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Record W3037381002 · doi:10.3171/2020.4.jns20378

Preoperative factors associated with adverse events during awake craniotomy: analysis of 609 consecutive cases

2020· article· en· W3037381002 on OpenAlexaffabout
Hirokazu Takami, Nikki Khoshnood, Mark Bernstein

Bibliographic record

VenueJournal of neurosurgery · 2020
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Sedative Agents
Canadian institutionsToronto Western Hospital
Fundersnot available
KeywordsMedicineCraniotomyAdverse effectAnesthesiaSedationCohortUnivariate analysisSurgeryMultivariate analysisInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Awake surgery is becoming more standard and widely practiced for neurosurgical cases, including but not limited to brain tumors. The optimal selection of patients who can tolerate awake surgery remains a challenge. The authors performed an updated cohort study, with particular attention to preoperative clinical and imaging characteristics that may have an impact on the viability of awake craniotomy in individual patients. METHODS: The authors conducted a single-institution cohort study of 609 awake craniotomies performed in 562 patients. All craniotomies were performed by the same surgeon at Toronto Western Hospital during the period from 2006 to 2018. Analyses of preoperative clinical and imaging characteristics that may have an impact on the viability of awake craniotomy in individual patients were performed. RESULTS: Twenty-one patients were recorded as having experienced intraoperative adverse events necessitating deeper sedation, which made the surgery no longer "awake." In 2 of these patients, conversion to general anesthesia was performed. The adverse events included emotional intolerance of awake surgery (n = 13), air embolism (n = 3), generalized seizure (n = 4), and unexpected subarachnoid hemorrhage (n = 1). Preoperative cognitive decline, dysphasia, and low performance status, as indicated by the Karnofsky Performance Status (KPS) score, were significantly associated with emotional intolerance on univariate analysis. Only a preoperative KPS score < 70 was significantly associated with this event on multivariate analysis (p = 0.0057). Compared with patients who did not experience intraoperative adverse events, patients who did were more likely to undergo inpatient admission (p = 0.0004 for all cases; p = 0.0036 for cases originally planned as day surgery), longer hospital stay (p < 0.0001), and discharge to a location other than home (p = 0.032). CONCLUSIONS: Preoperative physical status was found to be the most decisive factor in predicting whether patients can tolerate an awake craniotomy without complications, whereas older age and history of psychiatric treatment were not necessarily associated with adverse events. Patients who had intraoperative adverse events often had reduced chances of same-day discharge and discharge to home. Preoperative careful selection of patients who are most likely to tolerate the procedure is the key to success for awake surgery.

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)0.000
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 score0.005
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.277
Teacher spread0.216 · 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

Citations25
Published2020
Admission routes2
Has abstractyes

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