Clinical characteristics of postoperative cognitive dysfunction after local balloon compression for trigeminal neuralgia: a retrospective study
Bibliographic record
Abstract
Abstract Purpose To identify the high-risk population of trigeminal neuralgia (TN) with postoperative cognitive dysfunction, reduce the consequent long-term postoperative complications, and improve the postoperative quality of life. Methods A retrospective study was conducted among 94 TN patients that underwent percutaneous balloon compression in the Affiliated Huai 'an First People's Hospital of Nanjing Medical University from 2017 to 2022. Patients were divided according to the post- Mini-Mental State Examimation (MMSE) scores (postoperative cognitive dysfunction and postoperative cognitive function normal groups). General information, past medical history, laboratory examination, treatment methods, self rating anxiety scale (SAS) score, visual analog scale (VAS) score and MMSE score were collected. Results Total 21 patients developed postoperative cognitive impairment, of which 16 were transient, and 3 were prolonged. Postoperative cognitive impairment prolonged the hospital stay (p< 0.001). Advanced age (p = 0.028), high preoperative SAS score (p < 0.001), and prolonged anesthesia duration (p < 0.032) were independent risk factors for surgical patients of TN. Three patients in the postoperative cognitive dysfunction group showed brain swelling and extensive white matter degeneration in the frontal and parietal lobes. Eight patients were treated with hyperbaric oxygen (HBO), following which, the MMSE score was significantly higher (p < 0.05) than that in the group without HBO, with no long-term complications. Preoperative SAS score was negatively correlated with the postoperative MMSE score (R = 0.3541, p < 0.001). Conclusion Postoperative cognitive dysfunction prolongs hospital stay in patients with TN. Functional magnetic resonance imaging can reflect brain tissue damage, and HBO therapy helps in postoperative cognitive function recovery.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".