Ketofol (Ketamine-Propofol) in Pediatric Awake Neurosurgery: An Anesthetic Perspective
Bibliographic record
Abstract
Awake neurosurgical procedures for brain tumor resections are uncommon in the pediatric population, and careful consideration is required regarding the patient's cognitive maturity, emotional readiness, and ability to cooperate throughout the intraoperative mapping process. The functional significance of the tumor location may demand precise neurological monitoring, while minimizing sedation to maintain patient responsiveness during cortical stimulation and language testing. We present the case of a 14-year-old patient who was diagnosed with a left temporal lobe tumor. Neuroimaging revealed a lesion with radiological characteristics and clinical correlation highly suggestive of a low-grade glioma. The tumor was situated within the dominant hemisphere, near eloquent cortical regions critically involved in language processing and memory function. These anatomical considerations posed a significant challenge to achieving maximal resection while minimizing the risk of neurological deficits. After thorough multidisciplinary discussion, the neurosurgical team opted for an awake craniotomy. This approach was chosen to facilitate intraoperative cortical and subcortical functional mapping, allowing real-time monitoring of language and cognitive functions. The primary objective was to achieve the greatest possible extent of safe tumor resection while preserving essential neurological functions and ensuring the patient's long-term quality of life. Anesthetic management of this patient was particularly challenging, as intraoperative seizures were a major concern due to both the tumor's cortical irritability and the stimulation required for functional mapping. We administered a combination of propofol and ketamine (ketofol) to provide monitored anesthesia care during the procedure. Preoperative planning included seizure prophylaxis, clear communication with the neurosurgical and neuropsychology teams, and the development of contingency strategies for airway management in the event that conversion to general anesthesia became necessary. This case underscores the complexity of pediatric awake craniotomy and highlights the importance of a multidisciplinary, individualized approach to optimize patient safety and surgical outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".