Identification and Management of Neurologic Complications in Patients Undergoing Adult Spinal Deformity Surgery
Bibliographic record
Abstract
Study DesignNarrative Literature Review.ObjectiveTo provide a comprehensive literature review of neurologic complications in Adult Spinal Deformity (ASD) surgery in the pre-operative, peri-operative and post-operative periods.MethodsA broad review of the literature was conducted using the multiple databases including Pubmed, Embase, Scopus and the Cochrane library. Individual studies of relevance were appraised and included at the discretion of the authors on the basis of pertinence, impact on practice and scientific merit.ResultsThe evidence regarding epidemiology, classification of complications, pre-operative evaluation of patients, peri-operative strategies to mitigate risk, intra-operative management of neuromonitoring changes and post-operative management of neurologic injury was critically appraised. Patients with the highest risk of neurologic complication include those with pre-surgery neuroaxis abnormality, high Deformity Angular Ratio, 3 column osteotomies and increased blood loss. Accurate and timely identification of intraoperative neuromonitoring changes is critical to ensuring appropriate response depending on whether changes are perfusion based (maintain adequate MAP and Hb, reverse corrective maneuvers) or traumatic (decompression of neural elements, assessment of instrumentation, reversal of corrective maneuvers, steroids). Surgical checklists can help surgeons navigate these stressful events to ensure appropriate steps and interventions are taken.ConclusionNeurological injuries occurring during the course of ASD surgery are potentially devastating complication, with regards to both patient morbidity and economic impact. Pre-operative identification of high risk patients, perioperative strategies to improve safety, timely recognition and management of intra-operative neuromonitoring changes and post-operative supportive measures can potentially reduce the incidence and significance of neurological injuries.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.016 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".