Dexmedetomidine (DMET) is a useful agent for sedation, both alone and in combination with other agents, in critically ill patients, including those on extracorporeal membrane oxygenation (ECMO) therapy. The drug is a clonidine-like derivative with an 8-fold greater specificity for the alpha 2-receptor while maintaining respiratory and cardiovascular stability. An in vitro ECMO circuit was used to study the effects of both "new" and "old" membrane oxygenators on the clearance of dexmedetomidine over the course of 24 hours. Once primed, the circuit was dosed with 840 μg of dexmedetomidine for a final concentration of 0.9 μg/ml. Serial samples, both pre- and post-oxygenator, were taken at 5, 60, 360, and 1440 minutes. Concentrations of the drug were expressed as a percentage of the original concentration remaining at each time point, both for new and old circuits. The new circuits were run at a standard flow for 24 hours, after which time the circuit was considered old and re-dosed with dexmedetomidine and the trial repeated. Results show that dexmedetomidine losses occur early in the circuits and then continue to decline. Initial losses in the first hour were 11+-65% and 59-73% pre- and post-oxygenator in the new circuit and 36-50% and 42-72% in the old circuit. The clearance of the drug through the membrane oxygenator exhibits no statistical difference between pre and post or new and old circuits. Dexmedetomidine can be expected to exhibit concentration changes during ECMO therapy. This effect appears to be more related to adsorption to the polyvinyl chloride (PVC) tubing rather than the membrane oxygenator. Dosage adjustments during dexmedetomidine administration during ECMO therapy may be warranted in order to maintain adequate serum concentrations and, hence, the desired degree of sedation.*(Lack of equilibrium).

Objectives: The objectives of this study were to: 1) determine the association between vasopressor dosing intensity during the first 6 hours and first 24 hours after the onset of septic shock and 30-day in-hospital mortality; 2) determine whether the effect of vasopressor dosing intensity varies by fluid resuscitation volume; and 3) determine whether the effect of vasopressor dosing intensity varies by dosing titration pattern. Design: Multicenter prospective cohort study between September 2017 and February 2018. Vasopressor dosing intensity was defined as the total vasopressor dose infused across all vasopressors in norepinephrine equivalents. Setting: Thirty-three hospital sites in the United States (n = 32) and Jordan (n = 1). Patients: Consecutive adults requiring admission to the ICU with septic shock treated with greater than or equal to 1 vasopressor within 24 hours of shock onset. Interventions: None. Measurements and Main Results: Out of 1,639 patients screened, 616 were included. Norepinephrine (93%) was the most common vasopressor. Patients received a median of 3,400 mL (interquartile range, 1,851–5,338 mL) during the 24 hours after shock diagnosis. The median vasopressor dosing intensity during the first 24 hours of shock onset was 8.5 μg/min norepinephrine equivalents (3.4–18.1 μg/min norepinephrine equivalents). In the first 6 hours, increasing vasopressor dosing intensity was associated with increased odds ratio of 30-day in-hospital mortality, with the strength of association dependent on concomitant fluid administration. Over the entire 24 hour period, every 10 μg/min increase in vasopressor dosing intensity was associated with an increased risk of 30-day mortality (adjusted odds ratio, 1.33; 95% CI, 1.16–1.53), and this association did not vary with the amount of fluid administration. Compared to an early high/late low vasopressor dosing strategy, an early low/late high or sustained high vasopressor dosing strategy was associated with higher mortality. Conclusions: Increasing vasopressor dosing intensity during the first 24 hours after septic shock was associated with increased mortality. This association varied with the amount of early fluid administration and the timing of vasopressor titration.

