Machine Learning To Stratify Methicillin-Resistant Staphylococcus aureus Risk among Hospitalized Patients with Community-Acquired Pneumonia.

Methicillin-resistant Staphylococcus aureus (MRSA) is an uncommon but serious cause of community-acquired pneumonia (CAP). A lack of validated MRSA CAP risk factors can result in overuse of empirical broad-spectrum antibiotics. We sought to develop robust models predicting the risk of MRSA CAP using machine learning using a population-based sample of hospitalized patients with CAP admitted to either a tertiary academic center or a community teaching hospital. Data were evaluated using a machine learning approach. Cases were CAP patients with MRSA isolated from blood or respiratory cultures within 72 h of admission; controls did not have MRSA CAP. The Classification Tree Analysis algorithm was used for model development. Model predictions were evaluated in sensitivity analyses. A total of 21 of 1,823 patients (1.2%) developed MRSA within 72 h of admission. MRSA risk was higher among patients admitted to the intensive care unit (ICU) in the first 24 h who required mechanical ventilation than among ICU patients who did not require ventilatory support (odds ratio [OR], 8.3; 95% confidence interval [CI], 2.4 to 32). MRSA risk was lower among patients admitted to ward units than among those admitted to the ICU (OR, 0.21; 95% CI, 0.07 to 0.56) and lower among ICU patients without a history of antibiotic use in the last 90 days than among ICU patients with antibiotic use in the last 90 days (OR, 0.03; 95% CI, 0.002 to 0.59). The final machine learning model was highly accurate (receiver operating characteristic [ROC] area = 0.775) in training and jackknife validity analyses. We identified a relatively simple machine learning model that predicted MRSA risk in hospitalized patients with CAP within 72 h postadmission.

Individual meropenem epithelial lining fluid and plasma PK/PD target attainment.

It is unclear whether plasma is a reliable surrogate for target attainment in the epithelial lining fluid (ELF). The objective of this study was to characterize meropenem target attainment in plasma and ELF using prospective samples. The first 24-hour T>MIC was evaluated vs 1xMIC and 4xMIC targets at the patient (i.e., fixed MIC of 2 mg/L) and population [i.e., cumulative fraction of response (CFR) according to EUCAST MIC distributions] levels for both plasma and ELF. Among 65 patients receiving ≥24 hours of treatment, 40% of patients failed to achieve >50% T>4xMIC in plasma and ELF, and 30% of patients who achieved >50% T>4xMIC in plasma had <50% T>4xMIC in ELF. At 1xMIC and 4xMIC targets, 3% and 25% of patients with >95% T>MIC in plasma had <50% T>MIC in ELF, respectively. Those with a CRCL >115 mL/min were less likely to achieve >50%T>4xMIC in ELF (P < 0.025). In the population, CFR for Escherichia coli at 1xMIC and 4xMIC was >97%. For Pseudomonas aeruginosa, CFR was ≥90% in plasma and ranged 80%-85% in ELF at 1xMIC when a loading dose was applied. CFR was reduced in plasma (range: 75%-81%) and ELF (range: 44%-60%) in the absence of a loading dose at 1xMIC. At 4xMIC, CFR for P. aeruginosa was 60%-86% with a loading dose and 18%-62% without a loading dose. We found that plasma overestimated ELF target attainment inup to 30% of meropenem-treated patients, CRCL >115 mL/min decreased target attainment in ELF, and loading doses increased CFR in the population.

Making the case for precision dosing: visualizing the variability of cefepime exposures in critically ill adults.

