Performance of ePlex® blood culture identification panels in clinical isolates and characterization of antimicrobial stewardship opportunities.

We assessed the performance of GenMark's ePlex® Blood Culture Identification (BCID) Panels for overall agreement of organism identification and resistance mechanism detection with standard microbiologic methods. This study included patients with a positive blood culture from May 2020 to January 2021. The primary outcomes were to assess concordance of ePlex® organism identification with standard identification methods and concordance of ePlex® genotypic resistance mechanism detection with standard phenotypic susceptibility testing. Secondary outcomes included panel specific performance and characterization of antimicrobial stewardship opportunities. The overall identification concordance rate in 1276 positive blood cultures was 98.1%. The overall concordance for the presence of resistance markers was 98.2% and concordance for the absence of resistance markers was 100%. A majority of ePlex® results (69.5%) represented opportunities for potential antimicrobial stewardship intervention. High concordance rates between the ePlex® BCID panels and standard identification and susceptibility methods enable utilization of results to guide rapid antimicrobial optimization.

Effect modification of dosing strategy (AUC or trough) on AKI associated with vancomycin in combination with piperacillin/tazobactam or cefepime and meropenem.

Piperacillin-tazobactam (TZP), cefepime (FEP), or meropenem (MEM) and vancomycin (VAN) are commonly used in combination for sepsis. Studies have shown an increased risk of acute kidney injury (AKI) with TZP and VAN compared to FEP or MEM. VAN guidelines recommend area under the curve (AUC) monitoring over trough (Tr) to minimize the risk of AKI. We investigated the association of AKI and MAKE-30 with the two VAN monitoring strategies when used in combination with TZP or FEP/MEM. Adult patients between 2015 and 2019 with VAN > 72 hours were included. Patients with AKI prior to or within 48 hours of VAN or baseline CrCl of ≤30 mL/min were excluded. Four cohorts were defined: FEP/MEM/Tr, FEP/MEM/AUC, TZP/Tr, and TZP/AUC. A Cox Proportional Hazard Model was used to model AKI as a function of the incidence rate of at-risk days, testing monitoring strategy as a treatment effect modification. Multivariable logistic regression was used to model MAKE-30. Overall incidence of AKI was 18.6%; FEP/MEM/Tr = 115 (14.6%), FEP/MEM/AUC = 52 (14.9%), TZP/Tr = 189 (26%), and TZP/AUC = 96 (17.1%) (P < 0.001). Both drug group [(TZP; P = 0.0085)] and monitoring strategy [(Tr; P = 0.0007)] were highly associated with the development of AKI; however, the effect was not modified with interaction term [(TZP*Tr); 0.085)]. The odds of developing MAKE-30 were not different between any group and FEP/MEM/AUC. The effect of VAN/TZP on the development of AKI was not modified by the VAN monitoring strategy (AUC vs trough). MAKE-30 outcomes were not different among the four cohorts.

Vancomycin AUC0-24 estimation using first-order pharmacokinetic methods in pediatric patients.

INTRODUCTION: The optimal dosing and monitoring of vancomycin in pediatrics is still unknown but has evolved to emphasize area under the curve over 24 h (AUC0-24) over minimum concentration (Cmin) monitoring. Real-world data supporting the feasibility of two-concentration kinetics with first-order equations for the estimation of vancomycin AUC0-24 in pediatric patients are lacking. OBJECTIVES: To describe the interplay of vancomycin dose, AUC0-24, and Cmin using first-order equations within four pediatric age groups. METHODS: This is a single-center, retrospective cohort study analyzing pediatric patients (<18 years) receiving intravenous vancomycin between 2020 and 2022. Included patients received at least 24 h of intravenous vancomycin with two concentrations obtained within 96 h of therapy initiation. Patients with baseline renal dysfunction were excluded. Patients were divided into four age categories: neonates (≤28 days), infants (29 days to <1 year), children (1-12 years), and adolescents (13-17 years). First-order equations were utilized to estimate pharmacokinetic parameters and AUC0-24. RESULTS: Overall, 219 patients (median age of 6 years [IQR 1-12]) met inclusion criteria. The median vancomycin daily dose was 30 mg/kg in neonates, 70 mg/kg in infants and children, and 52 mg/kg in adolescents. Median Cmin and AUC0-24 values among all age groups were 8.68 mg/L and 505 mg * h/L, respectively. For AUC0-24 values outside of the therapeutic range (400-600 mg * h/L), more values were SUPRAtherapeutic (>600 mg * h/L) than SUBtherapeutic (<400 mg * h/L). The overall trend within our data showed suboptimal correlation between Cmin and AUC0-24. However, 71% of patients with Cmin values of 5-10 mg/L had an AUC0-24 within the therapeutic range of 400-600 mg * h/L, whereas 23 patients (92%) with a SUPRAtherapeutic AUC0-24 had a Cmin value ≥15 mg/L. Approximately 10% of patients experienced acute kidney injury. CONCLUSIONS: Our data describe the relationship between vancomycin dose, Cmin, and AUC0-24 in pediatric patients. We demonstrated the feasibility of using first-order equations to estimate AUC0-24, using two concentrations obtained at steady state to monitor efficacy and safety in pediatric patients receiving intravenous vancomycin. Our data showed suboptimal correlation between AUC0-24 and Cmin, which indicates that Cmin should not be used as a surrogate marker for a therapeutic AUC0-24 in pediatric patients. In alignment with the 2020 vancomycin consensus guidelines, we suggest utilizing AUC0-24 for efficacy and safety monitoring.

