Association between vancomycin minimum inhibitory concentration and mortality among patients with Staphylococcus aureus bloodstream infections: a systematic review and meta-analysis.
Kalil Andre C,Van Schooneveld Trevor C,Fey Paul D,Rupp Mark E
JAMA
IMPORTANCE:Staphylococcus aureus bacteremia (SAB) is a worldwide problem. It is unclear whether higher-vancomycin minimum inhibitory concentration (MIC) is associated with mortality. This potential association has direct consequences for patients and public health. DATA SOURCES:PubMed, Embase, the Cochrane Library, Evidence-based Medicine BMJ, and the American College of Physicians Journal Club were searched from inception through April 2014. STUDY SELECTION:Studies reporting mortality and vancomycin MIC in patients with SAB were included. DATA EXTRACTION AND SYNTHESIS:Two authors performed the literature search and the study selection separately. Random-effects modeling was used for all analyses. MAIN OUTCOMES AND MEASURES:All-cause mortality. FINDINGS:Among 38 included studies that involved 8291 episodes of SAB, overall mortality was 26.1%. The estimated mortality was 26.8% among SAB episodes (n = 2740) in patients with high-vancomycin MIC (≥1.5 mg/L) compared with 25.8% mortality among SAB episodes (n = 5551) in patients with low-vancomycin MIC (<1.5 mg/L) (adjusted risk difference [RD], 1.6% [95% CI, -2.3% to 5.6%]; P = .43). For the highest-quality studies, the estimated mortality was 26.2% among SAB episodes (n = 2318) in patients with high-vancomycin MIC compared with 27.8% mortality among SAB episodes (n = 4168) in patients with low-vancomycin MIC (RD, 0.9% [95% CI, -2.9% to 4.6%]; P = .65). In studies that included only methicillin-resistant S aureus infections (n = 7232), the mortality among SAB episodes (n = 2384) in patients with high-vancomycin MIC was 27.6% compared with mortality of 27.4% among SAB episodes (n = 4848) in patients with low-vancomycin MIC (adjusted RD, 1.6% [95% CI, -2.3% to 5.5%]; P = .41). No significant differences in risk of death were observed in subgroups with high-vancomycin MIC vs low-vancomycin MIC values across different study designs, microbiological susceptibility assays, MIC cutoffs, clinical outcomes, duration of bacteremia, previous vancomycin exposure, and treatment with vancomycin. CONCLUSIONS AND RELEVANCE:In this meta-analysis of SAB episodes, there were no statistically significant differences in the risk of death when comparing patients with S aureus exhibiting high-vancomycin MIC (≥1.5 mg/L) to those with low-vancomycin MIC (<1.5 mg/L), although the findings cannot definitely exclude an increased mortality risk. These findings should be considered when interpreting vancomycin susceptibility and in determining whether alternative antistaphylococcal agents are necessary for patients with SAB with elevated but susceptible vancomycin MIC values.
10.1001/jama.2014.6364
Innovative approaches to optimizing the delivery of vancomycin in individual patients.
Pai Manjunath P,Neely Michael,Rodvold Keith A,Lodise Thomas P
Advanced drug delivery reviews
The delivery of personalized antimicrobial therapy is a critical component in the treatment of patients with invasive infections. Vancomycin, the drug of choice for infections due to methicillin-resistant Staphylococcus aureus, requires the use of therapeutic drug monitoring (TDM) for delivery of optimal therapy. Current guidance on vancomycin TDM includes the measurement of a trough concentration as a surrogate for achieving an AUC to minimum inhibitory concentration (MIC) by broth microdilution (AUC/MICBMD) ratio≥400. Although trough-only monitoring has been widely integrated into clinical practice, there is a high degree of inter-individual variability between a measured trough concentration and the actual AUC value. The therapeutic discordance between AUC and trough may lead to suboptimal outcomes among patients with infections due to less susceptible pathogens or unnecessarily increase the probability of acute kidney injury (AKI) in others. Given the potentially narrow vancomycin AUC range for optimal effect and minimal AKI, clinicians need a "real-time" system to predict accurately the AUC with limited pharmacokinetic (PK) sampling. This article reviews two innovative approaches for calculating the vancomycin AUC in clinical practice based on one or two drug concentrations. One such approach involves the use of Bayesian computer software programs to estimate the "true" vancomycin AUC value with minimal PK sampling and provide AUC-guided dosing recommendations at the bedside. An alternative involves use of two concentrations (peak and trough) and simple analytic equations to estimate AUC values. Both approaches provide considerable improvements over the current trough-only concentration monitoring method.