OBJECTIVE: To investigate and describe the variability in cefepime exposures among 'real-world', critically ill patients by using population pharmacokinetic modelling and simulations, and with translation of these findings to visualizations. METHODS: A cohort of adult medical ICU patients who received cefepime with therapeutic drug monitoring was studied. Two compartment models were developed to estimate cefepime clearance (Model 1) and simulate cefepime exposures among 1000 patients, each with identical creatinine clearance of 60 mL/min and receiving a regimen of cefepime 1 gram IV over 30 minutes, every 8 hours (Model 2). Variability in the relationship between cefepime clearance and creatinine clearance (CrCL) was visualized, and a random, representative sample of 10 simulated patients was utilized to illustrate variability in cefepime exposures. RESULTS: A total of 75 adult medical ICU patients (52% female) and 98 serum cefepime samples were included in the study. Population parameter estimates for cefepime displayed a wide range of variation in Model 1 (CV: 45% to 95%), with low bias at the individual level at 0.226 mg/L but high bias in the population model 10.6 mg/L. Model 2 displayed similar fits, demonstrating that correcting for individual patient creatinine clearance slightly improves the bias of the population model (bias = 4.31 mg/L). Among 10 simulated patients that a clinician would deem similar from a dosing perspective (i.e. equivalent creatinine clearance), maximum concentrations after three simulated doses varied more than 8-fold from 41.2 to 339 mg/L at the 5th and 95th percentiles, and clearance profiles were highly different. CONCLUSION: Creatinine clearance estimates alone are inadequate for predicting cefepime exposures. Wide variations in cefepime exposure exist among ICU patients, even for those with similar kidney function estimates. Current population adjustment schemes based solely on creatinine clearance will result in unintended high and low exposures leading to safety and efficacy concerns, respectively.

Antibiotic choice for Group B Streptococcus prophylaxis in mothers with reported penicillin allergy and associated newborn outcomes.

OBJECTIVE: To evaluate the choice of antibiotic used for intrapartum Group B Streptococcus (GBS) prophylaxis in pregnant individuals with reported penicillin allergies compared to those without reported penicillin allergies and investigate whether there are associated differences in neonatal outcomes. STUDY DESIGN: This retrospective cohort study included mother-infant dyads of GBS positive pregnant individuals who labored and delivered newborns ≥ 35 weeks of gestation at a high-volume urban hospital (2005-2018). The type of antibiotic administered to the mothers for GBS prophylaxis (beta-lactam prophylaxis defined as penicillin-class drug or cefazolin; alternative prophylaxis defined as vancomycin or clindamycin) was compared between those with a penicillin allergy documented in their medical record versus those who did not. Neonatal outcomes included number of postnatal blood draws, antibiotic administration, neonatal intensive care unit (NICU) admission, bacteremia, and hospital length of stay and were compared between groups. Bivariable and multivariable analyses were performed. RESULTS: Of 11,334 mother-infant pairs, 1170 (10.3%) mothers had a penicillin allergy documented in their medical record. Of them, 49 (4.2%) received a penicillin, 259 (22.1%) received cefazolin, 449 (38.4%) received clindamycin, and 413 (35.3%) received vancomycin. Patients with a reported penicillin allergy were significantly more likely to receive alternative GBS prophylaxis compared to those without penicillin allergy (73.7% vs. 0.2%, p < 0.01). Neonates of patients who received alternative GBS prophylaxis were significantly more likely to undergo a postnatal lab draw compared to neonates of patients who received beta-lactam antibiotics (20.8% vs. 17.3%, OR 1.25 (95% CI 1.08-1.46)). This significant association persisted after adjusting for potential confounders (aOR 1.23, 95% CI 1.06-1.43). There were no other significant differences seen in other newborn outcomes. CONCLUSION: Pregnant individuals who report a penicillin allergy were more likely to receive alternative antibiotics for GBS prophylaxis compared to those without a penicillin allergy. This was associated with an increased frequency of postnatal blood draws among neonates of mothers with a reported penicillin allergy. Administration of alternative intrapartum antibiotic prophylaxis with vancomycin or clindamycin is common in individuals with self-reported penicillin allergy, and maternal alternative antibiotic administration may impact neonatal care, particularly via increased lab draws.

Individual target pharmacokinetic/pharmacodynamic attainment rates among meropenem-treated patients admitted to the ICU with hospital-acquired pneumonia.

OBJECTIVES: Critical illness reduces ß-lactam pharmacokinetic/pharmacodynamic (PK/PD) attainment. We sought to quantify PK/PD attainment in patients with hospital-acquired pneumonia. METHODS: Meropenem plasma PK data (n = 70 patients) were modelled, PK/PD attainment rates were calculated for empirical and definitive targets, and between-patient variability was quantified [as a coefficient of variation (CV%)]. RESULTS: Attainment of 100% T>4×MIC was variable for both empirical (CV% = 92) and directed (CV% = 33%) treatment. CONCLUSIONS: Individualization is required to achieve suggested PK/PD targets in critically ill patients.

