Livrepository.liverpool.ac.uk
Title: 24-Hour Pharmacokinetic Relationships for Intravenous Vancomycin and Novel Urinary Biomarkers of Acute Kidney Injury in a Rat Model Running Title: 24-hour Vancomycin exposure and AKI with intravenous injectionAuthors: Sean N. AVEDISSIAN1-2, Gwendolyn PAIS1-2, J. Nicholas O’DONNELL3, Thomas P. LODISE3, Jiajun LIU1-2, Walter C. PROZIALECK4, Medha D. JOSHI5, Peter C. LAMAR4, Leighton BECHER1, Anil GULATI5, William HOPE6,7, Marc H. SCHEETZ1-2,4*Affiliations: 1 Department of Pharmacy Practice, Chicago College of Pharmacy, Midwestern University, Downers Grove, IL, USA; 2Midwestern University Chicago College of Pharmacy Center of Pharmacometric Excellence; 3Department of Pharmacy Practice, Albany College of Pharmacy and Health Sciences, Albany, NY, USA; 4College of Graduate Studies, Midwestern University, Downers Grove, IL, USA; 5Department of Pharmaceutical Sciences, Chicago College of Pharmacy, Midwestern University, Downers Grove, IL, USA; 6Antimicrobial Pharmacodynamics and Therapeutics Laboratory, Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK; 7 Royal Liverpool and Broadgreen University Hospital Trust, Liverpool, UK* Corresponding author and reprint requests: Marc H. Scheetz, PharmD, MSc; Professor of Pharmacy Practice; Midwestern University Chicago College of Pharmacy; 555 31stSt., Downers Grove, IL 60515, Phone: 630-515-6116; Fax: 630-515-6958; Email:mschee@midwestern.eduWord count: 3633 Abstract word count: 234Synopsis:Objective: To identify the pharmacokinetic (PK) and toxicodynamic (TD) relationship for vancomycin induced kidney injury. Methods: Male Sprague-Dawley rats received intravenous (IV) vancomycin. Doses ranging from 150 mg/kg/day to 400 mg/kg/day were administered as a single or twice daily injection over 24 hours (total protocol duration). Controls received IV saline. Plasma was sampled with up to 8 samples in 24 hours per rat. Twenty-four-hour urine was collected and assayed for kidney injury molecule 1 (KIM-1), osteopontin and clusterin. Vancomycin in plasma was quantified via LC-MS/MS. PK analyses were conducted using Pmetrics for R. PK exposures during the first 24 hours (i.e., AUC0-24h, CMAX0-24h, CMIN0-24h) were calculated. PK-TD relationships were assessed with Spearman’s rank coefficient (rs) and the best fit mathematic model.Results: PK-TD data were generated from 45 vancomycin-treated and 5 control rats. A 2-compartment model fit the data well (Bayesian: observed versus predicted R2=0.97). Exposure-response relationships were found between AUC0-24 versus KIM-1 and osteopontin (R2=0.61 and 0.66) and CMAX0-24h versus KIM-1 and osteopontin (R2=0.50 and 0.56) using a 4-parameter Hill fit. Conversely, CMIN0-24h was less predictive of KIM-1 and osteopontin (R2=0.46 and 0.53). A vancomycin AUC0-24h of 482.2 mg/L*24h corresponded to a 90% of maximal rise in KIM-1.Conclusions: Vancomycin-induced kidney injury as defined by urinary biomarkers is driven by vancomycin AUC or CMAX rather than CMIN. Further, an identified PK/TD target AUC0-24h of 482.2 mg/L*24h may have direct relevance to human outcomes. IntroductionMany critically-ill patients receive vancomycin empirically or in a directed manner for their infection, making vancomycin the single most commonly prescribed antibiotic in the hospital setting. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5QYWt5ejwvQXV0aG9yPjxZZWFyPjIwMDg8L1llYXI+PFJl
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ADDIN EN.CITE.DATA 1-4 Based on 36.5 million hospital stays in the US annually ADDIN EN.CITE <EndNote><Cite><Author>Weiss</Author><Year>2006</Year><RecNum>140</RecNum><DisplayText><style face="superscript">5</style></DisplayText><record><rec-number>140</rec-number><foreign-keys><key app="EN" db-id="r0s5vvwwmrwafsee20pvt5d5erzza5zapf2d" timestamp="1537368569">140</key></foreign-keys><ref-type name="Book Section">5</ref-type><contributors><authors><author>Weiss, A. J.</author><author>Elixhauser, A.</author></authors></contributors><titles><title>Overview of Hospital Stays in the United States, 2012: Statistical Brief #180</title><secondary-title>Healthcare Cost and Utilization Project (HCUP) Statistical Briefs</secondary-title></titles><dates><year>2006</year></dates><pub-location>Rockville (MD)</pub-location><accession-num>25506966</accession-num><urls><related-urls><url> and a vancomycin prevalence of ~100 days of therapy/1000 patient days PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5CYWdnczwvQXV0aG9yPjxZZWFyPjIwMTY8L1llYXI+PFJl
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ZT5=
ADDIN EN.CITE.DATA 3, 4, over 3 million people receive vancomycin annually. Clinical reports suggest vancomycin-induced kidney injury (VIKI) rates may vary from 5-43% PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5HZWxmYW5kPC9BdXRob3I+PFllYXI+MjAxMzwvWWVhcj48
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ADDIN EN.CITE.DATA 6-12, and a prospective study of patients with HAP/VAP treated with vancomycin demonstrated an AKI rate of 18.8%. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XdW5kZXJpbms8L0F1dGhvcj48WWVhcj4yMDEyPC9ZZWFy
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ADDIN EN.CITE.DATA 13Given vancomycin’s frequent use, it is imperative to identify the safest delivery strategy. However, before dosing regimens can be recommended, identifying vancomycin exposures that cause AKI is crucial for implementing strategies to minimize the probability of toxicity while maintaining vancomycin efficacy. Retrospective studies and meta-analyses have identified several risk factors for VIKI such as higher daily dose, elevated troughs, and an increased duration of therapy. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Mb2Rpc2U8L0F1dGhvcj48WWVhcj4yMDA5PC9ZZWFyPjxS
