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Midazolam Metabolism: Implications for Individualised Dosing?

2009· article· en· W2159886469 on OpenAlexaff
Jason A. Roberts, M G Coulthard, Russell S. Addison, Carole Foot, Jeffrey Lipman

Bibliographic record

VenueJournal of Pharmacy Practice and Research · 2009
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Sedative Agents
Canadian institutionsCentre for Drug Research and Development
Fundersnot available
KeywordsMidazolamMedicineDosingInterquartile rangeSedationPharmacokineticsMetaboliteUrineProspective cohort studyAnesthesiaSedativePharmacologyInternal medicine

Abstract

fetched live from OpenAlex

ABSTRACT Aim To compare the clearance of midazolam and its metabolites in critically ill paediatric and adult patients. Method A prospective study conducted in paediatric and adult intensive care units. Patients over 2 years of age receiving midazolam for therapeutic sedation were eligible for enrolment. Midazolam and its metabolite concentrations were determined in plasma and urine. Results The median (interquartile range) steady‐state concentrations observed in the paediatric and adult groups were 90 mg/L (48–135) and 253 mg/L (148–404), respectively (p = 0.90). The median daily doses were 1.8 mg/kg (0.6–2.2) and 1.9 mg/kg (0.6–2.7), respectively (p = 0.84). Midazolam clearance in paediatric and adult patients was 1.1 mL/kg/min (0.9–3.8) and 2.9 mL/kg/min (0.9–3.8), respectively. Analysis of clearances by age identified two peaks in midazolam and its metabolites occurring around 12 years of age and at 45 years of age. Neither midazolam nor its metabolites appeared to accumulate in blood after long courses of treatment (> 3 days). Conclusion A conclusion that could be drawn from this study is that some of midazolam's pharmacokinetic variability may be explained by age‐related changes in metabolism. These findings require validation in a larger study.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.720
Threshold uncertainty score0.230

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.209
GPT teacher head0.538
Teacher spread0.329 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations3
Published2009
Admission routes1
Has abstractyes

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