10.1016/j.addr.2014.05.016
24-Hour Pharmacokinetic Relationships for Vancomycin and Novel Urinary Biomarkers of Acute Kidney Injury.
O'Donnell J Nicholas,Rhodes Nathaniel J,Lodise Thomas P,Prozialeck Walter C,Miglis Cristina M,Joshi Medha D,Venkatesan Natarajan,Pais Gwendolyn,Cluff Cameron,Lamar Peter C,Briyal Seema,Day John Z,Gulati Anil,Scheetz Marc H
Antimicrobial agents and chemotherapy
Vancomycin has been associated with acute kidney injury in preclinical and clinical settings; however, the precise exposure profiles associated with vancomycin-induced acute kidney injury have not been defined. We sought to determine pharmacokinetic/pharmacodynamics indices associated with the development of acute kidney injury using sensitive urinary biomarkers. Male Sprague-Dawley rats received clinical-grade vancomycin or normal saline as an intraperitoneal injection. Total daily doses between 0 and 400 mg/kg of body weight were administered as a single dose or 2 divided doses over a 24-h period. At least five rats were utilized for each dosing protocol. A maximum of 8 plasma samples per rat were obtained, and urine was collected over the 24-h period. Kidney injury molecule-1 (KIM-1), clusterin, osteopontin, cystatin C, and neutrophil gelatinase-associated lipocalin levels were determined using Milliplex multianalyte profiling rat kidney panels. Vancomycin plasma concentrations were determined via a validated high-performance liquid chromatography methodology. Pharmacokinetic analyses were conducted using the Pmetrics package for R. Bayesian maximal concentrations were generated and utilized to calculate the 24-h area under the concentration-time curve (AUC), the maximum concentration (), and the minimum concentration. Spearman's rank correlation coefficient ( ) was used to assess the correlations between exposure parameters, biomarkers, and histopathological damage. Forty-seven rats contributed pharmacokinetic and toxicodynamic data. KIM-1 was the only urinary biomarker that correlated with both composite histopathological damage ( = 0.348, = 0.017) and proximal tubule damage ( = 0.342, = 0.019). The vancomycin AUC and were most predictive of increases in KIM-1 levels ( = 0.438 and = 0.002 for AUC and = 0.451 and = 0.002 for ). Novel urinary biomarkers demonstrate that kidney injury can occur within 24 h of vancomycin exposure as a function of either AUC or .
10.1128/AAC.00416-17
Population Pharmacokinetic Modeling of Vancomycin in Thai Patients With Heterogeneous and Unstable Renal Function.
Therapeutic drug monitoring
BACKGROUND:Vancomycin is widely used to treat gram-positive bacterial infections. However, given significant interpatient variability in its pharmacokinetics, maintaining plasma concentrations is difficult within its characteristically narrow therapeutic window. This is especially challenging in patients with unstable renal function. Thus, the aim of this study was to develop a population pharmacokinetic model for vancomycin that is suitable for Thai patients with variable renal functions, including those with unstable renal function. METHODS:Data from 213 patients, including 564 blood samples, were retrospectively collected; approximately 70% patients exhibited unstable renal function during vancomycin treatment. The model building group was randomly assigned 108 patients and the remaining 33 patients comprised the validation group. A population pharmacokinetic model was developed that incorporated drug clearance (CL) as a function of time-varying creatine clearance (CrCL). The predictive ability of the resulting population model was evaluated using the validation data set, including its ability to forecast serum concentrations within a Bayesian feedback algorithm. RESULTS:A 2-compartment model with drug CL values that changed with time-varying CrCL adequately described vancomycin pharmacokinetics in the evaluated heterogeneous patient population with unstable renal function. Vancomycin CL was related to time-varying CrCL as follows: CL (t) = 0.11 + 0.021 × CrCL (t) (CrCL <120 mL/min. Using the population model, Bayesian estimation with at least one measured serum concentration resulted in a forecasting error of small bias (-2.4%) and adequate precision (31.5%). CONCLUSIONS:In hospitals with a high incidence of unstable renal function, incorporating time-varying CrCL with Bayesian estimation and at least one measured drug concentration, along with frequent CrCL monitoring, improves the predictive performance of therapeutic drug monitoring of vancomycin.