Implementation of a clinical pharmacist-driven comprehensive medication management program in an outpatient wound healing center.

BACKGROUND: The role of the pharmacist in wound healing management among patients with diabetic and nondiabetic foot ulcers (DFU) is unclear. We sought to implement and evaluate an integrated pharmacist-driven comprehensive medication management (CMM) program in a multidisciplinary podiatrist-led wound healing center (WHC). OBJECTIVES: The objectives were to determine the role of the clinical pharmacist in a WHC and evaluate the impact of CMM interventions on prescribing rates and wound healing rates. METHODS: A pharmacist-driven CMM program was implemented in a podiatrist-led WHC, and an evaluation spanning 6 years was conducted. RESULTS: Overall, 1018 patients were treated over 6 years, and 515 received wound treatment after the CMM period, of which, 309 received CMM services. A total of 441 medication related problems (MRPs) were identified; most were related to medication safety (35.1%) and inappropriate or ineffective therapy (31.3%), and problems with adherence accounted for 22.5% of documented MRPs. An average of 3.41 interventions per patient were documented, and most were related to patient education (40.8%). Only metformin (20.3 vs. 34.2%; P < 0.001) and insulin prescription (57.3 vs. 73.8%; P < 0.001) prevalence increased after CMM implementation. Other prescriptions were not significantly different among patients presenting in the pre- and post-CMM periods, respectively. Wound healing rates among patients with DFU were similar before and after implementation (55 vs. 52%; P = 0.49). Likewise, wound healing rates among those with non-DFUs were similar before- and after implementation (56 vs. 53%; P = 0.56). CONCLUSION: The implementation of a novel pharmacist-driven CMM program embedded within a multidisciplinary podiatrist-managed WHC provided the initial evidence of the potential benefits of providing pharmacist-driven CMM services to patients with lower extremity ulcers. Prospective studies of CMM in this patient population are needed.

Optimizing Aminoglycoside Dosing Regimens for Critically Ill Pediatric Patients with Augmented Renal Clearance: a Convergence of Parametric and Nonparametric Population Approaches.

Augmented renal clearance (ARC) can occur in critically ill pediatric patients receiving aminoglycosides such as gentamicin and tobramycin, yet optimal dosing strategies for ARC are undefined. We evaluated the probability of achieving efficacious or toxic exposures in pediatrics. Parallel population modeling of concentration strategies were pursued using Pmetrics v1.5.2 (nonparametric) and Monolix v2019R2 (parametric). Bayesian exposures were used to classify ARC based on total clearance (CL). The effects of serum creatinine (SCR), creatinine clearance (CRCL), total body weight (TBW), postnatal age (PNA), and ARC were explored as covariates. The probabilities of target attainment (PTA) (i.e., maximum concentration [Cmax]/MIC, area under the concentration-time curve [AUC]/MIC) and of toxic exposure (PTE) (i.e., minimum concentration [Cmin] > 2 µg/ml) were calculated according to PNA and ARC. A total of 123 patients (1 to 21 years old, 56% female) contributed 304 concentrations. A two-compartment model was superior to a one-compartment model in both approaches. Bayesian posterior predicted concentrations from the nonparametric base model fit the data well (R2 = 0.96) and classified 34 patients as having ARC (28%). Both the nonparametric and parametric approaches resulted in allometrically scaling of TBW on volume (V) and clearance (CL). ARC modified CL and central V. CRCL and a maturation function modified CL. ARC was associated with a 1.49- versus 1.66-fold increase in CL and a 1.56- versus 1.66-fold increase in the central V (nonparametric versus parametric). A high dose of 12 mg/kg of body weight/day was required to achieve adequate PTA when MICs were 1 to 2 µg/ml; ARC lowered achievable MICs. When PNA was <2 years, PTE was increased. Aminoglycoside monotherapy should be avoided in critically ill pediatric patients with ARC when MICs exceed 1 µg/ml, as optimal exposures are unachievable with standard dosing.