Association of vancomycin-induced acute kidney injury with trough versus AUC monitoring in patients receiving extended durations of therapy.

Objective: Vancomycin therapy is associated with an increased risk of acute kidney injury (AKI). Previous studies suggest that area under the curve (AUC) monitoring reduces the risk of AKI, but literature is lacking to support this in patients receiving longer durations of vancomycin therapy. Design: Retrospective cohort study. Method: Patients ≥18 years old, admitted between August 2015 and July 2017 or October 2017 and September 2019, and received at least 14 days of intravenous (IV) vancomycin therapy were included in the study. Our primary outcome was the incidence of AKI between trough monitoring and AUC monitoring groups using Kidney Disease Improving Global Outcomes criteria. Secondary outcomes included inpatient mortality, median inpatient length of stay, and median intensive care unit length of stay. Results: Overall, 582 patients were included in the study, with 318 patients included in the trough monitoring group and 264 included in the AUC monitoring group. The median duration of vancomycin therapy was 23 days (interquartile range, 16-39). Patients within the trough monitoring group had a higher incidence of AKI compared to the AUC monitoring group (45.6% vs 28.4%, p < 0.001). Furthermore, logistic regression analysis showed that AUC monitoring was associated with a 54% lower incidence of AKI (OR 0.46, 95% CI [0.31-0.69]). All-cause inpatient mortality was numerically higher in the trough monitoring group (12.9% vs 8.3%, p = 0.078). Conclusions: In patients who received at least 14 days of IV vancomycin therapy, AUC monitoring was associated with a lower incidence of AKI.

A comparison of active versus passive methods of responding to rapid diagnostic blood culture results.

Objective: To compare 2 methods of communicating polymerase chain reaction (PCR) blood-culture results: active approach utilizing on-call personnel versus passive approach utilizing notifications in the electronic health record (EHR). Design: Retrospective observational study. Setting: A tertiary-care academic medical center. Patients: Adult patients hospitalized with ≥1 positive blood culture containing a gram-positive organism identified by PCR between October 2014 and January 2018. Methods: The standard protocol for reporting PCR results at baseline included a laboratory technician calling the patient's nurse, who would report the critical result to the medical provider. The active intervention group consisted of an on-call pager system utilizing trained pharmacy residents, whereas the passive intervention group combined standard protocol with real-time in-basket notifications to pharmacists in the EHR. Results: Of 209 patients, 105, 61, and 43 patients were in the control, active, and passive groups, respectively. Median time to optimal therapy was shorter in the active group compared to the passive group and control (23.4 hours vs 42.2 hours vs 45.9 hours, respectively; P = .028). De-escalation occurred 12 hours sooner in the active group. In the contaminant group, empiric antibiotics were discontinued faster in the active group (0 hours) than in the control group and the passive group (17.7 vs 7.2 hours; P = .007). Time to active therapy and days of therapy were similar. Conclusions: A passive, electronic method of reporting PCR results to pharmacists was not as effective in optimizing stewardship metrics as an active, real-time method utilizing pharmacy residents. Further studies are needed to determine the optimal method of communicating time-sensitive information.

Comparison of Bayesian-derived and first-order analytic equations for calculation of vancomycin area under the curve.

