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Record W4224255819 · doi:10.3389/fonc.2022.885164

Benzodiazepine Sedation and Postoperative Neurological Deficits after Awake Craniotomy for Brain Tumor – An Exploratory Retrospective Cohort Study

2022· article· en· W4224255819 on OpenAlexaff
Eric Plitman, Tumul Chowdhury, Gabriel Paquin-Lanthier, Hirokazu Takami, Sudhakar Subramaniam, KW Leong, Abigail Daniels, Mark Bernstein, Lashmi Venkatraghavan

Bibliographic record

VenueFrontiers in Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineSedationAnesthesiaMidazolamCraniotomyBenzodiazepineCohortRetrospective cohort studyBrain tumorSurgeryInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

An awake craniotomy is a common neurosurgical procedure for excising brain tumor(s) located near or in eloquent areas. The use of benzodiazepine (BZD) for sedation in some patients with neuropathological conditions (e.g., stroke, brain tumors) has been previously linked with re-appearance of neurological deficits including limb incoordination, ataxia, and motor weakness, resulting in complications for the patient along with procedural challenges. Whether or not these findings can be extrapolated to patients undergoing brain tumor resection is largely unknown. The current work primarily sought to compare neurological outcome(s) in the immediate postoperative period between BZD-free and BZD-based sedation techniques in patients undergoing awake craniotomy. Using a database composed of awake craniotomies conducted within a single center and by a single surgeon, patients were retrospectively classified based on midazolam administration into BZD-free sedation (n=125) and BZD-based sedation (n=416) groups. Patients from each group were matched based on age, sex, tumor location, tumor grade, preoperative neurological deficits, non-operative BZD use, and Karnofsky Performance Scale scores, resulting in 108 patients within each group. Postoperative neurological deficits were recorded. Logistic regression analyses were conducted comparing postoperative neurological deficits between the matched groups. Postoperative neurological deficits were more prevalent within the BZD-based sedation group compared to the BZD-free sedation group (adjusted odds ratio (aOR)=1.903, 95% CI=1.018-3.560, p=0.044). In addition, subgroup analysis of the matched cohort showed a relationship between preoperative neurological symptoms and postoperative neurological deficits in the BZD-based sedation group (aOR=3.756, 95% CI=1.390-10.147, p=0.009). Our findings support the notion that the increased incidence of postoperative neurological deficits with BZD sedation may in part be related to the unmasking of preoperative neurological deficits. Further studies are required to confirm this phenomenon.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.014
GPT teacher head0.290
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), 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
Published2022
Admission routes1
Has abstractyes

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