Characterizing Risk Factors for Clostridioides difficile Infection among Hospitalized Patients with Community-Acquired Pneumonia.

Hospitalized patients with community-acquired pneumonia (CAP) are at risk of developing Clostridioides difficile infection (CDI). We developed and tested clinical decision rules for identifying CDI risk in this patient population. The study was a single-center retrospective, case-control analysis of hospitalized adult patients empirically treated for CAP between 1 January 2014 and 3 March 2018. Differences between cases (CDI diagnosed within 180 days following admission) and controls (no test result indicating CDI during the study period) with respect to prehospitalization variables were modeled to generate propensity scores. Postadmission variables were used to predict case status on each postadmission day where (i) ≥1 additional case was identified and (ii) each model stratum contained ≥15 subjects. Models were developed and tested using optimal discriminant analysis and classification tree analysis. Forty-four cases and 181 controls were included. The median time to diagnosis was 50 days postadmission. After weighting, three models were identified (20, 117, and 165 days postadmission). The day 20 model yielded the greatest (weighted [w]) accuracy (weighted area under the receiver operating characteristic curve [wROC area] = 0.826) and the highest chance-corrected accuracy (weighted effect strength for sensitivity [wESS] = 65.3). Having a positive culture (odds, 1:4; P = 0.001), receipt of ceftriaxone plus azithromycin for a defined infection (odds, 3:5; P = 0.006), and continuation of empirical broad-spectrum antibiotics with activity against P. aeruginosa when no pathogen was identified (odds, 1:8; P = 0.013) were associated with CDI on day 20. Three models were identified that accurately predicted CDI in hospitalized patients treated for CAP. Antibiotic use increased the risk of CDI in all models, underscoring the importance of antibiotic stewardship.

Of Rats and Men: a Translational Model To Understand Vancomycin Pharmacokinetic/Toxicodynamic Relationships.

Vancomycin area under the concentration curve (AUC) is known to predict vancomycin-induced acute kidney injury (AKI). Data were analyzed from a rat model (n = 48) and two prospective clinical studies (PROVIDE [n = 263] and CAMERA2 [n = 291]). A logit-link model was used to calculate the multiplicative factors between the probability of AKI from clinical studies and in the rat. The rat was 2.7 to 4.2 times more sensitive to AKI between AUCs of 199.5 and 794.3 mg·h/liter, respectively.

Piperacillin-Tazobactam Added to Vancomycin Increases Risk for Acute Kidney Injury: Fact or Fiction?

Vancomycin and piperacillin-tazobactam are 2 of the most commonly prescribed antibiotics in hospitals. Recent data from multiple meta-analyses suggest that the combination increases the risk for vancomycin-induced kidney injury when compared to alternative viable options. However, these studies are unable to prove biologic plausibility and causality as randomized controlled trials have not been performed. Furthermore, these studies define acute kidney injury according to thresholds of serum creatinine rise. Serum creatinine is not a direct indicator of renal injury, rather a surrogate of glomerular function. More reliable, specific, and sensitive biomarkers are needed to truly define if there is a causal relationship with increased toxicity when piperacillin-tazobactam is added to vancomycin. This viewpoint will explore the available evidence for and against increased acute kidney injury in the setting of vancomycin and piperacillin-tazobactam coadministration.

Long-term Persistence of an Extensively Drug-Resistant Subclade of Globally Distributed Pseudomonas aeruginosa Clonal Complex 446 in an Academic Medical Center.

