Impact of the introduction of real-time therapeutic drug monitoring on empirical doses of carbapenems in critically ill burn patients.

PURPOSE: Adequate empirical antibiotic dose selection for critically ill burn patients is difficult due to extreme variability in drug pharmacokinetics. Therapeutic drug monitoring (TDM) may aid antibiotic prescription and implementation of initial empirical antimicrobial dosage recommendations. This study evaluated how gradual TDM introduction altered empirical dosages of meropenem and imipenem/cilastatin in our burn ICU. METHODS: Imipenem/cilastatin and meropenem use and daily empirical dosage at a five-bed burn ICU were analyzed retrospectively. Data for all burn admissions between 2001 and 2011 were extracted from the hospital's computerized information system. For each patient receiving a carbapenem, episodes of infection were reviewed and scored according to predefined criteria. Carbapenem trough serum levels were characterized. Prior to May 2007, TDM was available only by special request. Real-time carbapenem TDM was introduced in June 2007; it was initially available weekly and has been available 4 days a week since 2010. RESULTS: Of 365 patients, 229 (63%) received antibiotics (109 received carbapenems). Of 23 TDM determinations for imipenem/cilastatin, none exceeded the predefined upper limit and 11 (47.8%) were insufficient; the number of TDM requests was correlated with daily dose (r=0.7). Similar numbers of inappropriate meropenem trough levels (30.4%) were below and above the upper limit. Real-time TDM introduction increased the empirical dose of imipenem/cilastatin, but not meropenem. CONCLUSIONS: Real-time carbapenem TDM availability significantly altered the empirical daily dosage of imipenem/cilastatin at our burn ICU. Further studies are needed to evaluate the individual impact of TDM-based antibiotic adjustment on infection outcomes in these patients.

Implementation of bayesian therapeutic drug monitoring in modern patient care

The variability observed in drug exposure has a direct impact on the overall response to drug. The largest part of variability between dose and drug response resides in the pharmacokinetic phase, i.e. in the dose-concentration relationship. Among possibilities offered to clinicians, Therapeutic Drug Monitoring (TDM; Monitoring of drug concentration measurements) is one of the useful tool to guide pharmacotherapy. TDM aims at optimizing treatments by individualizing dosage regimens based on blood drug concentration measurement. Bayesian calculations, relying on population pharmacokinetic approach, currently represent the gold standard TDM strategy. However, it requires expertise and computational assistance, thus limiting its large implementation in routine patient care. The overall objective of this thesis was to implement robust tools to provide Bayesian TDM to clinician in modern routine patient care. To that endeavour, aims were (i) to elaborate an efficient and ergonomic computer tool for Bayesian TDM: EzeCHieL (ii) to provide algorithms for drug concentration Bayesian forecasting and software validation, relying on population pharmacokinetics (iii) to address some relevant issues encountered in clinical practice with a focus on neonates and drug adherence. First, the current stage of the existing software was reviewed and allows establishing specifications for the development of EzeCHieL. Then, in close collaboration with software engineers a fully integrated software, EzeCHieL, has been elaborated. EzeCHieL provides population-based predictions and Bayesian forecasting and an easy-to-use interface. It enables to assess the expectedness of an observed concentration in a patient compared to the whole population (via percentiles), to assess the suitability of the predicted concentration relative to the targeted concentration and to provide dosing adjustment. It allows thus a priori and a posteriori Bayesian drug dosing individualization. Implementation of Bayesian methods requires drug disposition characterisation and variability quantification trough population approach. Population pharmacokinetic analyses have been performed and Bayesian estimators have been provided for candidate drugs in population of interest: anti-infectious drugs administered to neonates (gentamicin and imipenem). Developed models were implemented in EzeCHieL and also served as validation tool in comparing EzeCHieL concentration predictions against predictions from the reference software (NONMEM®). Models used need to be adequate and reliable. For instance, extrapolation is not possible from adults or children to neonates. Therefore, this work proposes models for neonates based on the developmental pharmacokinetics concept. Patients' adherence is also an important concern for drug models development and for a successful outcome of the pharmacotherapy. A last study attempts to assess impact of routine patient adherence measurement on models definition and TDM interpretation. In conclusion, our results offer solutions to assist clinicians in interpreting blood drug concentrations and to improve the appropriateness of drug dosing in routine clinical practice.