INTRODUCTION: Consensus guidelines recommend targeting a vancomycin area under the curve to minimum inhibitory concentration (AUC24 :MIC) ratio of 400-600 to improve therapeutic success and reduce nephrotoxicity. Although guidelines specify either Bayesian software or first-order equations may be used to estimate AUC24 , there are currently no large studies directly comparing these methods. OBJECTIVE: To compare calculated vancomycin AUC24 using first-order equations with two-drug concentrations at steady state to Bayesian two- and one-concentration estimations. METHODS: This was a single-center, retrospective cohort study of 978 adult hospitalized patients receiving intravenous vancomycin between 2017 and 2019. Patients were included if they received at least 72 h of vancomycin and had two-serum drug concentrations obtained. AUC24 was calculated using first-order analytic (linear), Bayesian two-concentration, and Bayesian one-concentration methods for each patient. The InsightRx™ software platform was used to calculate Bayesian AUC24 . Pearson's correlation and clinical agreement (based on AUC24  classified as subtherapeutic, therapeutic, or supratherapeutic) were used to assess agreement between methods. Bland-Altman plots were used to assess mean difference (MD) and 95% limits of agreement (LOA). RESULTS: Excellent agreement was observed between linear and Bayesian two-concentration methods (r = 0.963, clinical agreement = 87.4%) and Bayesian two-concentration and one-concentration methods (r = 0.931, clinical agreement = 88.5%); however, a degree of variability was noted with 95% LOA -99 to 76 (MD = -11.5 mg*h/L) and -92 to 113 (MD = -10.4 mg*h/L), for the respective comparisons. The agreement between linear and Bayesian one-concentration approaches was less than prior comparisons (r = 0.823, clinical agreement = 76.8%) and demonstrated the greatest amount of variability with 95% LOA -197 to 153 (MD = -21.9 mg*h/L). CONCLUSIONS: Linear and Bayesian two-concentration methods demonstrated high-level agreement with acceptable variability and may be considered comparable to estimate vancomycin AUC24 . As linear and Bayesian one-concentration methods demonstrated significant variability and suboptimal agreement, concerns exist surrounding the interchangeability of these methods in clinical practice, particularly at higher extremes of AUC24 .

Acute Kidney Injury Associated with Area under the Curve versus Trough Monitoring of Vancomycin in Obese Patients.

Vancomycin is a first-line agent used in the treatment of methicillin-resistant Staphylococcus aureus; however, vancomycin is associated with acute kidney injury (AKI). Previous literature demonstrates decreased incidence of AKI using 24-h area under the concentration-time curve (AUC24) monitoring, but its safety is unknown in obese populations. Patients ≥18 years, with body mass indices (BMI) ≥30 kg/m2, admitted between August 2015 and July 2017 or October 2017 and September 2019, who received vancomycin for ≥72 h and had level(s) drawn within 96 h of initiation were included. The primary outcome was incidence of AKI. Secondary outcomes included inpatient mortality rate, median inpatient length of stay, median vancomycin trough concentration, and median vancomycin AUC24. AKI was identified using the highest serum creatinine value compared with the value immediately prior to vancomycin initiation based on Kidney Disease Improving Global Outcomes (KDIGO) criteria. Overall, 1,024 patients met inclusion criteria, with 142 out of 626 patients in the trough group and 65 out of 398 patients in the AUC24 group meeting criteria for AKI (22.7% versus 16.3%, P = 0.008). Logistic regression of the data to account for confounding factors maintained significance for the reduction in incidence of AKI with AUC24 monitoring compared to trough monitoring (P = 0.010). Monitoring of vancomycin with AUC24 was associated with a decreased risk of AKI when compared with trough monitoring in obese patients.

Appropriateness of antibiotic use in patients with and without altered mental status diagnosed with a urinary tract infection.

Objective: The objective of this study was to determine antibiotic appropriateness based on Loeb minimum criteria (LMC) in patients with and without altered mental status (AMS). Design: Retrospective, quasi-experimental study assessing pooled data from 3 periods pertaining to the implementation of a UTI management guideline. Setting: Academic medical center in Lexington, Kentucky. Patients: Adult patients aged ≥18 years with a collected urinalysis receiving antimicrobial therapy for a UTI indication. Methods: Appropriateness of UTI management was assessed in patients prior to an institutional UTI guideline, after guideline introduction and education, and after implementation of a prospective audit-and-feedback stewardship intervention from September to November 2017-2019. Patient data were pooled and compared between patients noted to have AMS versus those with classic UTI symptoms. Loeb minimum criteria were used to determine whether UTI diagnosis and treatment was warranted. Results: In total, 600 patients were included in the study. AMS was one of the most common indications for testing across the 3 periods (19%-30.5%). Among those with AMS, 25 patients (16.7%) met LMC, significantly less than the 151 points (33.6%) without AMS (P < .001). Conclusions: Patients with AMS are prescribed antibiotic therapy without symptoms indicative of UTI at a higher rate than those without AMS, according to LMC. Further antimicrobial stewardship efforts should focus on prescriber education and development of clearly defined criteria for patients with and without AMS.