BACKGROUND: Antimicrobial resistance (AMR) is a major challenge in the treatment of infections caused by Pseudomonas aeruginosa. Highly drug-resistant infections are disproportionally caused by a small subset of globally distributed P. aeruginosa sequence types (STs), termed "high-risk clones." We noted that clonal complex (CC) 446 (which includes STs 298 and 446) isolates were repeatedly cultured at 1 medical center and asked whether this lineage might constitute an emerging high-risk clone. METHODS: We searched P. aeruginosa genomes from collections available from several institutions and from a public database for the presence of CC446 isolates. We determined antibacterial susceptibility using microbroth dilution and examined genome sequences to characterize the population structure of CC446 and investigate the genetic basis of AMR. RESULTS: CC446 was globally distributed over 5 continents. CC446 isolates demonstrated high rates of AMR, with 51.9% (28/54) being multidrug-resistant (MDR) and 53.6% of these (15/28) being extensively drug-resistant (XDR). Phylogenetic analysis revealed that most MDR/XDR isolates belonged to a subclade of ST298 (designated ST298*) of which 100% (21/21) were MDR and 61.9% (13/21) were XDR. XDR ST298* was identified repeatedly and consistently at a single academic medical center from 2001 through 2017. These isolates harbored a large plasmid that carries a novel antibiotic resistance integron. CONCLUSIONS: CC446 isolates are globally distributed with multiple occurrences of high AMR. The subclade ST298* is responsible for a prolonged epidemic (≥16 years) of XDR infections at an academic medical center. These findings indicate that CC446 is an emerging high-risk clone deserving further surveillance.

Evaluation of Dose-Fractionated Polymyxin B on Acute Kidney Injury Using a Translational In Vivo Rat Model.

We investigated dose-fractionated polymyxin B (PB) on acute kidney injury (AKI). PB at 12 mg of drug/kg of body weight per day (once, twice, and thrice daily) was administered in rats over 72 h. The thrice-daily group demonstrated the highest KIM-1 increase (P = 0.018) versus that of the controls (P = 0.99) and histopathological damage (P = 0.013). A three-compartment model best described the data (bias, 0.129 mg/liter; imprecision, 0.729 mg2/liter2; R2, 0.652,). Area under the concentration-time curve at 24 h (AUC24) values were similar (P = 0.87). The thrice-daily dosing scheme resulted in the most PB-associated AKI in a rat model.

Population Pharmacokinetics and Target Attainment of Cefepime in Critically Ill Patients and Guidance for Initial Dosing.

Cefepime is commonly used in the intensive care unit (ICU) to treat bacterial infections. The time during which the free cefepime concentration is above the MIC (fT>MIC) should be optimized to increase the efficacy of the regimen. We aim to optimize the exposure of cefepime in ICU patients by using population pharmacokinetic (PK) modeling and simulations. Two data sets were included in this study. The first was a prospective study of pediatric patients who received cefepime at 50 mg/kg of body weight and had extensive PK sampling. The second study comprised retrospective data for adult ICU patients admitted to UF Health Shands Hospital who received cefepime and had their cefepime concentrations measured. The population PK model was developed, and simulations were performed, using Pmetrics. The target exposures were 100% fT>MIC and 100% fT>4×MIC The studies included a total of 266 patients, and the mean ages were 3.9 years in the pediatric group and 55 years in adult group. More than half of the patients were males. The mean (standard deviation [SD]) creatinine clearance (CrCl) was 125 (93) ml/min. The mean (SD) daily dose for adults was 4.9 (1.6) g. Cefepime was well described by a two-compartment model with weight as a covariate on the volume of distribution and elimination rate constant (kel), and CrCl and age group as covariates on kel At a MIC of 8 mg/liter, a cefepime loading dose of 4 g as an extended infusion followed by a 6-g continuous infusion was needed for good target attainment. In conclusion, prolonged or continuous infusions will be needed to achieve optimal cefepime exposure for ICU patients. Given the observed variability, therapeutic drug monitoring can help individualize therapy.

Augmented renal clearance of aminoglycosides using population-based pharmacokinetic modelling with Bayesian estimation in the paediatric ICU.