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ADDIN EN.CITE.DATA 7, 8, 14, 15 However, it is difficult to attribute causality of AKI in retrospective clinical studies. Non-modifiable patient factors such as severity of illness, obesity, and concomitant nephrotoxic medications compound VIKI and are notoriously difficult to adjust/control. ADDIN EN.CITE <EndNote><Cite><Author>Gupta</Author><Year>2011</Year><RecNum>86</RecNum><DisplayText><style face="superscript">16</style></DisplayText><record><rec-number>86</rec-number><foreign-keys><key app="EN" db-id="r0s5vvwwmrwafsee20pvt5d5erzza5zapf2d" timestamp="1526935851">86</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Gupta, A.</author><author>Biyani, M.</author><author>Khaira, A.</author></authors></contributors><auth-address>Nephrology Division, University of Ottawa, Ottawa, Canada. parthankur@</auth-address><titles><title>Vancomycin nephrotoxicity: myths and facts</title><secondary-title>Neth J Med</secondary-title></titles><periodical><full-title>Neth J Med</full-title></periodical><pages>379-83</pages><volume>69</volume><number>9</number><keywords><keyword>Acute Kidney Injury/*chemically induced</keyword><keyword>Animals</keyword><keyword>Humans</keyword><keyword>Risk Factors</keyword><keyword>Vancomycin/*adverse effects/pharmacokinetics</keyword></keywords><dates><year>2011</year><pub-dates><date>Sep</date></pub-dates></dates><isbn>1872-9061 (Electronic)
0300-2977 (Linking)</isbn><accession-num>21978980</accession-num><urls><related-urls><url> In retrospective studies, it is also difficult to determine if vancomycin exposures caused AKI or if AKI from another cause caused vancomycin exposures to be elevated (as a function of decreased clearance). In contrast, animal models allow an environment that is free of these confounding factors. Furthermore, a directed experimental design can allow data collection during an early observational window to assess pharmacokinetic-toxicodynamic (PK/TD) drivers before the onset of AKI confounds PK variables. We recently demonstrated that sensitive urinary biomarkers for kidney injury such as kidney injury molecule-1 (KIM-1), osteopontin (OPN) and clusterin were highly correlated with vancomycin area under the curve (AUC0-24h) and maximum concentration (CMAX0-24h) in rats receiving vancomycin via intraperitoneal administration. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5PJmFwb3M7RG9ubmVsbDwvQXV0aG9yPjxZZWFyPjIwMTc8
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ADDIN EN.CITE.DATA 19 Further, KIM-1 can rise within hours of proximal tubule injury, plateau at 24 hours, and stay elevated through 120 hours from time of renal injury.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5WYWlkeWE8L0F1dGhvcj48WWVhcj4yMDEwPC9ZZWFyPjxS
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ADDIN EN.CITE.DATA 19 While our previous studies were able to identify the PK/TD parameters most associated with VIKI, discerning the exact quantitative relationship between vancomycin exposure and AKI was impeded because of variability of intraperitoneal absorption and confounded by the potential for instillation of vancomycin into the abdominal cavity (i.e., instillation into the retroperitoneal space). Thus in this study, we employed intravenous (IV) dosing. Materials and MethodsThis PK/TD study was conducted at Midwestern University in Downers Grove, IL. All study methods were approved by the Institutional Animal Care and Use Committee (IACUC; Protocol #2295) and conducted in compliance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals, 8th edition. ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Year>2011</Year><RecNum>140</RecNum><DisplayText><style face="superscript">20</style></DisplayText><record><rec-number>140</rec-number><foreign-keys><key app="EN" db-id="25arzar2ox9daqe50tapexpef0xztwprds5r" timestamp="1551388860">140</key></foreign-keys><ref-type name="Book Section">5</ref-type><contributors><secondary-authors><author>th,</author></secondary-authors></contributors><titles><secondary-title>Guide for the Care and Use of Laboratory Animals</secondary-title><tertiary-title>The National Academies Collection: Reports funded by National Institutes of Health</tertiary-title></titles><dates><year>2011</year></dates><pub-location>Washington (DC)</pub-location><isbn>9780309154000
0309154006</isbn><accession-num>21595115</accession-num><urls><related-urls><url> Experimental design and animals Experimental methods and design were similar to those previously described PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5PJmFwb3M7RG9ubmVsbDwvQXV0aG9yPjxZZWFyPjIwMTc8
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ADDIN EN.CITE.DATA 17, 18, with several notable differences. In brief, male Sprague-Dawley rats were randomized into either a treatment or control group (treatment receiving vancomycin or normal saline, respectively). All dosages were administered through IV injection via internal jugular vein catheter. Vancomycin-treated rats received total daily doses (dosing protocols) of 150, 200, 300, or 400 mg/kg as either a single or twice daily divided dose over 24 hours (e.g., 150 mg/kg was given as a single injection or as 75 mg/kg twice daily for a total of 24 hours). Doses given twice daily were scheduled every twelve hours. A complete dosing group disposition can be found in Figure 1. The dosing range was chosen based on previous studies PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5GdWNoczwvQXV0aG9yPjxZZWFyPjIwMTI8L1llYXI+PFJl
