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Year : 2020  |  Volume : 10  |  Issue : 5  |  Page : 1-5

Discordance of renal drug dosing using estimated creatinine clearance and measured urine creatinine clearance in hospitalized adults: A retrospective cohort study

Department of Pharmacy, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA

Date of Submission01-Aug-2019
Date of Acceptance14-Feb-2020
Date of Web Publication16-Sep-2020

Correspondence Address:
Dr. Anthony T Gerlach
Room 368 Doan Hall, 410 West 10th Avenue, Columbus, Ohio 43210
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/IJCIIS.IJCIIS_61_19

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Background: Assessment of kidney function is fundamental to optimize drug dosing. The Cockcroft–Gault (CG) equation is widely used but has questionable validity for females, changing renal function, and the critical ill. Eight-hour urine collections (U8h) offer direct measurement of creatinine clearance (CrCl) but lack the data for drug dosing. The primary objective of this study was to determine if there was a difference in renal drug dosing based on the estimation of CG CrCl (CrClCG) versus 8-h CrCl (CrCl8h).
Methods: This was an observational, retrospective cohort study of adult patients admitted between March 2018 and September 2018 with a collection U8hduring hospitalization. The primary outcome was discordance of renal drug dosing defined as the percentage of U8hfor which at least one different active medication CrCl dosing cutoff would result using the CrClCGversus CrCl8h. The secondary outcomes were correlation between CrClCGand CrCl8hand percentage of CrClCGvalues outside ± 20% of the CrCl8h.
Results: One hundred collections drawn from 85 unique patients (50.6% male, median age 55 [41–70] years, intensive care unit 88%) were included in the analysis. Median serum creatinine was 0.76 (0.52–1.06) mg/dL and blood urea nitrogen was 20 (14–28) mg/dL at time of collection8h. Median CrCl8hwas 86.2 (43.5–140.3) mL/min versus 99.7 (56.5–166.9) mL/min CrClCG(P < 0.001) and discordance was 25%. The correlation between CrCl8hand CrClCGwas 0.76 (P < 0.001). Only 31% of CrClCGvalues were within ± 20% of the CrCl8hvalue.
Conclusion: We found 25% discordance for drug dosing between CrCl8hand CrClCG.Further studies are needed to determine the impact on clinical outcomes.

Keywords: Augmented renal clearance, Cockcroft–Gault equation, Creatinine clearance, renal dosing, urine collection

How to cite this article:
Brown AR, Lavelle RI, Gerlach AT. Discordance of renal drug dosing using estimated creatinine clearance and measured urine creatinine clearance in hospitalized adults: A retrospective cohort study. Int J Crit Illn Inj Sci 2020;10:1-5

How to cite this URL:
Brown AR, Lavelle RI, Gerlach AT. Discordance of renal drug dosing using estimated creatinine clearance and measured urine creatinine clearance in hospitalized adults: A retrospective cohort study. Int J Crit Illn Inj Sci [serial online] 2020 [cited 2022 Dec 3];10:1-5. Available from: https://www.ijciis.org/text.asp?2020/10/5/1/295216

   Introduction Top

The assessment of kidney function is fundamental to determine the dose adjustments of renally eliminated medications to maximize efficacy and minimize adverse effects. The Cockcroft–Gault (CG) equation was developed in a study conducted at a Veterans Hospital in the 1970s to provide a simple calculation of creatinine clearance (CrCl) to estimate a patient's kidney function without the need for urine collection.[1] The CG study originally planned to use 505 urine collections, but only 249 were reproducible and arbitrarily determined to be good approximations of actual clearance. Furthermore, 96% of the study participants were male; patients with variable serum creatinine (SCr) values were excluded; and the patients were mainly located in medical wards. Therefore, the validity of the CG equation in patients who are female, have fluctuating SCr values, and/or are critically ill is unknown.[1]

The Food and Drug Administration (FDA) recommended the use of the CG equation for developing drug dosing guidelines and pharmacokinetic studies in 1998.[2] More recently, the FDA draft guidance in 2010 recommended using both the CG-estimated CrCl (CrClCG) and the Modification of Diet and Renal Disease estimation of glomerular filtration rate (eGFR) for study design in patients with impaired renal function.[3] In 2017, meropenem/vaborbactam became the first drug in the United States labeled for dosing adjustment based on eGFR.[4] Dosage adjustments based on kidney function are essential to appropriate drug therapy, but limited data assessing the various estimates of CrCl and potentially different drug dosing exist.[5],[6]

As an alternative to estimating CrCl, urine collections provide a method to directly measure CrCl.[7] Twenty-four hour urine collections have been used to assess kidney function, and the CG equation was originally validated using this method.[1] More recently, the use of the 8-h urine collection (U8h) has evolved due to faster results, decreased workload, and decreased potential for collection errors. The comparison of 8-h urine CrCl (CrCl8h) with 24-hour urine CrCl (CrCl24h) has shown a good correlation in the surgical intensive care unit (ICU), trauma, and hospitalized elderly patients.[8],[9] However, U8h has limited studies addressing the use for drug dosing in comparison with the CG equation.