OBJECTIVE: To evaluate augmented renal clearance (ARC) using aminoglycoside clearance (CLAMINO24h) derived from pharmacokinetic (PK) modelling. METHODS: A retrospective study at two paediatric hospitals of patients who received tobramycin or gentamicin from 1999 to 2016 was conducted. Compartmental PK models were constructed using the Pmetrics package, and Bayesian posteriors were used to estimate CLAMINO24h. ARC was defined as a CLAMINO24h of ≥130 mL/min/1.73 m2. Risk factors for ARC were identified using multivariate logistic regression. RESULTS: The final population model was fitted to 275 aminoglycoside serum concentrations. Overall clearance (L/h) was=CL0×(TBW/70)0.75×AGEH/(TMH + AGEH) + CL1 (0.5/SCr), where TBW is total body weight, H is the Hill coefficient, TM is a maturation term and SCr is serum creatinine. Median CLAMINO24h in those with versus without ARC was 157.36 and 93.42 mL/min/1.73 m2, respectively (P<0.001). ARC was identified in 19.5% of 118 patients. For patients with ARC, median baseline SCr was lower than for those without ARC (0.38 versus 0.41 mg/dL, P=0.073). Risk factors for ARC included sepsis [adjusted OR (aOR) 3.77, 95% CI 1.01-14.07, P=0.048], increasing age (aOR 1.11, 95% CI 1-1.23, P=0.04) and low log-transformed SCr (aOR 0.16, 95% CI 0.05-0.52, P=0.002). Median 24 h AUC (AUC24h) was significantly lower in patients with ARC at 45.27 versus 56.95 mg·h/L, P<0.01. CONCLUSIONS: ARC was observed in one of every five patients. Sepsis, increasing age and low SCr were associated with ARC. Increased clearance was associated with an attenuation of AUC24h in this population. Future studies are needed to define optimal dosing in paediatric patients with ARC.

ß-Lactam pharmacodynamics in Gram-negative bloodstream infections in the critically ill.

OBJECTIVES: To determine the ß-lactam exposure associated with positive clinical outcomes for Gram-negative blood stream infection (BSI) in critically ill patients. PATIENTS AND METHODS: Pooled data of critically ill patients with mono-microbial Gram-negative BSI treated with ß-lactams were collected from two databases. Free minimum concentrations (fCmin) of aztreonam, cefepime, ceftazidime, ceftriaxone, piperacillin (co-administered with tazobactam) and meropenem were interpreted in relation to the measured MIC for targeted bacteria (fCmin/MIC). A positive clinical outcome was defined as completion of the treatment course or de-escalation, without other change of antibiotic therapy, and with no additional antibiotics commenced within 48 h of cessation. Drug exposure breakpoints associated with positive clinical outcome were determined by classification and regression tree (CART) analysis. RESULTS: Data from 98 patients were included. Meropenem (46.9%) and piperacillin/tazobactam (36.7%) were the most commonly prescribed antibiotics. The most common pathogens were Escherichia coli (28.6%), Pseudomonas aeruginosa (19.4%) and Klebsiella pneumoniae (13.3%). In all patients, 87.8% and 71.4% achieved fCmin/MIC ≥1 and fCmin/MIC >5, respectively. Seventy-eight patients (79.6%) achieved positive clinical outcome. Two drug exposure breakpoints were identified: fCmin/MIC >1.3 for all ß-lactams (predicted difference in positive outcome 84.5% versus 15.5%, P < 0.05) and fCmin/MIC >4.95 for meropenem, aztreonam or ceftriaxone (predicted difference in positive outcome 97.7% versus 2.3%, P < 0.05). CONCLUSIONS: A ß-lactam fCmin/MIC >1.3 was a significant predictor of a positive clinical outcome in critically ill patients with Gram-negative BSI and could be considered an antibiotic dosing target.

Lack of synergistic nephrotoxicity between vancomycin and piperacillin/tazobactam in a rat model and a confirmatory cellular model.