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ADDIN EN.CITE.DATA 14, 22 Male Sprague-Dawley rats (n=50, approximately 8-10 weeks old, mean weight 310g) were housed in a light and temperature-controlled room for the duration of the study and allowed free access to water and food, except during the metabolic cage period (restricted). Rats (n=5-6 per dosing protocol) were administered IV injections of vancomycin in normal saline (NS) or NS only (control). Data were analyzed for all animals that initiated a protocol. When animals contributed incomplete data (i.e., early protocol termination), urinary biomarkers and urine output were treated as missing data. Blood and urine sampling Surgical catheters were implanted 24 hours prior to protocol initiation. Blood samples were drawn from a single right-side internal jugular vein catheter, and dosing occurred via the left-side internal jugular vein catheter. A maximum of 8 samples per animal were obtained and scheduled at 0, 15, 30, 60, 120, 240, 750 and 1440 min for the once daily and twice daily dosing treatment protocol. Each sample (0.25 mL aliquot) was replaced with an equivalent volume of NS to maintain euvolemia. Blood samples from vancomycin-treated animals were immediately transferred to a disodium ethylenediaminetetraacetic acid (EDTA, [Sigma-Aldrich Chemical Company, Milwaukee WI]) treated microcentrifuge tube and centrifuged at 3000 rpm for 10 minutes. Plasma supernatant was collected and stored at - 80oC for batch sample analysis. Following the 2 hour blood sample, animals were placed in metabolic cages for urine collection (Nalgene, catalogue # 650-0350, Rochester, NY) for the remainder of the 24 hour study (with the exception that they were briefly removed for scheduled blood samples). Urine volume was measured at 24 hours. The urine was centrifuged at 400 x g for 5 minutes, and the supernatant was stored at -80oC until batch analysis.Chemicals and reagents Animals were administered vancomycin hydrochloride (Lot#: 591655DD) for injection obtained commercially (Hospira, Lake Forrest, IL). All solvents were of liquid chromatography-tandem mass spectrometry (LC-MS/MS) grade. For LC-MS/MS, vancomycin hydrochloride, United States Pharmacopeia was used (Enzo Life Science, Farmingdale, NY) with a purity of 99.3%. Polymyxin B (Sigma-Aldrich, St. Louis, MO), acetonitrile, and methanol were purchased from VWR International (Radnor, PA). Formic acid was obtained from Fischer Scientific (Waltham, MA). Frozen, non-medicated, non-immunized, pooled Sprague-Dawley rat plasma (anticoagulated with disodium EDTA) was used for calibration of standard curves (BioreclamationIVT, Westbury, NY). Determination of vancomycin concentrations in plasma Plasma concentrations of vancomycin were quantified with LC and column conditions similar to our previous report PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5PJmFwb3M7RG9ubmVsbDwvQXV0aG9yPjxZZWFyPjIwMTc8
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ADDIN EN.CITE.DATA 17, 23, with the following notable changes to transfer the method to LC-MS/MS. A plasma sample volume of 40 μL was combined with 4 uL of the internal standard of polymyxin B at a concentration of 0.1 mg/mL. Protein precipitation was facilitated using 455 uL methanol containing 1% formic acid. Following centrifugation for 10-minutes at 16,000g (Eppendorf Model: 5424), 75 μL of the supernatant was collected and reserved for analysis. Two μL were injected into an in Agilent 1260 LC attached to Agilent 6420 triple quadrupole mass spectrometer. Mass spectrometry was conducted with electrospray ionization in positive mode (ESI+). The MS source conditions: gas temp set to 350 °C, gas flow set to 13 L/min, nebulizer set at 40 psi, fragmentor set at 140 V, and cell accelerator voltage set at 4V. Vancomycin collision energy for the quantifier and qualifier was set at 15 and 34 eV. Polymyxin B1 collision energy was set at 22 eV. The following transitions (m/z) for vancomycin and polymyxin B1 were identified and utilized: 725.6. → 144.1 for vancomycin quantifier, 725.6 → 100.1 for vancomycin qualifier, and 402.2 → 101.1 for polymyxin B1 quantifier. The assay was linear between concentrations 0.5 and 100 mg/L (R2 = 0.998) with an applied weight 1/x. The lower limit of quantification was 0.5 mg/L. Precision was <6.7% for all measurements, including intra- and inter-assay measurements. Greater than 92% of the analyte was recovered in all samples tested with an overall mean assay accuracy of 100%. Any samples measuring above the upper limit of quantification were diluted.Determination of urinary biomarkers of AKI Urine samples were analyzed in batch to determine concentrations of clusterin, KIM-1, and OPN. Microsphere-based Luminex X-MAP technology was used for the determination of all biomarker concentrations, as previously described. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Qcm96aWFsZWNrPC9BdXRob3I+PFllYXI+MjAwOTwvWWVh
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ADDIN EN.CITE.DATA 24, 25 Urine samples were aliquoted into 96-well plates supplied with MILLIPLEX? MAP Rat Kidney Toxicity Magnetic Bead Panels 1 and 2 (EMD Millipore Corporation, Charles, MO), prepared and analyzed according to the manufacturer’s recommendations. Vancomycin pharmacokinetic model and exposure determination One- and 2-compartment rate constant (Ke) models solved algebraically (minus the absorption constant in the stock model for the program) ADDIN EN.CITE <EndNote><Cite><RecNum>236</RecNum><DisplayText><style face="superscript">26</style></DisplayText><record><rec-number>236</rec-number><foreign-keys><key app="EN" db-id="r0s5vvwwmrwafsee20pvt5d5erzza5zapf2d" timestamp="1551374573">236</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors></contributors><titles><title>Laboratory of Applied Pharmacokinetics and Bioinformatics Optimizing drug therapy for populations and individuals. Pmetrics Model Files. Available at were considered as base models and were fit using the nonparametric adaptive grid (NPAG) algorithm within the Pmetrics package version 1.5.0 (Los Angeles, CA) for R version 3.2.1 (R Foundation for Statistical Computing, Vienna, Austria). PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5OZWVseTwvQXV0aG9yPjxZZWFyPjIwMTI8L1llYXI+PFJl