10.1097/FTD.0000000000000801
Are vancomycin trough concentrations adequate for optimal dosing?
Neely Michael N,Youn Gilmer,Jones Brenda,Jelliffe Roger W,Drusano George L,Rodvold Keith A,Lodise Thomas P
Antimicrobial agents and chemotherapy
The current vancomycin therapeutic guidelines recommend the use of only trough concentrations to manage the dosing of adults with Staphylococcus aureus infections. Both vancomycin efficacy and toxicity are likely to be related to the area under the plasma concentration-time curve (AUC). We assembled richly sampled vancomycin pharmacokinetic data from three studies comprising 47 adults with various levels of renal function. With Pmetrics, the nonparametric population modeling package for R, we compared AUCs estimated from models derived from trough-only and peak-trough depleted versions of the full data set and characterized the relationship between the vancomycin trough concentration and AUC. The trough-only and peak-trough depleted data sets underestimated the true AUCs compared to the full model by a mean (95% confidence interval) of 23% (11 to 33%; P = 0.0001) and 14% (7 to 19%; P < 0.0001), respectively. In contrast, using the full model as a Bayesian prior with trough-only data allowed 97% (93 to 102%; P = 0.23) accurate AUC estimation. On the basis of 5,000 profiles simulated from the full model, among adults with normal renal function and a therapeutic AUC of ≥400 mg · h/liter for an organism for which the vancomycin MIC is 1 mg/liter, approximately 60% are expected to have a trough concentration below the suggested minimum target of 15 mg/liter for serious infections, which could result in needlessly increased doses and a risk of toxicity. Our data indicate that adjustment of vancomycin doses on the basis of trough concentrations without a Bayesian tool results in poor achievement of maximally safe and effective drug exposures in plasma and that many adults can have an adequate vancomycin AUC with a trough concentration of <15 mg/liter.
10.1128/AAC.01653-13
Optimizing the Clinical Use of Vancomycin.
Álvarez Rocío,López Cortés Luis E,Molina José,Cisneros José M,Pachón Jerónimo
Antimicrobial agents and chemotherapy
The increasing number of infections produced by beta-lactam-resistant Gram-positive bacteria and the morbidity secondary to these infections make it necessary to optimize the use of vancomycin. In 2009, the American Society of Health-System Pharmacists, the Infectious Diseases Society of America, and the Society of Infectious Disease Pharmacists published specific guidelines about vancomycin dosage and monitoring. However, these guidelines have not been updated in the past 6 years. This review analyzes the new available information about vancomycin published in recent years regarding pharmacokinetics and pharmacodynamics, serum concentration monitoring, and optimal vancomycin dosing in special situations (obese people, burn patients, renal replacement therapy, among others). Vancomycin efficacy is linked to a correct dosage which should aim to reach an area under the curve (AUC)/MIC ratio of ≥400; serum trough levels of 15 to 20 mg/liter are considered a surrogate marker of an AUC/MIC ratio of ≥400 for a MIC of ≤1 mg/liter. For Staphylococcus aureus strains presenting with a MIC >1 mg/liter, an alternative agent should be considered. Vancomycin doses must be adjusted according to body weight and the plasma trough levels of the drug. Nephrotoxicity has been associated with target vancomycin trough levels above 15 mg/liter. Continuous infusion is an option, especially for patients at high risk of renal impairment or unstable vancomycin clearance. In such cases, vancomycin plasma steady-state level and creatinine monitoring are strongly indicated.
10.1128/AAC.03147-14
Development of a Physiologically Based Pharmacokinetic Modelling Approach to Predict the Pharmacokinetics of Vancomycin in Critically Ill Septic Patients.
