Flumazenil Reversal of Remimazolam Sedation During Posterior Spinal Fusion in Two Adolescents
Bibliographic record
Abstract
Remimazolam is a novel, ester-metabolized benzodiazepine, which received approval by the United States Food and Drug Administration (FDA) for procedural sedation in adults in 2020. Since then, its clinical uses have expanded to intraoperative use both as the primary agent or as an adjunct to general anesthesia. Although its novel route of metabolism through tissue esterases generally results in a rapid resolution of its effects when the infusion is discontinued; in certain clinical scenarios, reversal of its clinical effects may be achieved with flumazenil. We present two clinical cases outlining the use of flumazenil to reverse the effects of remimazolam, which was used as an adjunct to total intravenous anesthesia during posterior spinal fusion (PSF) in two adolescent patients. In our first case, to facilitate an intraoperative wake-up test, the clinical effects of remimazolam were reversed with flumazenil. In the second case, flumazenil reversed the residual effects of remimazolam to speed awakening and tracheal extubation at the completion of the surgical procedure. The clinical uses of remimazolam are reviewed, experience with its use as an adjunct during PSF is discussed, and the clinical role of reversal with flumazenil is presented.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".