BACKGROUND: Vancomycin and piperacillin/tazobactam are reported in clinical studies to increase acute kidney injury (AKI). However, no clinical study has demonstrated synergistic toxicity, only that serum creatinine increases. OBJECTIVES: To clarify the potential for synergistic toxicity between vancomycin, piperacillin/tazobactam and vancomycin + piperacillin/tazobactam treatments by quantifying kidney injury in a translational rat model of AKI and using cell studies. METHODS: (i) Male Sprague-Dawley rats (n = 32) received saline, vancomycin 150 mg/kg/day intravenously, piperacillin/tazobactam 1400 mg/kg/day intraperitoneally or vancomycin + piperacillin/tazobactam for 3 days. Urinary biomarkers and histopathology were analysed. (ii) Cellular injury was assessed in NRK-52E cells using alamarBlue®. RESULTS: Urinary output increased from Day -1 to Day 1 with vancomycin but only after Day 2 for vancomycin + piperacillin/tazobactam-treated rats. Plasma creatinine was elevated from baseline with vancomycin by Day 2 and only by Day 4 for vancomycin + piperacillin/tazobactam. Urinary KIM-1 and clusterin were increased with vancomycin from Day 1 versus controls (P < 0.001) and only on Day 3 with vancomycin + piperacillin/tazobactam (P < 0.001, KIM-1; P < 0.05, clusterin). The histopathology injury score was elevated only in the vancomycin group when compared with piperacillin/tazobactam as a control (P = 0.04) and generally not so with vancomycin + piperacillin/tazobactam. In NRK-52E cells, vancomycin induced cell death with high doses (IC50 48.76 mg/mL) but piperacillin/tazobactam did not, and vancomycin + piperacillin/tazobactam was similar to vancomycin. CONCLUSIONS: All groups treated with vancomycin demonstrated AKI; however, vancomycin + piperacillin/tazobactam was not worse than vancomycin. Histopathology suggested that piperacillin/tazobactam did not worsen vancomycin-induced AKI and may even be protective.

Vancomycin Area Under the Curve and Acute Kidney Injury: A Meta-analysis.

BACKGROUND: This study analyzed the relationship between vancomycin area under the concentration-time curve (AUC) and acute kidney injury (AKI) reported across recent studies. METHODS: A systematic review of PubMed, Medline, Scopus, and compiled references was conducted. We included randomized cohort and case-control studies that reported vancomycin AUCs and risk of AKI (from 1990 to 2018). The primary outcome was AKI, defined as an increase in serum creatinine of ≥0.5 mg/L or a 50% increase from baseline on ≥2 consecutive measurements. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Primary analyses compared the impact of AUC cutpoint (greater than ~650 mg × hour/L) and AKI. Additional analysis compared AUC vs trough-guided monitoring on AKI incidence. RESULTS: Eight observational studies met inclusion/exclusion criteria with data for 2491 patients. Five studies reported first-24-hour AUCs (AUC0-24) and AKI, 2 studies reported 24- to 48-hour AUCs (AUC24-48) and AKI, and 2 studies reported AKI associated with AUC- vs trough-guided monitoring. AUC less than approximately 650 mg × hour/L was associated with decreased AKI for AUC0-24 (OR, 0.36 [95% CI, .23-.56]) as well as AUC24-48 (OR, 0.45 [95% CI, .27-.75]). AKI associated with the AUC monitoring strategy was significantly lower than trough-guided monitoring (OR, 0.68 [95% CI, .46-.99]). CONCLUSIONS: AUCs measured in the first or second 24 hours and lower than approximately 650 mg × hour/L may result in a decreased risk of AKI. Vancomycin AUC monitoring strategy may result in less vancomycin-associated AKI. Additional investigations are warranted.

Trends in and Predictors of Carbapenem Consumption across North American Hospitals: Results from a Multicenter Survey by the MAD-ID Research Network.

We sought to define trends in and predictors of carbapenem consumption across community, teaching, and university-affiliated hospitals in the United States and Canada. We conducted a retrospective multicenter survey of carbapenem and broad-spectrum noncarbapenem beta-lactam consumption between January 2011 and December 2013. Consumption was tabulated as defined daily doses (DDD) or as days of therapy (DOT) per 1,000 patient days (PD). Multivariate mixed-effects models were explored, and final model goodness of fit was assessed by regressions of observed versus predicted values and residual distributions. A total of 20 acute-care hospitals responded. The centers treated adult patients (n = 19/20) and pediatric/neonatal patients (n = 17/20). The majority of the centers were nonprofit (n = 17/20) and not affiliated with medical/teaching institutions (n = 11/20). The median (interquartile range [IQR]) carbapenem consumption rates were 38.8 (17.4 to 95.7) DDD/1,000 PD and 29.7 (19.2 to 40.1) DOT/1,000 PD overall. Carbapenem consumption was well described by a multivariate linear mixed-effects model (fixed effects, R2 = 0.792; fixed plus random effects, R2 = 0.974). Carbapenem consumption increased by 1.91-fold/quarter from 48.6 DDD/1,000 PD (P = 0.004) and by 0.056-fold/quarter from 45.7 DOT/1,000 PD (P = 0.93) over the study period. Noncarbapenem consumption was independently related to increasing carbapenem consumption (beta = 0.31 for increasing noncarbapenem beta-lactam consumption; P < 0.001). Regular antibiogram publication and promotion of conversion from intravenous (i.v.) to oral (p.o.) administration independently affected carbapenem consumption rates. In the final model, 58.5% of the observed variance in consumption was attributable to between-hospital differences. Rates of carbapenem consumption across 20 North American hospitals differed greatly, and the observed differences were correlated with hospital-specific demographics. Additional studies focusing on the drivers of hospital-specific carbapenem consumption are needed to determine whether these rates are justifiable.