Radke Christian,Horn Dagmar,Lanckohr Christian,Ellger Björn,Meyer Michaela,Eissing Thomas,Hempel Georg
Clinical pharmacokinetics
BACKGROUND AND OBJECTIVES:Sepsis is characterised by an excessive release of inflammatory mediators substantially affecting body composition and physiology, which can be further affected by intensive care management. Consequently, drug pharmacokinetics can be substantially altered. This study aimed to extend a whole-body physiologically based pharmacokinetic (PBPK) model for healthy adults based on disease-related physiological changes of critically ill septic patients and to evaluate the accuracy of this PBPK model using vancomycin as a clinically relevant drug. METHODS:The literature was searched for relevant information on physiological changes in critically ill patients with sepsis, severe sepsis and septic shock. Consolidated information was incorporated into a validated PBPK vancomycin model for healthy adults. In addition, the model was further individualised based on patient data from a study including ten septic patients treated with intravenous vancomycin. Models were evaluated comparing predicted concentrations with observed patient concentration-time data. RESULTS:The literature-based PBPK model correctly predicted pharmacokinetic changes and observed plasma concentrations especially for the distribution phase as a result of a consideration of interstitial water accumulation. Incorporation of disease-related changes improved the model prediction from 55 to 88% within a threshold of 30% variability of predicted vs. observed concentrations. In particular, the consideration of individualised creatinine clearance data, which were highly variable in this patient population, had an influence on model performance. CONCLUSION:PBPK modelling incorporating literature data and individual patient data is able to correctly predict vancomycin pharmacokinetics in septic patients. This study therefore provides essential key parameters for further development of PBPK models and dose optimisation strategies in critically ill patients with sepsis.
10.1007/s40262-016-0475-3
Using a Vancomycin PBPK Model in Special Populations to Elucidate Case-Based Clinical PK Observations.
Emoto Chie,Johnson Trevor N,McPhail Brooks T,Vinks Alexander A,Fukuda Tsuyoshi
CPT: pharmacometrics & systems pharmacology
Simultaneous changes in several physiological factors may contribute to the large pharmacokinetic (PK) variability of vancomycin. This study was designed to systematically characterize the effects of multiple physiological factors to the altered PK of vancomycin observed in special populations. A vancomycin physiologically based pharmacokinetic (PBPK) model was developed as a PK simulation platform to quantitatively assess the effects of changes in physiologies to the PK profiles. The developed model predicted the concentration-time profiles in healthy adults and diseased patients. The implementation of developmental changes in both renal and non-renal elimination pathways to the pediatric model improved the predictability of vancomycin clearance. Simulated PK profiles with a 50% decrease in cardiac output (peak plasma concentration (C ), 59.9 ng/mL) were similar to those observed in patients before bypass surgery (C , 55.1 ng/mL). The PBPK modeling of vancomycin demonstrated its potential to provide mechanistic insights into the altered disposition observed in patients who have changes in multiple physiological factors.
10.1002/psp4.12279
Development and Validation of a Risk Prediction Model of Vancomycin-Associated Nephrotoxicity in Elderly Patients: A Pilot Study.
Pan Chen,Wen Aiping,Li Xingang,Li Dandan,Zhang Yang,Liao Yin,Ren Yue,Shen Su
Clinical and translational science
This exploratory study aimed to develop a risk prediction model of vancomycin-associated nephrotoxicity (VANT) in elderly patients. Clinical information of elderly patients who received vancomycin therapy from January 2016 to June 2018 was retrieved. A total of 255 patients were included in this study. Univariate analysis and multivariable logistic regression analysis revealed that vancomycin trough concentration ≥ 20 mg/L (odds ratio (OR) = 3.009; 95% confidence interval (CI) 1.345-6.732), surgery (OR = 3.357; 95% CI 1.309-8.605), the Charlson Comorbidities Index ≥ 4 points (OR = 2.604; 95% CI 1.172-5.787), concomitant use of cardiotonic drug (OR = 3.283; 95% CI 1.340-8.042), plasma volume expander (OR = 3.459; 95% CI 1.428-8.382), and piperacillin/tazobactam (OR = 2.547; 95% CI 1.680-6.007) were risk factors for VANT in elderly patients. Furthermore, a VANT risk prediction model was developed, which had good discriminative power and was well-calibrated.
