Early Cognitive Decline In Pituitary Surgery: Is Nitrous Oxide the Culprit?
Bibliographic record
Abstract
Aim: Pituitary tumors have been found to produce cognitive dysfunctions predominantly related to memory and attention. There exists a potential interaction between surgical and anesthetic factors in producing cognitive changes. Therefore we aim to investigate the incidence of cognitive decline and role of nitrous oxide (N2O) on immediate cognitive changes in patients undergoing transsphenoidal removal of pituitary tumors. Patients & methods: Ninety patients between 18 and 65 years of age, undergoing transsphenoidal surgery for pituitary tumor removal, were enrolled and divided into two (air and N2O-based anesthetic regime) groups. Cognitive functions were noted using the Hindi Mini Mental State Examination at baseline and three times in the postoperative period (1-h, 24-h postextubation and at the time of hospital discharge). Results: Both groups were comparable with respect to demographics, baseline parameters and cognitive scores. Significant number of patients (73%) showed cognitive decline in both the groups within 24 h postoperatively. In the factor analysis, thyroid-stimulating hormone and fentanyl consumption were linked with changes in cognitive scores. Conclusion: Patients undergoing pituitary surgery have significantly immediate cognitive decline in the short followup, but N2O-based anesthesia alone does not increase the risk of postoperative cognitive decline.
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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 | 0.000 | 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) | 0.001 | 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".