Understanding the Components, Calculation, and Impact of Monthly and Seasonal Variation of the Standardized Antimicrobial Utilization Ratio (SAAR).

This study sought to characterize the impact of 3 types of variation on the Standardized Antimicrobial Administration Ratio (SAAR) utilizing local National Healthcare Safety Network (NHSN) data. SAAR and antimicrobial days per 1,000 days present (AD/1000DP) were compiled monthly for Northwestern Memorial Hospital from 2014 to 2016. Antimicrobial consumption was aggregated into agent categories (via NHSN criteria). Month-to-month changes in SAAR and AD/1000DP were evaluated. Azithromycin and oseltamivir AD/1000DP from 2012 through 2017 were explored for seasonal variation. A sensitivity analysis was performed to explore the effect of seasonality and altered consumption at other hypothetical hospitals on the SAAR. Across agent categories for both the intensive care unit (n = 4) and general wards (n = 4), the average matched-month percent change in AD/1000DP was correlated with the corresponding change in SAAR (coefficient of determination of 0.99). The monthly mean ± standard deviation (SD) AD/1000DP was 235 (range, 47.2 to 661.5), and the mean ± SD SAAR was 1.09 ± 0.26 (range, 0.79 to 1.09) across the NHSN agent categories. Five seasons exhibited seasonal variation in AD/1000DP for azithromycin with a mean percent change of 26.76% (range, 22.27 to 30.69). Eight seasons exhibited seasonal variation in AD/1000DP for oseltamivir with a mean percent change of 129.1% (range, 32.01 to 352.74). The sensitivity analyses confirm that antimicrobial usage at comparator hospitals does not impact the local SAAR, and seasonal variation of antibiotics has the potential to impact SAAR. Month-to-month changes in the SAAR mirror monthly changes in an institution's AD/1000DP. Seasonal variation is an important variable for future SAAR consideration, and the variable antibiotic use at peer hospitals is not currently captured by the SAAR methodology.

Comparative Performance of Urinary Biomarkers for Vancomycin-Induced Kidney Injury According to Timeline of Injury.

Urinary biomarkers are superior to serum creatinine for defining onset and extent of kidney injury. This study classifies the temporal predictive ability of biomarkers for vancomycin-induced kidney injury (VIKI) as defined by histopathologic damage. Male Sprague-Dawley rats (n = 125) were randomized to receive 150 to 400 mg/kg of body weight/day vancomycin via once or twice daily intraperitoneal injection over 1, 3, or 6 days. Urine was collected once during the 24 h prior to euthanasia or twice for rats treated for 6 days. Receiver operating characteristic (ROC) curves were employed to assess the urinary biomarker performances of kidney injury molecule 1 (KIM-1), clusterin, osteopontin (OPN), cystatin C, and neutrophil gelatinase-associated lipocalin (NGAL) to predict histopathologically defined VIKI (using a national standard pathological assessment scheme from hematoxylin and eosin stained kidneys). Urinary KIM-1, clusterin, and OPN outperformed cystatin C and NGAL with regard to sensitivity and specificity. For the earliest injury, urinary KIM-1 (area under the receiver operating characteristic curve [AUC], 0.662; P < 0.001) and clusterin (AUC, 0.706; P < 0.001) were the most sensitive for predicting even low-level histopathologic damage at 24 h compared to NGAL. KIM-1 and clusterin are the earliest and most sensitive predictors of VIKI. As injury progresses, KIM-1, clusterin, and OPN best define the extent of damage.