10.1111/cts.12731
Evaluation of the Effectiveness of Dose Individualization to Achieve Therapeutic Vancomycin Concentrations.
Abulfathi Ahmed A,Chirehwa Maxwell,Rosenkranz Bernd,Decloedt Eric H
Journal of clinical pharmacology
The glycopeptide antibiotic vancomycin is used for treatment of methicillin-resistant Gram-positive cocci. Adequate vancomycin plasma concentrations are related to bacterial cure. However, inter- and intrapatient variability make it difficult to achieve therapeutic vancomycin concentrations. The primary objective of this study was to determine the effectiveness of using computerized therapeutic drug monitoring (TDM) to assist in achieving therapeutic vancomycin concentrations at a tertiary hospital in South Africa. This was a 2-period study consisting of a retrospective 1-month observational period followed by a prospective 1-month period in which computerized TDM was implemented as an intervention to assist with vancomycin dose individualization. During the prospective period, all vancomycin TDM results were followed by dosage individualization using computerized TDM. The retrospective period included 77 patients with 292 vancomycin concentrations: 69% (53/77) adult and 31% (24/77) pediatric patients. The prospective period included 80 patients with 217 vancomycin concentrations measured: 69% (55/80) adult and 31% (25/80) pediatric patients. Fewer vancomycin TDM data were requested during the prospective period with a median (interquartile range) of 2 (1-3) samples per patient compared with 3 (1-5) samples per patient during the retrospective period. The odds ratio of achieving therapeutic trough concentrations was 3.63 (95%CI 1.81-7.3) in the prospective period when TDM-adjusted vancomycin dosing and appropriate TDM procedures were applied. The use of computerized TDM resulted in a higher frequency of therapeutic vancomycin concentrations in a middle-income setting. Trough vancomycin concentrations alone correlate poorly with the area under plasma concentration-time curve from 0 to 24 hours.
10.1002/jcph.1254
Comparison of the Area Under the Curve for Vancomycin Estimated Using Compartmental and Noncompartmental Methods in Adult Patients With Normal Renal Function.
Shingde Rashmi V,Graham Garry G,Reuter Stephanie E,Carland Jane E,Day Richard O,Stocker Sophie L
Therapeutic drug monitoring
BACKGROUND:Vancomycin pharmacokinetics are best described using a 2-compartment model. However, 1-compartment population models are commonly used as the basis for dose prediction software. Therefore, the validity of using a 1-compartment model to guide vancomycin drug dosing was examined. METHODS:Published plasma concentration-time data from adult subjects (n = 30) with stable renal function administered a single intravenous infusion of vancomycin were extracted from previous studies. The vancomycin area under the curve (AUC0-∞) was calculated for each subject using noncompartmental methods (AUCNCA) and by fitting 1- (AUC1CMT), 2- (AUC2CMT), and 3- (AUC3CMT) compartment infusion models. The optimal model fit was determined using the Akaike information criterion and visual inspection of the residual plots. The individual compartmental AUC0-∞ values from the 1- and 2-compartment models were compared with AUCNCA values using one-way repeated measures analysis of variance. RESULTS:The mean (±SD) AUC estimates were similar for the different methods: AUCNCA 180 ± 86 mg·h/L, AUC1CMT 167 ± 79 mg·h/L, and AUC2CMT 183 ± 88 mg·h/L. Despite the overlapping AUC values, AUC2CMT and AUCNCA were significantly greater than AUC1CMT (P < 0.05). The 3-compartment model was excluded from the analysis because of the failure to converge in some instances. CONCLUSIONS:Dose prediction software using a 1-compartment model as the basis for Bayesian forecasting underestimates drug exposure (estimated as the AUC) by less than 10%. This is unlikely to be clinically significant with respect to dose adjustment. Therefore, a 1-compartment model may be sufficient to guide vancomycin dosing in adult patients with stable renal function.
10.1097/FTD.0000000000000690
The dosing and monitoring of vancomycin: what is the best way forward?