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ADDIN EN.CITE.DATA 27, 28 Model performance was evaluated and compared utilizing a regression of observed versus predicted concentrations, visual plots of parameter estimates, Akaike information criterion (AIC), and the rule of parsimony. The initial estimate of parameter weighting was accomplished using the inverse of the assay variance. The observation variance was proportional with a scalar (gamma) to assay variance. Estimation of PK exposure profiles and statistical analysis The best-fit model was utilized to obtain median maximum a posteriori probability (MAP) Bayesian vancomycin plasma concentration estimates at 12-minute intervals over the 24 hour study period, generated from each animal’s measured vancomycin concentrations, exact dose, and dosing schedule. Bayesian posteriors for each animal were used to determine exposures over the 24 hour time period (i.e., AUC0-24h, CMAX0-24h, CMIN0-24h). The pharmacokinetic values CMAX0-24h and CMIN0-24h were calculated using ‘makeNCA’ within Pmetrics (Los Angeles, CA, USA). PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5OZWVseTwvQXV0aG9yPjxZZWFyPjIwMTI8L1llYXI+PFJl
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ADDIN EN.CITE.DATA 27, 29 The highest predicted concentration was determined to be each individual animal’s CMAX0-24h, and the concentration at hour 24 following the initial vancomycin dose was determined to be that subject’s CMIN0-24h. Twenty-four hour exposure, as measured by AUC0-24h, was calculated using the trapezoidal rule under the Pmetrics command “makeAUC”. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5OZWVseTwvQXV0aG9yPjxZZWFyPjIwMTI8L1llYXI+PFJl
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ADDIN EN.CITE.DATA 27, 29 PK exposure measure variability was calculated as the coefficient of variation percent (CV%). Relationships between PK exposure parameters were evaluated using Spearman’s rank coefficient (rs) as described below. Association of PK measures with urinary AKI biomarkers Exposure parameters were assessed for relationships with urinary biomarkers using GraphPad Prism version 7.02 (GraphPad Software Inc., La Jolla, CA). PK/TD exposure-response relationships were evaluated using Spearman’s rs and Hill-type functions; log transformations of variables (i.e., Log2 and Log10) were employed to explore the relationship between PK parameters and urinary biomarkers. The 90th percentile effective concentration (EC90) for each PK exposure versus specific biomarker was calculated from the best-fit Hill model. The EC90 was selected on the basis that 1) an antecedent value of KIM-1 >16 ng/mL was identified to predict AKI two days prior to event (83% sensitivity and 95% specificity) PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Nb3JhbGVzLUJ1ZW5yb3N0cm88L0F1dGhvcj48WWVhcj4y
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ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Nb3JhbGVzLUJ1ZW5yb3N0cm88L0F1dGhvcj48WWVhcj4y
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ADDIN EN.CITE.DATA 30, 2) that KIM-1 values of 16.5 ng/mL corresponded to the 90th percentile for values in our model, and 3) KIM-1 is the primary biomarker of interest as it is specific to the proximal tubule and associated with VIKI. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5PJmFwb3M7RG9ubmVsbDwvQXV0aG9yPjxZZWFyPjIwMTc8
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ADDIN EN.CITE.DATA 17, 31Statistical analysis for between treatment group comparisons Urine output, body weight loss, and PK exposure measures were compared across vancomycin total daily dose and dosing frequency groups. Log transformations were employed as needed to maintain parametric distributions. Differences were evaluated either using Student’s t-test or the Wilcoxon rank sum test, as appropriate. Regressions on biomarkers were completed with categories treated as the dependent variable and control animals set as the referent category. All tests were two-tailed, with an a priori level of statistical significance set at an alpha of 0.05.ResultsCharacteristics of animal cohortAll 45 dosing protocol animals contributed model data. Mean weight loss and urine output was not significantly different between controls and vancomycin dosing protocol animals (4.8g versus 8.6g, p=0.35, 16.86mL versus 15.74mL, p=0.59; Table 1). Three animals (two animals in the 150mg twice daily cohort and one from the 400mg once daily cohort) did not complete the full protocol given either complications from surgery or anesthesia (Figure 1). Of these three animals, only n=1 from 150mg vancomycin twice daily contributed 12 hour urinary biomarker data. Analyses were run including and excluding this animal. Since all interpretations were identical when excluding the animal with only 12-hour urine (data not shown), the animal was included for all analyses. All animals contributed PK data and were thus included for PK study. All available/appropriate vancomycin plasma samples and urine biomarkers were utilized for model building and post hoc Bayesian posterior generation. Vancomycin PK models, parameter estimates and exposuresModels were successfully fit for one- and two-compartment models. A two-compartmental model was chosen as the final model given it was the most parsimonious with the least bias/imprecision and the lowest AIC compared to other models. The overall PK exposures for all rats are summarized in Table 2. The final model’s population mean parameter values (SD) for Ke, V, KCP and KPC were: 0.6 hr-1 (0.38), 0.11 L (0.08), 5.33 hr-1 (8.5), 3.66 hr-1 (6.56), respectively. Model predictive performance for: observed versus Bayesian predicted concentrations, bias, imprecision (i.e., bias-adjusted mean weighted squared prediction error) and the coefficient of determination (R2) were 0.49 mg/L, 34 (mg/L)2, and 0.97 respectively (Figure 2). Pharmacokinetic exposures (i.e. AUC0-24h, CMAX0-24h, CMIN0-24h) were variably correlated when assessed using Spearman’s rs correlation coefficient (AUC-CMAX, rs = 0.92; AUC-CMIN, rs =0.76, CMAX-CMIN, rs = 0.62; p-values<0.01), displayed in Table 3. Urinary BiomarkersUrinary biomarkers (KIM-1, clusterin, and OPN) for the vancomycin dosing group were all significantly different from control (p<0.05), displayed in Table 1. For KIM-1, the median (IQR) for control versus vancomycin group was 1.02 (0.88-1.05) and 12.3 (5.6-13.9), respectively, p<0.001. For clusterin, the median (IQR) for control versus vancomycin group was 319.5 (308.9-332.2) and 879.4 (617.6-1362), respectively p=0.0043. For OPN, the median (IQR) for control versus vancomycin group was 0.02 (0.01-0.03) and 0.218 (0.11-0.39), respectively p<0.001. Exposure-Response Relationships and EC90Four parameter Hill models best described the exposure:biomarker relationships. Exposure:biomarker relationships were found between AUC0-24 versus KIM-1 and OPN (R2=0.61 and R2=0.66) and CMAX0-24 versus KIM-1 and OPN (R2=0.50 and R2=0.56). Conversely, CMIN0-24h and mg/kg/day was less predictive of KIM-1(R2=0.46 and R2=0.47) and OPN (R2=0.53 and R2=0.50). All exposure-biomarker relationships are shown in Figure 3. The EC90 (95% confidence interval [CI]) for PK/TD pairs were as follows: AUC0-24h versus KIM-1 (482.2 mg/L*24h, CI: 320.2-1030) and OPN (939.4 mg/L*24h, CI: 539.9-3171); CMAX0-24 versus KIM-1 (323.1 mg/L, CI: unable to estimate) and OPN (695.8 mg/L, CI: unable to estimate); CMIN0-24h versus KIM-1(CI: unable to estimate) and OPN (17.45 mg/L CI: unable to estimate).PK/TD Correlations Correlations of urinary biomarkers and vancomycin exposure metrics (i.e., AUC0-24h, CMAX0-24h, CMIN0-24h) are shown in Table 4. KIM-1 was highly correlated with AUC0-24h (rs=0.53, p<0.01). OPN demonstrated the highest correlation with AUC0-24h (rs=0.75, p<0.01), followed by CMAX0-24h and CMIN0-24h (Both: rs=0.68, p<0.01). Correlations between CMIN0-24h and urinary biomarkers were less pronounced, and clusterin was less correlated with all biomarkers (data not shown).DiscussionIn this study, we found that AUC0-24h and CMAX0-24h were highly correlated with increased urinary concentrations of KIM-1 and OPN. CMIN0-24h was less correlated with AKI measures. Here, we identified that an AUC0-24h of 482.2 mg/L*24h and a CMAX of 323.1 mg/L, was associated with a 90% maximal increase in KIM-1 within a 24-hour period. We believe KIM-1 to be the most relevant urinary biomarker as it is specific for proximal tubule injury. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5LaW5nPC9BdXRob3I+PFllYXI+MjAwNDwvWWVhcj48UmVj
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AG==
ADDIN EN.CITE.DATA 17, 32, 33 OPN, on the other hand, is more generically indicative of non-specific tubule or glomeruli damage. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5GdWNoczwvQXV0aG9yPjxZZWFyPjIwMTI8L1llYXI+PFJl
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ADDIN EN.CITE.DATA 21, 34 Further studies looking into this are warranted. Our previous work indicates that KIM-1 is more specific to the proximal tubule in VIKI as it was correlated with proximal tubule injury score PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5PJmFwb3M7RG9ubmVsbDwvQXV0aG9yPjxZZWFyPjIwMTc8
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ADDIN EN.CITE.DATA 17 and this is consistent with the known mechanistic effect ADDIN EN.CITE <EndNote><Cite><Author>King</Author><Year>2004</Year><RecNum>113</RecNum><DisplayText><style face="superscript">32</style></DisplayText><record><rec-number>113</rec-number><foreign-keys><key app="EN" db-id="r0s5vvwwmrwafsee20pvt5d5erzza5zapf2d" timestamp="1533579048">113</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>King, D. W.</author><author>Smith, M. A.</author></authors></contributors><auth-address>School of Public Health, University of Texas-Houston Health Science Center, Houston, TX 77030, USA. dking@</auth-address><titles><title>Proliferative responses observed following vancomycin treatment in renal proximal tubule epithelial cells</title><secondary-title>Toxicol In Vitro</secondary-title></titles><periodical><full-title>Toxicol In Vitro</full-title></periodical><pages>797-803</pages><volume>18</volume><number>6</number><keywords><keyword>Adenosine Triphosphate/metabolism</keyword><keyword>Animals</keyword><keyword>Anti-Bacterial Agents/pharmacology/*toxicity</keyword><keyword>Cell Culture Techniques</keyword><keyword>Cell Cycle/drug effects</keyword><keyword>Cell Proliferation/*drug effects</keyword><keyword>Dose-Response Relationship, Drug</keyword><keyword>Kidney/*drug effects/*pathology</keyword><keyword>Kidney Tubules, Proximal/cytology/*pathology</keyword><keyword>Mitochondria/physiology</keyword><keyword>Mitogens/pharmacology</keyword><keyword>Oxygen Consumption</keyword><keyword>Signal Transduction</keyword><keyword>Swine</keyword><keyword>Vancomycin/pharmacology/*toxicity</keyword></keywords><dates><year>2004</year><pub-dates><date>Dec</date></pub-dates></dates><isbn>0887-2333 (Print)
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ADDIN EN.CITE.DATA 30 It is notable that our identified AUC target is in agreement with a prospective multi-center clinical study of vancomycin concentrations at day two that cause acute kidney injury (as defined by defined as a ≥1.5-fold increase in serum creatinine for patients with a baseline creatinine <2.0 mg/dL) during vancomycin therapy. ADDIN EN.CITE <EndNote><Cite><Author>Lodise TP</Author><Year>2017</Year><RecNum>118</RecNum><DisplayText><style face="superscript">35</style></DisplayText><record><rec-number>118</rec-number><foreign-keys><key app="EN" db-id="r0s5vvwwmrwafsee20pvt5d5erzza5zapf2d" timestamp="1533659095">118</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lodise TP, Rosenkranz SL, Finnemeyer M, Huvane J, Pereira A, Scheetz MH, </style><style face="italic" font="default" size="100%">et al</style></author></authors></contributors><titles><title>The Emperor’s New Clothes: Prospective Observational Evaluation of the Association between the Day 2 Vancomycin Exposure and Failure Rates among Adult Hospitalized Patients with MRSA Bloodstream