Optimization of Fluconazole Dosing for the Prevention and Treatment of Invasive Candidiasis Based on the Pharmacokinetics of Fluconazole in Critically Ill Patients.

The efficacy of fluconazole is related to the area under the plasma concentration-time curve (AUC) over the MIC of the microorganism. Physiological changes in critically ill patients may affect the exposure of fluconazole, and therefore dosing adjustments might be needed. The aim of this study was to evaluate variability in fluconazole drug concentration in intensive care unit (ICU) patients and to develop a pharmacokinetic model to support personalized fluconazole dosing. A prospective observational pharmacokinetic study was performed in critically ill patients receiving fluconazole either as prophylaxis or as treatment. The association between fluconazole exposure and patient variables was studied. Pharmacokinetic modeling was performed with a nonparametric adaptive grid (NPAG) algorithm using R package Pmetrics. Data from 33 patients were available for pharmacokinetic analysis. Patients on dialysis and solid organ transplant patients had a significantly lower exposure to fluconazole. The population was best described with a one-compartment model, where the mean volume of distribution was 51.52 liters (standard deviation [SD], 19.81) and the mean clearance was 0.767 liters/h (SD, 0.46). Creatinine clearance was tested as a potential covariate in the model, but was not included in the final population model. A significant positive correlation was found between the fluconazole exposure (AUC) and the trough concentration (Cmin). Substantial variability in fluconazole plasma concentrations in critically ill adults was observed, where the majority of patients were underexposed. Fluconazole Cmin therapeutic drug monitoring (TDM)-guided dosing can be used to optimize therapy in critically ill patients. (This study has been registered at ClinicalTrials.gov under identifier NCT02491151.).

Invasive Candidiasis in the Elderly: Considerations for Drug Therapy.

Candida infections in the elderly are an important and expanding clinical problem, with significantly higher mortality in this group than in younger patients. The increasing problem of invasive Candida infections may be related to higher prevalence of immunocompromised older people and the emergence of treatment resistance. Older people, especially the frail and critically ill, are at higher risk of medication-related harmful effects due to changes in pharmacokinetics and pharmacodynamics, which may be further complicated by organ dysfunction, diminished homeostatic control, co-morbidities and polypharmacy. Here, we review the available options for the treatment of Candida infections and provide insights into the challenges surrounding the optimal use of antifungal drugs in the elderly.

Consensus guidelines for optimising antifungal drug delivery and monitoring to avoid toxicity and improve outcomes in patients with haematological malignancy, 2014.

Antifungal agents may be associated with significant toxicity or drug interactions leading to sub-therapeutic antifungal drug concentrations and poorer clinical outcomes for patients with haematological malignancy. These risks may be minimised by clinical assessment, laboratory monitoring, avoidance of particular drug combinations and dose modification. Specific measures, such as the optimal timing of oral drug administration in relation to meals, use of pre-hydration and electrolyte supplementation may also be required. Therapeutic drug monitoring (TDM) of antifungal agents is warranted, especially where non-compliance, non-linear pharmacokinetics, inadequate absorption, a narrow therapeutic window, suspected drug interaction or unexpected toxicity are encountered. Recommended indications for voriconazole and posaconazole TDM in the clinical management of haematology patients are provided. With emerging knowledge regarding the impact of pharmacogenomics upon metabolism of azole agents (particularly voriconazole), potential applications of pharmacogenomic evaluation to clinical practice are proposed.

Comparing dose prediction software used to manage gentamicin dosing.

BACKGROUND: Current Australian guidelines recommend initiating directed therapy of gentamicin if administration exceeds 48 h. Directed doses of gentamicin require the monitoring of plasma concentrations of gentamicin to determine the 24-h area under the time course of plasma gentamicin concentrations (AUC) and a dosage prediction program, for example TCIWorks or Aladdin. However, doses calculated by such programs have not been compared with an established program. AIM: To compare the directed dosage of gentamicin calculated by TCIWorks, Aladdin and an Excel-based program, with an established program, Abbottbase. METHODS: Peak and trough plasma concentrations after the first and second administered doses of gentamicin were available from three patient groups (n = 20-23) with varying creatinine clearances (<40, 40-80, >80 mL/min). The directed dose needed to produce 24-h AUC values of 80 mg.h/L was calculated using each program. RESULTS: There was a strong correlation between the directed doses predicted by each of the three programs compared with Abbottbase, following the first administered dose (r(2) > 0.97, P < 0.0001). The mean ratio (90% confidence intervals) of these directed doses of the gentamicin were: TCIWorks/Abbottbase 106% (105-107%), Aladdin/Abbottbase 102% (101-103%) and Excel/Abbottbase 108% (106-109%). The correlations and dose ratios were also similar when comparisons were made following the second administered dose. For each of the three renal function groups, all programs yielded similar directed doses. CONCLUSIONS: The four programs used in the calculation of directed doses of gentamicin yielded similar results. Any would be suitable for use in clinical practice.

Candidemia following solid organ transplantation in the era of antifungal prophylaxis: the Australian experience.

Solid organ transplant (SOT) recipients have high rates of invasive fungal infections, with Candida species the most commonly isolated fungi. The aim of this study was to identify differences between incidence rates, risk factors, clinical presentations, and outcomes of candidemia in SOT recipients and non-SOT patients. Data from the multicenter prospective Australian Candidaemia Study were examined. From August 2001 to July 2004, 24 episodes (2.2%; 24/1068) of candidemia were identified in SOT recipients. During this period, the numbers of transplanted organs included liver (n=455), kidney (n=1605), single lung (n=57), bilateral lung (n=183), heart and lung (n=18), heart (n=157), and pancreas (n=62). The overall annual estimated incidence of candidemia in SOT recipients was higher (3 per 1000 transplant admissions) than in non-SOT patients (incidence 0.21 per 1000 admissions; P<0.001). The incidence and timing of candidemia post transplant was influenced by the transplanted organ type, with the majority of episodes (n=14, 54%) occurring >6 months after renal transplantation. Risk factors for candidemia in the month preceding diagnosis were similar to non-SOT recipients except for corticosteroid therapy (P<0.001). Antifungal prophylaxis did not select for more resistant or non-albicans Candida species in the SOT group. The 30-day all-cause mortality was similar to non-SOT patients with candidemia and remains high at 21%. All deaths in SOT recipients occurred early (within 5 days of diagnosis), underlining a need for better diagnostic tests, targeted prevention, and early treatment strategies.