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Record W1986520007 · doi:10.2217/fnl.14.45

Early Cognitive Decline In Pituitary Surgery: Is Nitrous Oxide the Culprit?

2014· article· en· W1986520007 on OpenAlexaff
Tumul Chowdhury, Hemanshu Prabhakar, Parmod K. Bithal, Bernhard Schaller, Hari H. Dash

Bibliographic record

VenueFuture Neurology · 2014
Typearticle
Languageen
FieldNeuroscience
TopicAnesthesia and Neurotoxicity Research
Canadian institutionsUniversity of Manitoba
FundersAll-India Institute of Medical Sciences
KeywordsCognitionCognitive declineCulpritMedicineAnestheticIncidence (geometry)Pituitary tumorsNitrous oxideAnesthesiaSurgeryInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.715

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.024
GPT teacher head0.272
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2014
Admission routes1
Has abstractyes

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