Infections (PROVIDE). Oral Presentation 985. ID Week. San Diego, CA. 2017</title></titles><dates><year>2017</year></dates><urls></urls></record></Cite></EndNote>35 The results of the clinical study demonstrated that the first risk stratification by CART analysis occurred between 343 and 793 mg/L*24h ADDIN EN.CITE <EndNote><Cite><Author>Lodise TP</Author><Year>2017</Year><RecNum>118</RecNum><DisplayText><style face="superscript">35</style></DisplayText><record><rec-number>118</rec-number><foreign-keys><key app="EN" db-id="r0s5vvwwmrwafsee20pvt5d5erzza5zapf2d" timestamp="1533659095">118</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lodise TP, Rosenkranz SL, Finnemeyer M, Huvane J, Pereira A, Scheetz MH, </style><style face="italic" font="default" size="100%">et al</style></author></authors></contributors><titles><title>The Emperor’s New Clothes: Prospective Observational Evaluation of the Association between the Day 2 Vancomycin Exposure and Failure Rates among Adult Hospitalized Patients with MRSA Bloodstream Infections (PROVIDE). Oral Presentation 985. ID Week. San Diego, CA. 2017</title></titles><dates><year>2017</year></dates><urls></urls></record></Cite></EndNote>35, which agrees with the threshold of 482 mg/L*24h that we found. We believe that our results can be viewed as similar to minimum inhibitory concentration testing for bacterial resistance classification. While the testing conditions are different from the clinical environment (i.e. MIC testing environment does not mimic a standard physiologic environment), the numerical agreement of the surrogate (e.g. MIC to clinical efficacy) is important for predicting downstream patient outcomes. Hence, we believe that the 24-hour intravenous rat model and biomarker thresholds will be translatable for early identification of meaningful kidney injury. Notably, our results are also qualitatively similar to our previous rat studies when we utilized doses between 150-400 mg/kg either given as a single or twice daily intraperitoneal injections. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5PJmFwb3M7RG9ubmVsbDwvQXV0aG9yPjxZZWFyPjIwMTc8
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ADDIN EN.CITE.DATA 19, 21 conducting vancomycin dose-response studies have similarly identified KIM-1 and OPN as sensitive and specific biomarkers predictive of kidney damage in rat models. Our results and concordance amongst the works provides further evidence to support that vancomycin CMIN is not likely the parameter that mediates VIKI. Notably, the current vancomycin treatment guidelines focus solely on the measurement of trough concentrations. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5SeWJhazwvQXV0aG9yPjxZZWFyPjIwMDk8L1llYXI+PFJl
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ADDIN EN.CITE.DATA 36The present study focuses on IV treated rats utilizing a range of dosages to allometrically scale low to high clinical exposures. IV dosing offers several advantages. First, in contrast to IP dose, there is a more predictable and reproducible exposure profile with IV dosing. This is important because erratic absorption from IP studies requires that multiple samples are drawn after every dose (in order to characterize each exposure curve). In small animal studies, the number of blood samples possible are limited. Second, with IP dosing, vancomycin may inadvertently be injected into the retroperitoneal space and serve as a direct nephrotoxin via external contact. Additionally, there is a remote possibility for the injection to physically damage the kidney. Thus, IV dosing in rats represents a more reflective biodistribution profile to that seen in typical clinical use in humans and additionally avoids unnecessary variability. Importantly, our data reinforces that the rat model is highly translational for understanding vancomycin-induced kidney damage. In the clinical setting, the median onset of vancomycin-induced AKI has been reported as 6-7 days into therapy, but these studies have relied on traditional and insensitive markers of AKI such as SCr and BUN. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Mb2Rpc2U8L0F1dGhvcj48WWVhcj4yMDA5PC9ZZWFyPjxS
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ADDIN EN.CITE.DATA 8, 12, 13 We previously analyzed Scr in animals and found no relationship in the 24 hour to 3 day studies, likely since SCr and BUN did not have enough time to become demonstrably elevated. As SCr requires 30-50% parenchymal damage before detectability, kidney injury can be severe before changes in SCr can be detected. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5EdWFydGU8L0F1dGhvcj48WWVhcj4xOTkzPC9ZZWFyPjxS
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ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5EdWFydGU8L0F1dGhvcj48WWVhcj4xOTkzPC9ZZWFyPjxS
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ADDIN EN.CITE.DATA 37 Using sensitive biomarkers for detection of early kidney damage may allow for early indication of renal injury and enable clinicians to change therapy prior to more substantial damage. Both the FDA and EMEA have issued letters of support for KIM-1 and OPN. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5EaWV0ZXJsZTwvQXV0aG9yPjxZZWFyPjIwMTA8L1llYXI+