Drennan Philip G,Begg Evan J,Gardiner Sharon J,Kirkpatrick Carl M J,Chambers Steve T
International journal of antimicrobial agents
We have evaluated the literature to review optimal dosing and monitoring of intravenous vancomycin in adults, in response to evolving understanding of targets associated with efficacy and toxicity. The area under the total concentration-time curve (0-24 h) divided by the minimum inhibitory concentration (AUC/MIC) is the most commonly accepted index to guide vancomycin dosing for the treatment of Staphylococcus aureus infections, with a value of 400 h a widely recommended target for efficacy. Upper limits of AUC exposure of around 700 (mg/L).h have been proposed, based on the hypothesis that higher exposures of vancomycin are associated with an unacceptable risk of nephrotoxicity. If AUC/MIC targets are used, sources of variability in the assessment of both AUC and MIC need to be considered. Current consensus guidelines recommend measuring trough vancomycin concentrations during intermittent dosing as a surrogate for the AUC. Trough concentrations are a misleading surrogate for AUC and a poor end-point in themselves. AUC estimation using log-linear pharmacokinetic methods based on two plasma concentrations, or Bayesian methods are superior. Alternatively, a single concentration measured during continuous infusion allows simple AUC estimation and dose-adjustment. All of these methods have logistical challenges which must be overcome if they are to be adopted successfully.
10.1016/j.ijantimicag.2018.12.014
Individualized dosing of vancomycin in geriatric patients.
Suchánková H,Lečbychová K,Strojil J,Fürst T
Epidemiologie, mikrobiologie, imunologie : casopis Spolecnosti pro epidemiologii a mikrobiologii Ceske lekarske spolecnosti J.E. Purkyne
AIMS:Pharmacotherapy in geriatric patients is challenging due to frequent multimorbidity, polypharmacy, increased risk of adverse drug effects, and altered pharmacokinetics and pharmacodynamics associated with aging. Therapeutic drug monitoring (TDM) is a dosing individualisation strategy that helps to minimise toxicity whilst maximising the efficacy of the agent. Routine TDM of vancomycin is recommended in clinical practice in order to optimise drug exposure. Guidelines by Rybak et al. from 2009 on vancomycin TDM promote monitoring of trough concentrations only, with higher target ranges for dosage adjustment. The aim of the study was to evaluate the practice of vancomycin TDM in geriatric (aged 65 ys) and non-geriatric patients, compare two methods of dosing adjustment (trough-based vs. AUC-based approach), and finally determine covariates enabling to choose an appropriate initial vancomycin maintenance dosing regimen in geriatric patients. Methods: A retrospective analysis of all vancomycin plasma concentrations determined during a five year period in patients treated with IV vancomycin in the University Hospital Olomouc was performed. Haemodialysis patients were excluded. Each trough value was compared with the guidelines by Rybak et al. and subsequently, pharmacokinetic modelling was performed to assess individual AUC24 values. RESULTS:A total of 1,458 vancomycin concentrations were included, which represented 799 individual monitoring events in 380 patients. Vancomycin was most commonly prescribed for sepsis (41.6% of all patients). Pathogens with MIC > 1 mg/L were responsible for 16.7% of all infections. Initial dosing led to optimum vancomycin exposure in 37.8% of patients. Vancomycin dosage based on the guidelines by Rybak et al. from 2009 would agree with the AUC-based dosing adjustments in 65% of all monitoring events. Approximately 19.1% of trough concentrations were below the minimum target suggested by the guidelines despite the fact that their corresponding AUC24/MIC ratios were high enough ( 400), and in further 6.1% of monitoring events, the trough-only approach would fail to accurately identify supratherapeutic concentrations. Initial dosing of 1 g twice daily was prescribed to 62.9% of patients, although it would be considered as optimal only in 32.1% of all patients. For 48 % of patients in the non-geriatric cohort, higher dosing (3 to 4 g daily) would be necessary to achieve optimum vancomycin exposure, whereas for 56% of geriatric patients, lower dosage regimens (up to 1.5 g daily) would be considered optimal. The estimated glomerular filtration rate was the most significant covariate in the pharmacokinetic model enabling the construction of a dosing nomogram. CONCLUSION:AUC-based vancomycin monitoring is superior to trough-based approach as the latter can lead to unnecessarily aggressive dosing in over a quarter of patients. A simple nomogram using the estimated glomerular filtration rate may increase the percentage of patients receiving an optimal initial vancomycin dose.
