Anesthesia for the Pregnant Patient Undergoing Intracranial Procedures
Bibliographic record
Abstract
This focused review explores the current literature on anesthetic care of pregnant patients requiring intracranial intervention. Neuropathology in pregnancy is rare, and existing evidence for management remains limited by the ethical complexities surrounding maternal and fetal research-related risks; pregnant women are typically excluded from randomized controlled trials. Physiological changes during pregnancy, combined with additional fetal considerations, alter pharmacodynamics and complicate the safety profile of maternal interventions. This review highlights the complex interplay between the physiological changes of pregnancy and common neuropathologies in this patient population. Up-to-date strategies for managing elevated maternal intracranial pressure, appropriate timing of delivery relative to neurosurgical intervention, and key medications in neuro-interventional and obstetrical care are described. The appropriateness of imaging, current evidence in stroke management, and consideration for neuraxial anesthesia and awake surgery in pregnant patients are also addressed. Emphasis is placed on the importance of multidisciplinary collaboration to ensure safe, patient-centered care tailored to neuropathology, gestational age, and clinical status. Despite recent advances, significant gaps in evidence persist. Further research from large retrospective or observational data sets is recommended to improve evidence-based approaches for managing this complex and uncommon patient population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".