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ADDIN EN.CITE.DATA 40, 41 Further, urinary biomarkers (e.g. KIM-1 and Clusterin) are already qualified for rat ADDIN EN.CITE <EndNote><Cite><RecNum>250</RecNum><DisplayText><style face="superscript">42</style></DisplayText><record><rec-number>250</rec-number><foreign-keys><key app="EN" db-id="r0s5vvwwmrwafsee20pvt5d5erzza5zapf2d" timestamp="1551388914">250</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors></contributors><titles><title>US Food and Drug Administration. Critical Path Institute's Predictive Safety Testing Consortium Nephrotoxicity Working Group (CPATH PSTC-NWG), and Foundation for the National Institutes of Health’s Biomarker Consortium Kidney Safety Biomarker Project Team (FNIH BC-KSP). Urinary nephrotoxicity biomarker panel as assessed by immunoassays. Safety biomarker to be used with traditional indicators to indicate renal injury in rat. Available at and human ADDIN EN.CITE <EndNote><Cite><RecNum>251</RecNum><DisplayText><style face="superscript">43</style></DisplayText><record><rec-number>251</rec-number><foreign-keys><key app="EN" db-id="r0s5vvwwmrwafsee20pvt5d5erzza5zapf2d" timestamp="1551389626">251</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors></contributors><titles><title>US Food and Drug Administration. Critical Path Institute's Predictive Safety Testing Consortium Nephrotoxicity Working Group (CPATH PSTC-NWG), and Foundation for the National Institutes of Health’s Biomarker Consortium Kidney Safety Biomarker Project Team (FNIH BC-KSP). Urinary nephrotoxicity biomarker panel as assessed by immunoassays. Safety biomarker panel to aid in the detection of kidney tubular injury in phase 1 trials in healthy volunteers. Available at . </title></titles><dates></dates><urls></urls></record></Cite></EndNote>43 drug trials by the FDA (i.e. for drug induced AKI). Thus, our results and agreement with robust clinical data indicate that KIM-1 can serve as an early surrogate for realized kidney injury. We acknowledge several limitations in our study. First, our study was limited to 24 hour dosing. However as previously noted, elevations in biomarkers have already been linked to histopathologic damage within this time period PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5WYWlkeWE8L0F1dGhvcj48WWVhcj4yMDEwPC9ZZWFyPjxS
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ADDIN EN.CITE.DATA 19. Despite the one day nature of our study, we have demonstrated similar AUC thresholds to those identified in humans. ADDIN EN.CITE <EndNote><Cite><Author>Lodise TP</Author><Year>2017</Year><RecNum>118</RecNum><DisplayText><style face="superscript">35</style></DisplayText><record><rec-number>118</rec-number><foreign-keys><key app="EN" db-id="r0s5vvwwmrwafsee20pvt5d5erzza5zapf2d" timestamp="1533659095">118</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lodise TP, Rosenkranz SL, Finnemeyer M, Huvane J, Pereira A, Scheetz MH, </style><style face="italic" font="default" size="100%">et al</style></author></authors></contributors><titles><title>The Emperor’s New Clothes: Prospective Observational Evaluation of the Association between the Day 2 Vancomycin Exposure and Failure Rates among Adult Hospitalized Patients with MRSA Bloodstream Infections (PROVIDE). Oral Presentation 985. ID Week. San Diego, CA. 2017</title></titles><dates><year>2017</year></dates><urls></urls></record></Cite></EndNote>35 Thus we suggest that this model is a surrogate for clinical human outcomes. Second, this study does not effectively separate CMAX and AUC, and additional studies will be needed to understand which is the primary driver of toxicity. These future studies will have implications for dosing administration time (e.g., continuous infusion versus intermittent infusion). Notably this study employed allometric scaled doses which is different than parameter scaling (matching Cmax in the rat to the human Cmax). ADDIN EN.CITE <EndNote><Cite><Author>Reisfeld</Author><Year>2012</Year><RecNum>230</RecNum><DisplayText><style face="superscript">44</style></DisplayText><record><rec-number>230</rec-number><foreign-keys><key app="EN" db-id="r0s5vvwwmrwafsee20pvt5d5erzza5zapf2d" timestamp="1537379998">230</key></foreign-keys><ref-type name="Book">6</ref-type><contributors><authors><author>Reisfeld, Brad</author><author>Mayeno, Arthur N.</author></authors></contributors><titles><title>Computational toxicology</title><secondary-title>Methods in molecular biology,</secondary-title></titles><number>929-930</number><num-vols>2</num-vols><keywords><keyword>Toxicology Data processing.</keyword><keyword>Computational Biology Laboratory Manuals.</keyword><keyword>Toxicology Laboratory Manuals.</keyword><keyword>Biological Markers Laboratory Manuals.</keyword><keyword>Models, Theoretical Laboratory Manuals.</keyword></keywords><dates><year>2012</year></dates><pub-location>New York</pub-location><publisher>Humana Press ; Springer</publisher><isbn>9781627030496 (v. 1 alk. paper)
1627030492 (v. 1 alk. paper)
9781627030588 (v. 2 alk. paper)
1627030581 (v. 2 alk. paper)
1064-3745 ;</isbn><accession-num>17429409</accession-num><call-num>RA1193.4 .C66 2012</call-num><urls></urls></record></Cite></EndNote>44 FDA guidance suggests allometrically scaled doses for toxicological analysis. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5NZWxsZW48L0F1dGhvcj48WWVhcj4yMDE3PC9ZZWFyPjxS
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ADDIN EN.CITE.DATA 45 Tethered animal models employing continuous infusion are needed for parameter scaling, and it is not clear if these results will be more translational the current studies. Third when fitting the data to the TD model, some mathematic relationships were not sufficient for defining the 95% CI of the EC90. For CMIN, this is due to overall poor model fit. It will be necessary to design studies to formally compare AUC to CMAX to fully define the PK/TD link; however for standard intermittent infusions, our AUC data are presently the most translational. Fourth, clinical studies have not identified single urinary biomarkers that are highly specific of drug induced kidney injury where multi-factorial processes are the rule rather than the exception . ADDIN EN.CITE <EndNote><Cite><Author>Ostermann</Author><Year>2007</Year><RecNum>105</RecNum><DisplayText><style face="superscript">46</style></DisplayText><record><rec-number>105</rec-number><foreign-keys><key app="EN" db-id="r0s5vvwwmrwafsee20pvt5d5erzza5zapf2d" timestamp="1527093594">105</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Ostermann, M.</author><author>Chang, R. W.