Trial reportEuropean journal of clinical pharmacology2012
Influence of real-time Bayesian forecasting of pharmacokinetic parameters on the precision of a rocuronium target-controlled infusion.
Trial report in European journal of clinical pharmacology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Propofol Breath Monitoring as a Potential Tool to Improve the Prediction of Intraoperative Plasma Concentrations.Clinical pharmacokinetics · 2016Trial
- Bayesian statistics in anesthesia practice: a tutorial for anesthesiologists.Journal of anesthesia · 2022Review
- Machine Learning, Deep Learning, and Closed Loop Devices-Anesthesia Delivery.Anesthesiology clinics · 2021Review
- Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations.Anesthesiology · 2020Review
- Pharmacokinetic-pharmacodynamic relationship of anesthetic drugs: from modeling to clinical use.F1000Research · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionBayesian forecasting has been shown to improve the accuracy of pharmacokinetic/pharmacodynamic (PK/PD) models by adding measured values to a population model. It could be done in real time for neuromuscular blockers (NMB) using measured values of effect. This study was designed to assess feasibility and benefit of Bayesian forecasting during a rocuronium target-controlled infusion (TCI).
methodsAfter internal review board (IRB) approval and informed consent, 21 women scheduled for breast plastic surgery were included. Anesthesia was maintained with propofol, alfentanil, and controlled ventilation through a laryngeal mask. Rocuronium was delivered in TCI with Stanpump software and the Plaud population model. The target effect was 50% blockade until insertion of breast prosthesis; thereafter it was set to 0%. Response to train of four (TOF) at adductor pollicis was recorded using a force transducer. In ten patients, drug delivery was based on the population model. In the others, repeated measures values were entered in the software, and the PK model was adjusted to minimize the error in predicted effect. Model precision was compared between groups using mean prediction error and mean absolute prediction error.
resultsAt target 50%, model accuracy was not improved with Bayesian adjustments; conversely, post-infusion errors were significantly decreased. The first two measures had the most influence on the model changes. DISCUSSION: Below clinical utility, such adjustments may be used to explore cofactors influencing interindividual and intraindividual variability in NMB dose-response relationship. Similar tools may also be developed for drugs in which a quantitative effect is available, such as electroencephalography (EEG) for hypnotics. IMPLICATION: Real-time Bayesian forecasting combining measured values of effect with a population model is suitable to guide NMB-agent delivery using Stanpump software.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.