Clinical Pharmacokinetic Monitoring of Midazolam in Critically Ill Patients
Bibliographic record
Abstract
Midazolam is a commonly used sedative in critically ill, mechanically ventilated patients in intensive care unit (ICU) settings worldwide. We used a nine-step decision-making algorithm to determine whether therapeutic monitoring of midazolam in the ICU is warranted. Midazolam has a higher clearance and shorter half-life than other benzodiazepines, and prolonged sedation is achieved with continuous infusion. There appears to be very good correlation between plasma concentrations of both midazolam and its active metabolite, alpha1-hydroxymidazolam, and the degree of sedation. However, due to high interpatient variability, it is not possible to predict the level of sedation in any given individual based on plasma concentration of midazolam or its metabolites. Moreover, no simple and practical assay is available to quantitate midazolam plasma concentrations in the acute ICU setting. Many scales are available to assess the sedative effects of midazolam. Because the plasma concentration of midazolam required to achieve a constant level of sedation is highly variable, it is usually more prudent for the clinician to monitor for sedation with a validated clinical scale than by plasma concentrations alone. Various physiologic parameters, including age-related effects, compromised renal function, and liver dysfunction affect the pharmacokinetics of midazolam and alpha1-hydroxymidazolam. Although routine drug monitoring for all critically ill patients receiving midazolam is not recommended, this practice is likely beneficial in patients with neurologic damage in whom sedation cannot be assessed and in patients who have renal failure with a prolonged time to awakening.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".