</author></authors></contributors><auth-address>Department of Intensive Care, Guy's and St Thomas' Hospital, London, UK. marlies@ostermann.freeserve.co.uk</auth-address><titles><title>Acute kidney injury in the intensive care unit according to RIFLE</title><secondary-title>Crit Care Med</secondary-title></titles><periodical><full-title>Crit Care Med</full-title></periodical><pages>1837-43; quiz 1852</pages><volume>35</volume><number>8</number><keywords><keyword>Acute Kidney Injury/classification/*diagnosis/mortality</keyword><keyword>Adolescent</keyword><keyword>Adult</keyword><keyword>Aged</keyword><keyword>Aged, 80 and over</keyword><keyword>Female</keyword><keyword>Germany/epidemiology</keyword><keyword>Hospital Mortality</keyword><keyword>Humans</keyword><keyword>Intensive Care Units</keyword><keyword>Logistic Models</keyword><keyword>Male</keyword><keyword>Middle Aged</keyword><keyword>Multivariate Analysis</keyword><keyword>Prognosis</keyword><keyword>ROC Curve</keyword><keyword>Reproducibility of Results</keyword><keyword>Retrospective Studies</keyword><keyword>Risk Factors</keyword><keyword>*Severity of Illness Index</keyword><keyword>United Kingdom/epidemiology</keyword></keywords><dates><year>2007</year><pub-dates><date>Aug</date></pub-dates></dates><isbn>0090-3493 (Print)
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ADDIN EN.CITE.DATA 48 These quantitative relationships require further exploration and clinical trials. In summary, these data demonstrate that VIKI is caused by either elevated peak plasma concentrations (CMAX0-24) or total plasma exposure (AUC0-24) of vancomycin rather than with troughs (CMIN0-24). These findings may have clinical implications for vancomycin monitoring schemes. Further clarification of the drivers of VIKI are needed to improve dosing regimens that maximize efficacy while minimizing toxicity. Finally, our study demonstrates the utility of the rat model for understanding PK/TD for vancomycin. Acknowledgments: We kindly acknowledge the Core Facility at Midwestern University for access to the LCMS-MS. Funding: Research reported in this publication was supported by National Institute of Allergy and Infectious Diseases under award number R15-AI105742. 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Does Piperacillin-Tazobactam Increase the Risk of Nephrotoxicity when Used with Vancomycin: A Meta-Analysis of Observational Trials. Current drug safety 2017; 12: 62-6.46.Ostermann M, Chang RW. Acute kidney injury in the intensive care unit according to RIFLE. Crit Care Med 2007; 35: 1837-43; quiz 52.47.Schley G, Koberle C, Manuilova E et al. Comparison of Plasma and Urine Biomarker Performance in Acute Kidney Injury. PLoS One 2015; 10: e0145042.48.Zhang Z, Humphreys BD, Bonventre JV. Shedding of the urinary biomarker kidney injury molecule-1 (KIM-1) is regulated by MAP kinases and juxtamembrane region. J Am Soc Nephrol 2007; 18: 2704-14.Figure 1. Randomization and animal dosing flow chart Abbreviations: IV= intravenous, TDD= total daily dose, x1= once daily dose, q12h twice daily doseFigure 2. Best fit plot for Bayesian observed versus predicted plasma vancomycin concentrations utilizing the final 2-compartmental model Figure 3. AUC0-24 (mg*h/L), CMAX0-24 (mg/L), and CMIN0-24 (mg/L) versus urinary biomarkers KIM-1# (A, B, C) and OPN* (D, E, F) relationship by 4-Parameter Hill model fit TD: 4-Parameter Hill model equation: Y=Bottom?+?(Top-Bottom)/(1+10^((LogEC50-X)*Hill Slope))Note: Data for clusterin not shown as did not show strong relationship or correlation. #units for biomarker in ng/mL. Biomarker values were Log2 transformed and exposure values were Log10 transformed. Abbreviations: AUC= area under the curve, CMAX= maximum concentration, CMIN= minimum concentration, KIM-1= kidney injury molecule-1, OPN= osteopontin, EC50= concentration at 50% of total biomarker rise Table 1: Summary of weight loss, urinary output, and urinary biomarkers Control Vancomycin P-value Number of animals (n) 545-Baseline Weight (g), mean ± SD 323.8 ± 22.42312.87 ± 15.370.16Weight loss (g), mean ± SD 4.8 ± 2.288.6 ± 8.95(n=40)* 0.35Urine output (mL), mean ± SD 16.86 ± 3.0715.74 ± 4.48 (n=41)* 0.59KIM-1 (ng/mL), median (IQR) 1.02 (0.88-1.05)12.3 (5.6-13.9)(n=43)** <0.001Clusterin (ng/mL), median (IQR)319.5 (308.9-332.2)879.4 (617.6-1362)(n=43)**0.0043OPN (ng/mL), median (IQR) 0.02 (0.01-0.03)0.218 (0.11-0.39)(n=43)** <0.001*Some values inadvertently not recorded**For animals completing urine endpoint Abbreviations: SD= standard deviation, KIM-1= kidney injury molecule-1, OPN= osteopontin, IQR= interquartile rangeTable 2: PK exposure summary for vancomycin treatment animals PK Exposure Vancomycin *(n=45)AUC0-24 (mg*h/L), median (IQR)643.1 (427.7-2769.4)CMAX0-24 (mg/L), median (IQR)350.9 (209.7-917.9)CMIN0-24 (mg/L), median (IQR)2.9 (0.8-36)* Controls were excluded given they did not receive vancomycin Abbreviations: PK=pharmacokinetics, AUC= area under the curve, CMAX= maximum concentration, CMIN= minimum concentrationTable 3: Spearman correlation between untransformed PK exposure parameters PK Exposure *(n=45)AUC0-24h(rs)CMAX0-24h(rs)CMIN0-24h(rs)AUC0-24h1--CMAX0-24h0.92 (p<0.001)1-CMIN0-24h0.76(p<0.001)0.62(p<0.001)1* Controls were excluded given they did not receive vancomycin Abbreviations: PK=pharmacokinetics, AUC= area under the curve, CMAX= maximum concentration, CMIN= minimum concentration, rs= Spearman correlation coefficientTable 4: Spearman Correlation for untransformed PK exposure parameters and urinary biomarkersBiomarker AUC0-24(rs)CMAX0-24(rs)CMIN0-24(rs)KIM-10.53 (p<0.001)0.40(p<0.001)0.49 (p<0.001)Clusterin0.27 (p=0.06)0.18(p=0.22)0.19 (p=0.19)OPN0.75 (p<0.001)0.68(p<0.001)0.68(p<0.001)Abbreviations: PK=pharmacokinetics, AUC= area under the curve, CMAX= maximum concentration, CMIN= minimum concentration, KIM-1= kidney injury molecule-1, OPN= osteopontin, rs= Spearman correlation coefficient ADDIN ................
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