Efficacy and safety of vancomycin loading doses in critically ill patients with methicillin-resistant Staphylococcus aureus infection.

BACKGROUND: While vancomycin loading doses may facilitate earlier pharmacokinetic-pharmacodynamic target attainment, the impact of loading doses on clinical outcomes remains understudied. Critically ill patients are at highest risk of morbidity and mortality from methicillin resistant Staphylococcus aureus (MRSA) infection and hypothesized to most likely benefit from a loading dose. We sought to determine the association between receipt of a vancomycin loading dose and clinical outcomes in a cohort of critically ill adults. METHODS: Four hundred and forty-nine critically ill patients with MRSA cultures isolated from blood or respiratory specimens were eligible for the study. Cohorts were established by receipt of a loading dose (⩾20 mg/kg actual body weight) or not. The primary outcome was clinical failure, a composite outcome of death within 30 days of first MRSA culture, blood cultures positive ⩾7 days, white blood cell count up to 5 days from vancomycin initiation, temperature up to 5 days from vancomycin initiation, or substitution (or addition) of another MRSA agent. RESULTS: There was no difference in the percentage of patients experiencing clinical failure between the loading dose and no loading dose groups (74.8% versus 72.8%; p = 0.698). Secondary outcomes were also similar between groups, including mortality and acute kidney injury, as was subgroup analysis based on site of infection. Exploratory analyses, including assessment of loading dose based on quartiles and a multivariable logistic regression model showed no differences. CONCLUSION: Use of vancomycin loading doses was not associated with improved clinical outcomes in critically ill patients with MRSA infection.

Pharmacist Survey: Pharmacist Perception of Vancomycin Area Under the Curve Therapeutic Drug Monitoring.

BACKGROUND: Evidence suggests the standard vancomycin trough goal of 15 to 20 mg/L for serious Staphylococcus aureus infections is associated with acute kidney injury, whereas appropriate monitoring of 24-hour area under the curve (AUC) may decrease nephrotoxicity. As a result, institutions have transitioned to AUC monitoring, the predictive pharmacokinetic/pharmacodynamic parameter of vancomycin to improve safety outcomes. However, this method may require increased pharmacist time and effort. Pharmacist perception of the practice change is largely unknown and warrants investigation. METHODS: An electronic survey was disseminated via e-mail to pharmacists 5 months post-AUC implementation. Items of interest were focused on pharmacist perception, including quantity of patients monitored using AUC, justification of the practice change, differences in efficacy and safety, and changes in monitoring time requirements. RESULTS: The pharmacist survey was distributed to 196 pharmacists and 84 responded (43% response rate). Eighty-one pharmacists had monitored patients using AUC methods. Sixty-nine percent of these respondents perceived the change to result in increased or slightly increased patient safety, 27% described no difference, and 4% stated safety was decreased or slightly decreased. Forty-two percent perceived the transition to result in increased or slightly increased efficacy, while 48% noted no difference and 10% responded that efficacy was decreased or slightly decreased. Pharmacists stated the creation of an institutional calculator decreased the time required to calculate AUC. CONCLUSION: After the change to AUC monitoring, pharmacists perceived improvements in safety outcomes while efficacy was at least similar if not increased.

First-Dose Vancomycin Pharmacokinetics Versus Empiric Dosing on Area-Under-the-Curve Target Attainment in Critically Ill Patients.

