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Record W4386946491 · doi:10.1055/s-0043-1771365

Emergence Patterns from General Anesthesia after Epilepsy Surgery: An Observational Pilot Study

2023· article· en· W4386946491 on OpenAlexaff
Lashmi Venkatraghavan, Suparna Bhardwaj, Sujoy Banik, Tumul Chowdhury, Mary Pat McAndrews, Taufik A. Valiante

Bibliographic record

VenueAsian Journal of Neurosurgery · 2023
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsWestern UniversityToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsObservational studyMedicineEpilepsy surgeryNeuropsychologyEpilepsyAnesthesiaProspective cohort studySurgeryPsychiatryCognitionInternal medicine

Abstract

fetched live from OpenAlex

Abstract Objective Emergence from anesthesia starts from the limbic structures and then spreads outwards to brainstem, reticular activating systems, and then to the cortex. Epilepsy surgery often involves resection of limbic structures and hence may disrupt the pattern of emergence. The aim of this study was to explore the pattern of emergence from anesthesia following epilepsy surgery and to determine associated variables affecting the emergence pattern. Setting and Design Tertiary care center, prospective observational study. Materials and Methods We conducted a prospective observation pilot study on adult patients undergoing anterior temporal lobectomy and amygdalohippocampectomy for epilepsy. Anesthesia management was standardized in all patients, and they were allowed to wake up with “no touch” technique. Primary outcome of the study was the pattern of emergence (normal emergence, agitated emergence, or slow emergence) from anesthesia. Secondary outcomes were to explore the differences in preoperative neuropsychological profile and limbic structure volumes between the different patterns of emergence. Quantitative variables were analyzed using Student's t-test. Qualitative variables were analyzed using chi-square test. Results Twenty-nine patients completed the study: 9 patients (31%) had agitated emergence, and 20 patients had normal emergence. Among the agitated emergence, 2 patients had Riker scale of 7 indicating violent emergence. Patient demographics, anesthetic used, neuropsychological profile, and limbic structure volumes were similar between normal emergence and agitated emergence groups. However, two patients who had severe agitation (Riker scale of 7) had the lowest intelligence quotient. Conclusion Our pilot study showed that emergence agitation is not uncommon in patients undergoing epilepsy surgery. However, due to smaller sample size, the role of preoperative neuropsychologic profile and hippocampal volumes in predicting the pattern of emergence is inconclusive.

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)0.000
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 score0.041
Threshold uncertainty score0.860

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.146
GPT teacher head0.345
Teacher spread0.199 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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