RESUMO
WHAT IS KNOWN AND OBJECTIVE?: The latest published guidelines advocate for the area under the concentration-time curve to minimal inhibitory concentration (AUC0-24h /MIC) estimated with bayesian calculations. This recommended pharmacokinetic monitoring transition is not based on randomized controlled prospective data. METHODS: In this open-label feasibility RCT, patients were assigned to have their vancomycin dosing adjusted based on bayesian-guided AUC0-24h /MIC or trough levels. Primary outcomes were consent rate, number of patients recruited per month, compliance with blood sampling schedule and compliance with bayesian software recommendations. Secondary outcomes focused on target attainment, safety and operational impacts. RESULTS AND DISCUSSION: Forty-five patients underwent randomization (23 bayesian, 22 trough). Consent rate was 37,5% for an average of 9.8 patients recruited per month meeting pre-specified objectives of 30% (p = 0.073) and 10 (p = 0.74) respectively. A 74.8% compliance with blood sampling schedule was below the pre-specified objective of 80% (p = 0.038). There was no statistically significant difference between the 83.7% compliance with bayesian software recommendations and the pre-specified objective of 90% (p = 0.21). Although exploratory, key clinical results were significant increases in the bayesian group for proportion of levels at target (RR 1.32; 95% CI 1.01-1.72; P = 0.038), number of blood samplings for patients (p = 0.036) and pharmacists' time spent on monitoring (p < 0.0001). A tendency towards a reduced incidence of nephrotoxicity in the Bayesian group was observed (RR 0.57; 95% CI 0.16-2.12; p = 0.46). WHAT IS NEW AND CONCLUSIONS?: This trial demonstrates that it would be feasible to conduct a properly sized RCT comparing vancomycin Bayesian-guided AUC0-24h /MIC to trough level monitoring. Although exploratory, this trial also showed a tendency towards reduced incidence of nephrotoxicity and an increased proportion of dosages at therapeutic targets with Bayesian monitoring.
Assuntos
Antibacterianos , Vancomicina , Humanos , Estudos de Viabilidade , Teorema de Bayes , Estudos Prospectivos , Área Sob a Curva , Testes de Sensibilidade Microbiana , Estudos RetrospectivosRESUMO
BACKGROUND: Behavioural disturbances such as agitation are common following traumatic brain injury and can interfere with treatments, cause self-harm and delay rehabilitation. As there is a lack of evidence on the optimal approach to manage agitation in recovering TBI patients, various pharmacological agents are used including antipsychotics, anticonvulsants and sedative agents. Among sedatives, the safety and efficacy of dexmedetomidine to control agitation in traumatic brain injury patients is not well documented. OBJECTIVE: To describe the safety, use and efficacy of dexmedetomidine for the management of agitation following traumatic brain injury in the intensive care unit. METHODS: Medical records of all patients admitted to the intensive care unit of the Hôpital Sacré-Coeur de Montréal for a traumatic brain injury who received dexmedetomidine for agitation between 1 January 2017 and 31 December 2017 were reviewed. Patients who received dexmedetomidine for indications other than agitation were excluded. Data on dexmedetomidine prescription practices and safety were extracted. Frequency of agitation and concomitant psychoactive medication use was explored over a period starting two days prior to the initiation of dexmedetomidine to six days after or discontinuation, whichever came first. RESULTS: We identified 41 patients in whom dexmedetomidine was initiated. Dexmedetomidine was started on median ICU day 3 (25th -75th percentiles: 2-7) and had a median treatment duration of 3 days (25th -75th percentiles: 3-6) and a mean average rate of 0.62 mcg/kg/h (SD 0.25). Although hypotension (76%) and bradycardia (54%) were common, only one patient required intervention. The proportion of patients with at least one episode of agitation decreased from 100% on day 0, to 88%, 69% and 63% on days 1, 2 and 3 of dexmedetomidine, respectively. The decrease was statistically significant difference between days 0 and 2 as well as between days 0 and 3. Concomitant use of propofol and benzodiazepines also decreased over the course of dexmedetomidine treatment. CONCLUSION: Dexmedetomidine use was safe and associated with a reduction in agitation in traumatic brain injury patients in the 96 hours following its initiation.
Assuntos
Sintomas Comportamentais/tratamento farmacológico , Sintomas Comportamentais/etiologia , Lesões Encefálicas Traumáticas/complicações , Dexmedetomidina/uso terapêutico , Hipnóticos e Sedativos/uso terapêutico , Adulto , Fatores Etários , Idoso , Idoso de 80 Anos ou mais , Antipsicóticos/administração & dosagem , Benzodiazepinas/administração & dosagem , Peso Corporal , Lesões Encefálicas Traumáticas/epidemiologia , Comorbidade , Estado Terminal , Dexmedetomidina/efeitos adversos , Quimioterapia Combinada , Feminino , Escala de Coma de Glasgow , Humanos , Hipnóticos e Sedativos/efeitos adversos , Unidades de Terapia Intensiva , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Fatores Sexuais , Transtornos Relacionados ao Uso de Substâncias/epidemiologia , Índices de Gravidade do TraumaRESUMO
INTRODUCTION: Based on the recent guidelines for vancomycin therapeutic drug monitoring (TDM), the area under the curve to minimum inhibitory concentration ratio was to be employed combined with the usage of population pharmacokinetic (popPK) model for dosing adaptation. Yet, deploying these models in a clinical setting requires an external evaluation of their performance. OBJECTIVES: This study aimed to evaluate existing vancomycin popPK models from the literature for the use in TDM within the general patient population in a clinical setting. METHODS: The models under external evaluation were chosen based on a review of literature covering vancomycin popPK models developed in general adult populations. Patients' data were collected from Charles-Le Moyne Hospital (CLMH). The external evaluation was performed with NONMEM® (v7.5). Additional analyses such as evaluating the impact of number of samples on external evaluation, Bayesian forecasting, and a priori dosing regimen simulations were performed on the best performing model. RESULTS: Eight popPK models were evaluated with an independent dataset that included 40 patients and 252 samples. The model developed by Goti and colleagues demonstrated superior performance in diagnostic plots and population predictive performance, with bias and inaccuracy values of 0.251% and 22.7%, respectively, and for individual predictive performance, bias and inaccuracy were -4.90% and 12.1%, respectively. When limiting the independent dataset to one or two samples per patient, the Goti model exhibited inadequate predictive performance for inaccuracy, with values exceeding 30%. Moreover, the Goti model is suitable for Bayesian forecasting with at least two samples as prior for the prediction of the next trough concentration. Furthermore, the vancomycin dosing regimen that would maximize therapeutic targets of area under the curve to minimum inhibitory concentration ratio (AUC24/MIC) and trough concentrations (Ctrough) for the Goti model was 20 mg/kg/dose twice daily. CONCLUSION: Considering the superior predictive performance and potential for Bayesian forecasting in the Goti model, future research aims to test its applicability in clinical settings at CLMH, both in a priori and a posteriori scenario.