Dataset Information

Model-informed precision dosing of beta-lactam antibiotics and ciprofloxacin in critically ill patients: a multicentre randomised clinical trial.

ABSTRACT:

Purpose

Individualising drug dosing using model-informed precision dosing (MIPD) of beta-lactam antibiotics and ciprofloxacin has been proposed as an alternative to standard dosing to optimise antibiotic efficacy in critically ill patients. However, randomised clinical trials (RCT) on clinical outcomes have been lacking.

Methods

This multicentre RCT, including patients admitted to the intensive care unit (ICU) who were treated with antibiotics, was conducted in eight hospitals in the Netherlands. Patients were randomised to MIPD with dose and interval adjustments based on monitoring serum drug levels (therapeutic drug monitoring) combined with pharmacometric modelling of beta-lactam antibiotics and ciprofloxacin. The primary outcome was ICU length of stay (LOS). Secondary outcomes were ICU mortality, hospital mortality, 28-day mortality, 6-month mortality, delta sequential organ failure assessment (SOFA) score, adverse events and target attainment.

Results

In total, 388 (MIPD n = 189; standard dosing n = 199) patients were analysed (median age 64 [IQR 55-71]). We found no significant differences in ICU LOS between MIPD compared to standard dosing (10 MIPD vs 8 standard dosing; IRR = 1.16; 95% CI 0.96-1.41; p = 0.13). There was no significant difference in target attainment before intervention at day 1 (T1) (55.6% MIPD vs 60.9% standard dosing; p = 0.24) or at day 3 (T3) (59.5% vs 60.4%; p = 0.84). There were no significant differences in other secondary outcomes.

Conclusions

We could not show a beneficial effect of MIPD of beta-lactam antibiotics and ciprofloxacin on ICU LOS in critically ill patients. Our data highlight the need to identify other approaches to dose optimisation.

SUBMITTER: Ewoldt TMJ

PROVIDER: S-EPMC9645317 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Publications

Model-informed precision dosing of beta-lactam antibiotics and ciprofloxacin in critically ill patients: a multicentre randomised clinical trial.

Ewoldt Tim M J TMJ Abdulla Alan A Rietdijk Wim J R WJR Muller Anouk E AE de Winter Brenda C M BCM Hunfeld Nicole G M NGM Purmer Ilse M IM van Vliet Peter P Wils Evert-Jan EJ Haringman Jasper J Draisma Annelies A Rijpstra Tom A TA Karakus Attila A Gommers Diederik D Endeman Henrik H Koch Birgit C P BCP

Intensive care medicine 20221109 12

<h4>Purpose</h4>Individualising drug dosing using model-informed precision dosing (MIPD) of beta-lactam antibiotics and ciprofloxacin has been proposed as an alternative to standard dosing to optimise antibiotic efficacy in critically ill patients. However, randomised clinical trials (RCT) on clinical outcomes have been lacking.<h4>Methods</h4>This multicentre RCT, including patients admitted to the intensive care unit (ICU) who were treated with antibiotics, was conducted in eight hospitals in ...[more]

PMID: 36350354

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Project description:IntroductionAntibiotic dosing in critically ill patients is challenging because their pharmacokinetics (PK) are altered and may change rapidly with disease progression. Standard dosing frequently leads to inadequate PK exposure. Therapeutic drug monitoring (TDM) offers a potential solution but requires sampling and PK knowledge, which delays decision support. It is our philosophy that antibiotic dosing support should be directly available at the bedside through deep integration into the electronic health record (EHR) system. Therefore we developed AutoKinetics, a clinical decision support system (CDSS) for real time, model informed precision antibiotic dosing.ObjectiveTo provide a detailed description of the design, development, validation, testing, and implementation of AutoKinetics.MethodsWe created a development framework and used workflow analysis to facilitate integration into popular EHR systems. We used a development cycle to iteratively adjust and expand AutoKinetics functionalities. Furthermore, we performed a literature review to select and integrate pharmacokinetic models for five frequently prescribed antibiotics for sepsis. Finally, we tackled regulatory challenges, in particular those related to the Medical Device Regulation under the European regulatory framework.ResultsWe developed a SQL-based relational database as the backend of AutoKinetics. We developed a data loader to retrieve data in real time. We designed a clinical dosing algorithm to find a dose regimen to maintain antibiotic pharmacokinetic exposure within clinically relevant safety constraints. If needed, a loading dose is calculated to minimize the time until steady state is achieved. Finally, adaptive dosing using Bayesian estimation is applied if plasma levels are available. We implemented support for five extensively used antibiotics following model development, calibration, and validation. We integrated AutoKinetics into two popular EHRs (Metavision, Epic) and developed a user interface that provides textual and visual feedback to the physician.ConclusionWe successfully developed a CDSS for real time model informed precision antibiotic dosing at the bedside of the critically ill. This holds great promise for improving sepsis outcome. Therefore, we recently started the Right Dose Right Now multi-center randomized control trial to validate this concept in 420 patients with severe sepsis and septic shock.

Project description:Study objectiveMinimizing the duration of broad-spectrum antimicrobial exposure in the critically ill is a commonly used strategy aimed at preventing resistance. Our objective was to correlate the duration of exposure to antipseudomonal β-lactam antibiotics with the development of new resistance in critically ill patients.DesignSingle-center, retrospective cohort study.SettingA large, academic, tertiary care hospital.PatientsA total of 7118 adults with a discharge diagnosis of severe sepsis or septic shock who received at least one dose of cefepime, meropenem, or piperacillin-tazobactam during their hospitalization between 2010 and 2015.Measurements and main resultsCohort entry was defined as the first day of any antipseudomonal β-lactam initiation, and exposure was defined as the cumulative days of any antipseudomonal β-lactam exposure during the 60-day follow-up period. The primary outcome was development of new resistance to any antipseudomonal β-lactam > 3 days after cohort entry. New resistance was defined as detection of resistance to any antipseudomonal β-lactam not identified within 180 days before cohort entry. Patients without an outcome (i.e., did not develop new resistance) or who died by day 60 were censored. Cox proportional hazards models were performed to assess the risk of development of new resistance to any antipseudomonal β-lactam with each additional day of exposure. Analyses of each individual antipseudomonal β-lactam were evaluated as secondary outcomes. Each additional day of exposure to any antipseudomonal β-lactam resulted in an adjusted hazard ratio (aHR) of 1.04 (95% confidence interval [CI] 1.04-1.05) for new resistance development. The risk of developing new resistance to cefepime, meropenem, and piperacillin-tazobactam for each additional day of exposure resulted in an aHR of 1.08 (95% CI 1.07-1.09), 1.02 (95% CI 1.01-1.03), and 1.08 (95% CI 1.06-1.09), respectively.ConclusionAmong critically ill patients who receive antipseudomonal β-lactam antibiotics, each additional day of exposure to cefepime, meropenem, and piperacillin-tazobactam is associated with an increased risk of new resistance development.

Dataset Information

Model-informed precision dosing of beta-lactam antibiotics and ciprofloxacin in critically ill patients: a multicentre randomised clinical trial.

Purpose

Methods

Results

Conclusions

Publications

Model-informed precision dosing of beta-lactam antibiotics and ciprofloxacin in critically ill patients: a multicentre randomised clinical trial.

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