selective dorsal rhizotomy at a single medical center. The dorsal roots from L-2 to S-2 were stimulated to determine the threshold amplitude. The roots were then stimulated at 2 to 4 times the highest threshold with a 1-second 50-Hz train. A second stimulation run of the entire dorsal root was performed before it was divided into rootlets. Rootlets were individually stimulated and sectioned according to the extent of abnormal electrophysiological propagation. Motor responses were recorded by electromyography and were also assessed by a physiotherapist, and grades of 0 to 4+ were assigned. The difference in grades between the first and second stimulation trains was determined for 752 roots. Statistical analysis demonstrated a clear consistency in motor responses between the two stimulation runs, both in the electromyographic readings and the physiotherapist's assessment. More than 93% of dorsal roots had either no change or a difference of only one grade between the two trials. Furthermore, the vast majority of dorsal roots assigned a grade of 4+ at the first trial maintained the same maximally abnormal electrophysiological response during the second stimulation run. CONCLUSIONS: This study indicates that currently used techniques are reproducible and reliable for selection of abnormal rootlets. Intraoperative electrophysiological stimulation can be valuable in achieving a balance between elimination of spasticity and preservation of underlying strength.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".