No abstract

Antibiotic-associated diarrhea (AAD) describes any unexplained diarrhea associated with the use of an antibiotic. AAD also includes infection caused by Clostridium difficile, however this organism only accounts for a small percentage of diarrhea caused by antibiotics. AAD can be caused by multiple other organisms including C perfringens, S aureus, and Candida. Some antibiotics are more likely to cause non-C difficile AAD, such as erythromycin and the penicillin class. AAD develops through the loss of normal flora and reduced colonic bacterial carbohydrate metabolism during antibiotic administration. There is an increasing interest in the use of probiotics for the prevention of AAD. There are several meta-analyses that report a relative risk reduction of AAD with the use of probiotics during antibiotic administration. Interpretation of these studies has been challenging due to the heterogeneity and size of the patient populations, unclear probiotic regimen, and unclear safety profile. Since AAD can be a reason for a patient to become non-compliant or receive incomplete treatment, clinicians should monitor for this potential adverse effect caused by antibiotics.

Background: Phenytoin has a narrow therapeutic index and the potential of under-treatment or toxicity. Available equations are used to correct for the impact of hypoalbuminemia on unbound (free) phenytoin levels. The authors aimed to determine the accuracy of equations used to estimate free phenytoin in hospitalized patients and assess the impact of using additional clinical data. Methods: Concurrently measured total and free phenytoin levels in hospitalized patients (2014–2018) were retrospectively evaluated, excluding those from patients on renal replacement therapy and valproic acid. Differences between actual and estimated free phenytoin levels by the original (Original WTZ), Anderson-modified, and Kane-modified Winter–Tozer equations were assessed using Pearson correlations and Bland–Altman analysis. Thereafter, a population-derived formula was developed and validated in a testing cohort. Results: In the 4-year training cohort (n = 81), the Original WTZ equation had the smallest mean difference of all equations. A higher mean difference [−0.362 mcg/mL (95% CI −0.585 to −0.138) vs. −0.054 mcg/mL (95% CI −0.186 to 0.078)] was observed in intensive care unit (ICU) patients compared with non-ICU patients. A cross-validated multivariable model improved the accuracy of free phenytoin estimation in ICU and non-ICU patients, even in the separate testing cohort (n = 52) with respective mean differences of −0.322 mcg/mL (95% CI −0.545 to −0.098) and −0.025 mcg/mL (95% CI −0.379 to 0.329) and was superior to the Original WTZ [mean difference −0.858 mcg/mL (95% CI −1.069 to −0.647) vs. −0.106 mcg/mL (95% CI −0.362 to 0.151), respectively]. Conclusions: Free phenytoin levels in hospitalized patients cannot be accurately determined using available estimation equations, particularly in critically ill patients. Combining ICU status and other available clinical data can improve therapeutic drug monitoring and prevent high-magnitude errors, particularly when free phenytoin assays are not readily available.

Current fluconazole dosing strategies can be described using either standardized doses (800 or 400 mg) or as weight-based dosing recommendations (12 mg/kg loading dose followed by 6 mg/kg maintenance dose). The ideal method of fluconazole dosing is still unclear for certain patient populations, such as those receiving renal replacement therapy or the morbidly obese. We describe a 48-year-old man with a body mass index of 84 kg/m(2) who was receiving continuous venovenous hemofiltration (CVVH) and was treated with fluconazole by using a weight-based dose determined by lean body weight, infused at a rate of 200 mg/hour. Blood samples were collected at hour 0 (i.e., ~24 hrs after the loading dose was administered) and at 3.5, 6.8, and 11.3 hours after the start of the 600-mg maintenance dose, infused over 3 hours. Pharmacokinetic parameters calculated were maximum serum concentration 9.64 mg/L, minimum serum concentration 5.98 mg/L, area under the serum concentration-time curve from 0-24 hours (AUC0-24 ) 184.75 mg/L•hour, elimination rate constant 0.0199 hour(-1) , elimination half-life 34.8 hours, and total body clearance 3.25 L/hour. Our data, when combined with previously published literature, do not support using a linear dose-to-AUC approximation to estimate drug dosing needs in the critically ill patient population receiving CVVH. In addition, our results suggest that morbidly obese patients are able to achieve pharmacodynamic goals defined as an AUC:MIC ratio higher than 25 by using a lean body weight for fluconazole dosing calculations.

No abstract

No abstract