BACKGROUND: Early attainment of target area under the curve (AUC) to minimum inhibitory concentration (MIC) ratios have been associated with clinical success, as well as lower incidence of acute kidney injury (AKI), in patients receiving vancomycin for methicillin-resistant Staphylococcus aureus (MRSA). Critically ill patients are particularly vulnerable to poor outcomes from infection and face multiple risk factors for AKI, thus early precision dosing of vancomycin is vital in this population. We hypothesized that a personalized dosing approach, using vancomycin levels obtained after the first dose to guide further dosing, would be superior to empiric dosing in terms of AUC target attainment assessed at steady state (SS). METHODS: A retrospective cohort study of 66 critically ill adult patients admitted to the medical intensive care unit without AKI and receiving vancomycin with at least two SS concentrations obtained for AUC calculation was performed. Patients were separated into cohorts based on whether they had two concentrations assessed after the first dose of vancomycin and were subsequently dosed based on personalized pharmacokinetic calculations (first-dose kinetics) or whether they were empirically dosed using population estimates. The primary outcome was AUC target attainment (400-600 mg hour/L) at SS. RESULTS: Compared with patients receiving empiric dosing by population estimates, using first-dose kinetics to guide subsequent dosing resulted in significantly greater AUC target attainment at SS (58.6% first-dose vs 32.4% empiric; p=0.033). Patients dosed empirically yielded more variable AUC values across a wide range compared with the first-dose kinetics group (coefficient of variation 40.7% empiric vs 26.1% first-dose). There was no difference in AKI up to 48 hours after SS concentrations between the two dosing schemes. CONCLUSIONS: A dosing strategy using two vancomycin serum concentrations after the first dose and calculating personalized pharmacokinetic parameters to guide subsequent dosing is associated with greater AUC target attainment at SS compared with empiric dosing of vancomycin in critically ill adults with relatively stable renal function.

Vancomycin Area Under the Curve Dosing and Monitoring at an Academic Medical Center: Transition Strategies and Lessons Learned.

Due to the inconsistent correlation of vancomycin trough concentrations with 24-hour area under the curve (AUC) and a desire to reduce rates of vancomycin-associated acute kidney injury, an institutional guideline was implemented by the Antimicrobial Stewardship Team in September 2017 to monitor vancomycin using AUC. Three stages were utilized to organize the process: preparation, implementation, and evaluation. The preparation stage was used to present literature to key stakeholders, and pharmacy meetings focused on the development of a dosing and monitoring guideline. Along with institution-wide education, the implementation stage included information technology development and support. The evaluation stage was comprised of quality improvement and clinical research. Future plans include dissemination of the results and analyses. Numerous lessons were learned due to barriers experienced during the process, but the transition was successful.

Influence of ß-Lactam Infusion Strategy on Acute Kidney Injury.

Limited literature is available assessing nephrotoxicity with prolonged ß-lactam infusions. This study compared the incidence of acute kidney injury (AKI) associated with a prolonged ß-lactam infusion or an intermittent infusion. This was a retrospective, matched-cohort study at an academic medical center from July 2006 to September 2015. Adult patients who received piperacillin-tazobactam (TZP), cefepime (FEP), or meropenem (MEM) for at least 48 h were evaluated. Patients were excluded for preexisting renal dysfunction or pregnancy. The primary outcome was difference in incidence of AKI evaluated using the RIFLE (risk, injury, failure, loss, and end-stage) criteria. Patients in the intermittent group were matched 3:1 to patients in the prolonged-infusion group based on the following: ß-lactam agent, age, gender, Charlson comorbidity index, baseline creatinine clearance, hypotension, receipt of vancomycin, and treatment in an intensive care unit. A total of 2,390 patients were included in the matched analysis, with 1,700 receiving intermittent infusions and 690 receiving prolonged infusion. The incidence of AKI was similar in the prolonged-infusion group to that in the intermittent-infusion group (21.6% versus 18.6%; P = 0.1). After multivariate regression, prolonged infusion was not associated with increased odds of AKI (odds ratio [OR], 1.07; 95% confidence interval [95% CI], 0.83 to 1.39). Independent predictors of AKI included TZP therapy, concomitant nephrotoxins, hypotension, and heart failure. Although AKIs were numerically more common in patients receiving prolonged ß-lactam infusions than those receiving intermittent infusions, prolonged infusion was not an independent risk factor for AKI.

Pharmacist perception and use of UpToDate®.

A cross-sectional survey of a convenience sample of 1,199 pharmacists was conducted to describe pharmacists' use and perception of UpToDate®. Of 472 (39%) respondents, 217 (46%) reported using UpToDate. Most respondents who used or had heard of UpToDate indicated willingness to change a treatment plan based on UpToDate recommendations (77%). Many believed that UpToDate is updated weekly (31%) or monthly (49%) and that all articles undergo external peer review (51%). In conclusion, the majority of respondents reported that they would adjust drug therapy based on UpToDate recommendations; however, many pharmacists may hold misconceptions regarding the updating and peer-review processes.