MétaCan
Menu
Back to cohort
Record W2404441765 · doi:10.1093/neuonc/nov223.09

NCO-09THE EFFICACY OF THERAPEUTIC DISCOURSE ANALYSIS DURING BRAIN TUMOUR RESECTION IN AWAKE CRANIOTOMIES

2015· article· en· W2404441765 on OpenAlexaff
Shannon Milburn, Marco M. Garavaglia, Gregory M. T. Hare, Andrea Rigamonti, Catriona Kelly, Melanie A. Morrison, Simon J. Graham, Sunit Das

Bibliographic record

VenueNeuro-Oncology · 2015
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsSunnybrook HospitalUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineAnestheticHemiparesisResectionSurgical teamAnesthesiaSurgery

Abstract

fetched live from OpenAlex

Intraoperative brain mapping techniques are utilized in neuro-oncology to maximize the extent of tumor resection, seizure control, and minimize operative morbidity.1 The advancement of our understanding of speech, language and oral motor movement has facilitated the application of progressively sophisticated methods of assessing higher level function intra-operatively. An anesthetic approach that does not require airway manipulation2 was used, thereby optimizing brain mapping conditions as well as the patient's ability to participate in therapeutic discourse tasks during brain tumour resection. With REB approval and informed consent, case-reviews were performed for five patients who had undergone awake re-do craniotomies. The standardized anesthetic protocol was based on the scalp block and dexmedetomidine infusion as the primary anesthetic agent.2 The SLP completed a preoperative assessment, brain mapping with the surgical team, ongoing therapeutic discourse during tumour resection and a postoperative assessment. All five patients had successful resection of the tumour. In each case, the SLP provided a systematic evaluation of speech, language, oral motor, and cognitive communication function. The surgical team identified that real-time speech assessment directed the surgical plan, not only during brain mapping but also during tumour resection facilitating optimal tumour resection and the preservation of eloquent cortex. Three patients demonstrated speech arrest during tumour resection in an area that was mapped to be safe and two patients had seizures. These deficits would not have been appreciated had tumour resection been performed with the patient sedated post brain mapping or if an anesthetic technique with instrumented airway was used. All patients scored equal to or above their baseline scores during the postoperative assessment. The patient's assessment, preparation and an integrated team-expertise are crucial to the success of the awake craniotomy. The support of the SLP minimizes postoperative neurological sequelae by providing ongoing intraoperative assessment throughout mapping as well as brain tumour resection.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.036
GPT teacher head0.351
Teacher spread0.315 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueNeuro-OncologySame topicGlioma Diagnosis and TreatmentFrench-language works237,207