The Effect of Anaemia on Intra-operative Neuromonitoring Following Correction of Large Scoliosis Curves: Two Case Reports
Bibliographic record
Abstract
The correction of anemia is important in reversing significant intraoperative bilateral motor-evoked potential (MEP) loss following rod placement for correction of large scoliosis curves. This article presents a retrospective review of intraoperative neuromonitoring (IONM) data, anesthesia records, and medical charts of two patients with significant bilateral MEP changes associated with posterior spinal surgery for deformity correction. A 70 kg 12-year-old and a 44 kg 16-year-old female with main thoracic curves underwent a posterior scoliosis correction with multilevel posterior column osteotomies. Following rod insertion, significant reduction in the bilateral lower extremity MEP occurred in both cases despite mean arterial pressure exceeding 70 mmHg, which was presumed to be due to the scale of the correction attempted in the setting of haemorrhage which rendered the patient acutely anaemic, thus compromising cord vasculature and oxygen delivery. The rods were removed and packed red blood cell transfusions were administered in response to acute anaemia as a result of haemorrhage in both cases. Neither was noted to be anaemic preoperatively. Once the MEP signals improved, the rods were reinserted and correction was attempted, limited by neuromonitoring signals and resistance of the bony anchors to pullout. At closure, the MEPs were near baseline in the first case and >50% of baseline in the second. There were no changes in the somatosensory evoked potential signals in either case. Post-operative neurological function was normal in both patients. Correcting the circulating haemoglobin concentration through blood product resuscitation allowed for safe correction of spinal deformity in two cases with significant bilateral MEP loss following the initial placement of rods.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".