Prospective Trial on the Use of Trough Concentration versus Area under the Curve To Determine Therapeutic Vancomycin Dosing.
Neely Michael N,Kato Lauren,Youn Gilmer,Kraler Lironn,Bayard David,van Guilder Michael,Schumitzky Alan,Yamada Walter,Jones Brenda,Minejima Emi
Antimicrobial agents and chemotherapy
We hypothesized that dosing vancomycin to achieve trough concentrations of >15 mg/liter overdoses many adults compared to area under the concentration-time curve (AUC)-guided dosing. We conducted a 3-year, prospective study of vancomycin dosing, plasma concentrations, and outcomes. In year 1, nonstudy clinicians targeted trough concentrations of 10 to 20 mg/liter (infection dependent) and controlled dosing. In years 2 and 3, the study team controlled vancomycin dosing with BestDose Bayesian software to achieve a daily, steady-state AUC/MIC ratio of ≥400, with a maximum AUC value of 800 mg · h/liter, regardless of trough concentration. For Bayesian estimation of AUCs, we used trough samples in years 1 and 2 and optimally timed samples in year 3. We enrolled 252 adults who were ≥18 years old with ≥1 available vancomycin concentration. Only 19% of all trough concentrations were therapeutic versus 70% of AUCs ( < 0.0001). After enrollment, median trough concentrations by year were 14.4, 9.7, and 10.9 mg/liter ( = 0.005), with 36%, 7%, and 6% over 15 mg/liter ( < 0.0001). Bayesian AUC-guided dosing in years 2 and 3 was associated with fewer additional blood samples per subject (3.6, 2.0, and 2.4; = 0.003), shorter therapy durations (8.2, 5.4, and 4.7 days; = 0.03), and reduced nephrotoxicity (8%, 0%, and 2%; = 0.01). The median inpatient stay was 20 days among nephrotoxic patients versus 6 days ( = 0.002). There was no difference in efficacy by year, with 42% of patients having microbiologically proven infections. Compared to trough concentration targets, AUC-guided, Bayesian estimation-assisted vancomycin dosing was associated with decreased nephrotoxicity, reduced per-patient blood sampling, and shorter length of therapy, without compromising efficacy. These benefits have the potential for substantial cost savings. (This study has been registered at ClinicalTrials.gov under registration no. NCT01932034.).
10.1128/AAC.02042-17
[Assessment of Renal Function and Simulation Using Serum Cystatin-C in an Elderly Patient with Uncontrollable Plasma Vancomycin Levels Due to Muscular Dystrophy: A Case Report].
Onita Tetsushu,Ishihara Noriyuki,Yano Takahisa,Nishimura Nobuhiro,Tamaki Hiroki,Ikawa Kazuro,Morikawa Norifumi,Naora Kohji
Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
Herein, we describe a case of an elderly patient with muscular dystrophy for whom control of the plasma vancomycin (VCM) concentration proved difficult when he developed a catheter-related bloodstream infection. The pharmacist initially carried out therapeutic drug monitoring using an estimate of the creatinine clearance (CL) level, which was based on the serum creatinine (SCr) and serum cystatin-C (CysC) levels, but was ultimately unable to control the plasma VCM concentration. Therefore, the plasma VCM concentration was predicted ex post facto using population pharmacokinetic parameters as a covariate; that is, directly including the glomerular filtration rate (GFR) estimated from the CysC level, which is not affected by the muscle mass. As a result, the estimated VCM concentration was closer to the actual concentration than that predicted using CL. Furthermore, the results of examining the predictive accuracy according to the assessment of renal function at the time of initial VCM administration suggested that estimation of the trough concentration using GFR might be useful in elderly patients with muscular dystrophy.
10.1248/yakushi.20-00213
[Predictive performance of Smart Dose, PharmVan and JPKD on Vancomycin plasma concentration].
