The Impact of Different Renal Function Measuring Methods on the Dosages of Meropenem, Piperacillin/Tazobactam and Cefepime in Critically Ill Patients

Río, E. Diego del; Muner, Dolors Soy; Santanach, L. Gratacós; Sala, Josep Ribas

doi:10.1016/s2173-5085(08)70041-8

Cited by 2 publications

(2 citation statements)

References 23 publications

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“…Previous studies have shown that CG and MDRD perform better with varied scenarios [29][30][31][32]. However, the study on meropenem found no difference between CG and MDRD [33].…”

Section: Discussionmentioning

confidence: 81%

Variables Impacting GFR Estimation Method for Drug Dosing in Ckd: Artificial Neural Network Prediction Model

AlJASMI

Khan

Sulaiman

et al. 2019

Int J Pharm Pharm Sci

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Objective: This study aimed to measure concordance between different renal function estimates in terms of drug doses and determine the potential significant clinical differences.Methods: Around one hundred and eighty patients (≥ 1 8 y) with chronic kidney disease (CKD) were eligible for inclusion in this study. A pairedproportion cohort design was utilized using an artificial intelligence model. CKD patients refined into those who have drugs adjusted for renal function. For superiority of Cockcroft-Gault (CG) vs. modified diet in renal disease (MDRD) guided with references for concordance or discordance of the two equations and determined the dosing tiers of each drug. Validated artificial neural networks (ANN) was one outcome of interest. Variable impacts and performed reassignments were compared to evaluate the factors that affect the accuracy in estimating the kidney function for a better drug dosing. Results:The best ANN model classified most cases to CG as the best dosing method (79 vs. 72). The probability was 85% and the top performance was slightly above 93%. Creatinine levels and CKD staging were the most important factors in determining the best dosing method of CG versus MDRD. Ideal and actual body weights were second (24%). Whereas drug class or the specific drug was an important third factor (14%).Conclusion: Among many variables that affect the optimal dosing method, the top three are probably CKD staging, weight, and the drug. The contrasting CKD stages from the different methods can be used to recognize patterns, identify and predict the best dosing tactics in CKD patients.

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“…Previous studies have shown that CG and MDRD perform better with varied scenarios [29][30][31][32]. However, the study on meropenem found no difference between CG and MDRD [33].…”

Section: Discussionmentioning

confidence: 81%

Variables Impacting GFR Estimation Method for Drug Dosing in Ckd: Artificial Neural Network Prediction Model

AlJASMI

Khan

Sulaiman

et al. 2019

Int J Pharm Pharm Sci

View full text Add to dashboard Cite

show abstract

“…[44][45][46][47] However, the one on meropenem found no difference between CG and MDRD. 48 It screened samples from 61 patients which are a very modest size. Our simulations showed that for an outcome such as mortality, having a sufficient number of cases may help elucidate the actual difference between these methods in dosing medications.…”

Section: Discussionmentioning

confidence: 99%

Concordance Among Methods for Empiric Renal Drug Dosing: Meropenem as a Role Model for Clinical Superiority of Cockroft–Gault or Modification of Diet in Renal Disease

Jasmi

Khan

Saadah

et al. 2018

Clinical Medicine Insights: Therapeutics

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The objectives of this study are, first, to measure concordance between 5 different renal function estimates (methods) in terms of recommended drug doses, and, subsequently, to establish the potential for significant clinical differences between Cockroft-Gault (CG) and Modification of Diet in Renal Disease (MDRD) equations in dosing a specific medication, namely, meropenem. DESiGn AnD SETTinG: This study used a Monte Carlo simulation, and this is a computer-based study with no actual patient data. PATiEnTS: A total of 1200 and 8701 simulated cases to study the concordance for the 5 methods and the potential clinical significance of discordance between CG and MDRD, respectively, were chosen for the study. METhODS: Simulated factors were age, sex, height, weight, serum creatinine, ethnicity, and albumin. We estimated the renal function using 5 formulas (ie, 10 combinations) including CG, MDRD, and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI). Next, the team evaluated concordance for each combination in dosing 22 drugs. Finally, our researchers reviewed and simulated data from the literature to show how CG versus MDRD use can result in clinically significant differences for meropenem. RESulTS: Pairwise combinations yielded statistically significant differences (P < .0001) except for CG and MDRD (P < .5147). In addition, the highest concordance was for MDRD and CKD-EPI. Average discordance is in the range of 25% to 30% with the lowest being between CG and albumin-based estimates. Both CG and MDRD were largely discordant which can reach up to 40% with a drug like meropenem and may be associated with significant adverse outcomes. COnCluSiOnS: Both CG and MDRD in our simulation are statistically comparable. Clinically, nonetheless, they are significantly inconsistent in terms of recommended drug dosing. We encourage practical comparisons of outcomes for individual or groups of medications (eg, meropenem and antibiotics) empirically dosed in renal patients on the basis of equations used in distinct populations.

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The Impact of Different Renal Function Measuring Methods on the Dosages of Meropenem, Piperacillin/Tazobactam and Cefepime in Critically Ill Patients

Cited by 2 publications

References 23 publications

Variables Impacting GFR Estimation Method for Drug Dosing in Ckd: Artificial Neural Network Prediction Model

Variables Impacting GFR Estimation Method for Drug Dosing in Ckd: Artificial Neural Network Prediction Model

Concordance Among Methods for Empiric Renal Drug Dosing: Meropenem as a Role Model for Clinical Superiority of Cockroft–Gault or Modification of Diet in Renal Disease

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