Establishment of a Representative Practice-based Research Network (PBRN) for the Monitoring of Primary Care in Switzerland.

Data are urgently needed to better understand processes of care in Swiss primary care (PC). A total of 2027 PC physicians, stratified by canton, were invited to participate in the Swiss Primary care Active Monitoring network, of whom 200 accepted to join. There were no significant differences between participants and a random sample drawn from the same physician databases based on sex, year of obtaining medical school diploma, or location. The Swiss Primary care Active Monitoring network represents the first large-scale, nationally representative practice-based research network in Switzerland and will provide a unique opportunity to better understand the functioning of Swiss PC.

Therapeutic drug monitoring of targeted anticancer therapy.

New oral targeted anticancer therapies are revolutionizing cancer treatment by transforming previously deadly malignancies into chronically manageable conditions. Nevertheless, drug resistance, persistence of cancer stem cells, and adverse drug effects still limit their ability to stabilize or cure malignant diseases in the long term. Response to targeted anticancer therapy is influenced by tumor genetics and by variability in drug concentrations. However, despite a significant inter-patient pharmacokinetic variability, targeted anticancer drugs are essentially licensed at fixed doses. Their therapeutic use could however be optimized by individualization of their dosage, based on blood concentration measurements via the therapeutic drug monitoring (TDM). TDM can increase the probability of therapeutic responses to targeted anticancer therapies, and would help minimize the risk of major adverse reactions.

Blood monitoring of perfluorocarbon compounds (F-tert-butylcyclohexane, perfluoromethyldecalin and perfluorodecalin) by headspace-gas chromatography-tandem mass spectrometry.

A headspace-gas chromatography-tandem mass spectrometry (HS-GC-MS/MS) method for the trace measurement of perfluorocarbon compounds (PFCs) in blood was developed. Due to oxygen carrying capabilities of PFCs, application to doping and sports misuse is speculated. This study was therefore extended to perform validation methods for F-tert-butylcyclohexane (Oxycyte(®)), perfluoro(methyldecalin) (PFMD) and perfluorodecalin (PFD). The limit of detection of these compounds was established and found to be 1.2µg/mL blood for F-tert-butylcyclohexane, 4.9µg/mL blood for PFMD and 9.6µg/mL blood for PFD. The limit of quantification was assumed to be 12µg/mL blood (F-tert-butylcyclohexane), 48µg/mL blood (PFMD) and 96µg/mL blood (PFD). HS-GC-MS/MS technique allows detection from 1000 to 10,000 times lower than the estimated required dose to ensure a biological effect for the investigated PFCs. Thus, this technique could be used to identify a PFC misuse several hours, maybe days, after the injection or the sporting event. Clinical trials with those compounds are still required to evaluate the validation parameters with the calculated estimations.

Measurement Properties of the Smartphone-Based B-B Score in Current Shoulder Pathologies.

NlmCategory="UNASSIGNED">This study is aimed at the determination of the measurement properties of the shoulder function B-B Score measured with a smartphone. This score measures the symmetry between sides of a power-related metric for two selected movements, with 100% representing perfect symmetry. Twenty healthy participants, 20 patients with rotator cuff conditions, 23 with fractures, 22 with capsulitis, and 23 with shoulder instabilities were measured twice across a six-month interval using the B-B Score and shoulder function questionnaires. The discriminative power, responsiveness, diagnostic power, concurrent validity, minimal detectable change (MDC), minimal clinically important improvement (MCII), and patient acceptable symptom state (PASS) were evaluated. Significant differences with the control group and significant baseline-six-month differences were found for the rotator cuff condition, fracture, and capsulitis patient groups. The B-B Score was responsive and demonstrated excellent diagnostic power, except for shoulder instability. The correlations with clinical scores were generally moderate to high, but lower for instability. The MDC was 18.1%, the MCII was 25.2%, and the PASS was 77.6. No floor effect was observed. The B-B Score demonstrated excellent measurement properties in populations with rotator cuff conditions, proximal humerus fractures, and capsulitis, and can thus be used as a routine test to evaluate those patients.