Han Lu,Xu Fangmin,Zhang Xiaoshan,Wang Yuzhen,Lin Guanyang,Yu Xuben
Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE:To evaluate the predictive performance of the individualized drug delivery decision-making system including Smart Dose, PharmVan and JPKD on predicting the Vancomycin plasma concentration and to analyze the related factors affecting the predictive performance. METHODS:The clinical data of patients who were treated with Vancomycin and received therapeutic drug monitoring (TDM) admitted to the First Affiliated Hospital of Wenzhou Medical University from January 2018 to July 2020 were retrospectively collected. Smart Dose and PharmVan were used to predict the plasma concentration of Vancomycin of the initial regimen. Smart Dose, PharmVan and JPKD were used to predict the plasma concentration of Vancomycin of the adjustment regimen for patients whose initial steady-state trough concentration were not qualified. The relative predictive error (PE) between the measured plasma concentration and predicted plasma concentration was calculated and box plotted. Mann-Whitney U test was used to evaluate the difference of the absolute value of PE (APE) predicted by each software for Vancomycin plasma concentration. The TDM results were divided into accurate prediction group (APE < 30%) and the inaccurate prediction group (APE ≥ 30%) according to the APE value. Patients and disease characteristics including gender, age, body weight complication, Vancomycin medication and TDM results were collected from electronic medical records. Univariate analysis and multivariate Logistic regression analysis were used to screen the related factors that influence the predictive performance of Smart Dose, PharmVan and JPKD; and receiver operating characteristic curve (ROC curve) was drawn to evaluate its predictive value. RESULTS:A total of 185 patients were enrolled, and 258 plasma concentration of Vancomycin were collected, including 185 concentrations of initial regimen and 73 concentration of adjustment regimen. There was no significant difference in the APE of the initial regimen of plasma concentration between Smart Dose and PharmVan. No significant difference in the APE of the adjustment regimen of plasma concentration was found among Smart Dose, PharmVan and JPKD. The accuracy of Smart Dose in predicting the plasma concentration of the adjustment regimen was better than that of the initial regimen [22.94% (10.50%, 36.24%) vs. 29.33% (13.07%, 47.99%), P < 0.05]. The univariate analysis of factors affecting the performance of Smart Dose in predicting the concentration of initial regimen showed that the proportion of patients with hypertension in the accurate prediction group was significantly higher than that in the inaccurate prediction group [43.3% (42/97) vs. 27.3% (24/88), P < 0.05]. The univariate analysis of factors affecting the performance of Smart Dose in predicting the concentration of adjustment regimen showed that the proportion of patients with valvular heart disease in the accurate prediction group was significantly lower than that in the inaccurate prediction group [23.4% (11/47) vs. 46.2% (12/26), P < 0.05]. The univariate analysis of factors affecting the performance of JPKD in predicting the concentration of adjustment regimen showed that the body weight of patients in the accurate prediction group was significantly higher than that in the inaccurate prediction group (kg: 62.8±14.9 vs. 54.8±12.8, P < 0.05). Multivariate Logistic regression analysis indicated that hypertension was a beneficial factor for Smart Dose to predict the initial plasma concentration of Vancomycin [odds ratio (OR) = 0.526, 95% confidence interval (95%CI) was 0.281-0.983, P = 0.044], and low body weight was an independent risk factor for the inaccurate prediction of JPKD for adjustment regimen (OR = 1.042, 95%CI was1.001-1.085, P = 0.043). ROC curve analysis indicated that the area underROC curve (AUC) of the body weight for evaluating the accuracy of JPKD in predicting Vancomycin plasma concentration was 0.663, and 95%CI was 0.529-0.796 (P = 0.023). When the body weight was less than 55.95 kg, the risk of inaccurate prediction of JPKD in predicting Vancomycin plasma concentration was increased, and the predictive sensitivityand specificity were 75% and 60% respectively. CONCLUSIONS:There is no significant difference in the predictive performance of Smart Dose, PharmVan or JPKD on Vancomycin plasma concentration. Smart Dose had a better predictive performance for the Vancomycin plasma concentration of adjustment regimen than initial regimen. Smart Dose had a better predictive performance when the patient was concomitant with hypertension. JPKD had a poor predictive performance for low-body weight patients. The predictive performance of JPKD was decreased when the body weight was lower than 55.95 kg.
10.3760/cma.j.cn121430-20201016-00674