At our institution, U8h is a relatively new method used to assess a patient's renal function in addition to CG estimates. The primary aim of this study was to determine if there was a difference in renal drug dosing for selected renally eliminated drugs based on the estimation of CrClCG versus CrCl8h in adult hospitalized patients.

   Methods Top


This study was a single-center, observational, retrospective cohort design.

Participants and setting

The University Medical Center is a 1506 bed academic medical center consisting of seven hospitals. Patients hospitalized between March 1, 2018, and September 30, 2018, were evaluated. Patients were included if they were 18 years of age or older and had a U8h during their hospital admission. Patients were excluded for the following: pregnancy/lactation, incarceration, renal replacement therapy within 72 h before collection, diuretic administration within 8 h before or during the collection, past medical history (PMH) of renal transplant or admission for renal transplant, presence of ileal conduit, factors that do not allow for CG calculation (SCr below lower limit of detection of 0.2 mg/dL, height < 60″, SCr not collected within 24 h of collection, height and weight not recorded), and no active orders to select renally adjusted medications [Table 1]. These medications were chosen because of common use in the settings where U8h are utilized at our institution. This study was approved by our university institutional review board in accordance with the ethical standards set forth in the Helsinki Declaration in 1975 (IRB Number 2018E0698).
Table 1: Select Renally Adjusted Medications

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Data retrospectively collected from the electronic medical records (EMR, EPIC, Madison, Wisconsin, USA) included age, sex, race, height, actual body weight, PMH of chronic kidney disease, patient location, date/time of U8h, SCr, and corresponding blood urea nitrogen (BUN) within 24 h before urine collection, urine volume, CrCl8h calculated by the EMR, and active medication orders [Table 1] on the day of urine collection. Medications were placed within CrCl cutoffs originating from our institution's adult dosing guideline using the CrCl8h compared to the CrClCG. If a medication was not included in our institution's guideline, the package insert or societal guideline was used.[10],[11],[12] The study data were collected and managed using Research Electronic Data Capture.[13]

The EMR automatically calculates the CrClCG utilizing the actual body weight (WtActual) if WtActual is less than the ideal body weight (IBW). If the WtActual is ≥ 120% of the IBW, then adjusted body weight (Wtadjusted) is used. All other situations use IBW. The SCr drawn closest to the time of urine collection within the previous 24 h was used in the CG calculation and is referred to as the reference SCr. The following equations were used for calculating CrClCG:

Male IBW(kg)=50+ (2.3 × inches over 5 feet)

Female IBW(kg) = 45.5 + (2.3 × inches over 5 feet)

The EMR also displays the calculated urine CrCl for the U8h using the following equation:


The primary outcome was the discordance rate of renal drug dosing, defined as the number of urine collections for which at least one different medication CrCl dosing breakpoint would result using the CrClCG versus CrCl8h divided by the total number of collections multiplied by 100. The secondary outcomes were the correlation of the CrClCG and CrCl8h and percentage of CrClCG values outside ± 20% of the CrCl8h. Augmented renal clearance (ARC) was defined as a CrCl8h≥ 130 mL/min.[14]

Statistical analysis

The sample size was not calculated as there was a paucity of data comparing drug dosing using CrCl8h to CrClCG. Data were reported using the descriptive statistics. Dichotomous variables were analyzed using Fisher's exact test or the Chi-squared test as appropriate. Normally distributed continuous variables were presented as mean (±standard deviation) and analyzed using the paired Student's t-test, whereas nonnormally distributed data were presented as a median (25%–75% interquartile range) and analyzed using the Mann-Whitney U test. Spearman rank correlation was used to determine the correlation between CrCl8h and CrClCG. Statistical significance was defined as a P < 0.05. Data were analyzed using the Statistical Package for the Social Sciences software version 24.0 (SPSS®), Inc. (Chicago, IL, USA).

   Results Top

A total of 150 U8h were completed between March 2018 and September 2018. Fifty collections were excluded [Figure 1], leaving 100 collections drawn from 85 unique patients, with a median age of 55 (41–70) years. A little more than half of the patients were male (50.6%), and a majority (75.3%) were Caucasian. At the time of urine collection, 88% were in an ICU, but the median SCr and BUN were 0.76 (0.52–1.06) mg/dL and 20 (14–28) mg/dL, respectively. The median CrCl8h was 86.2 (43.5–140.3) mL/min versus 99.7 (56.5–166.9) mL/min CrClCG, P < 0.001. Other patient characteristics at the time of urine collection are included in [Table 2].
Figure 1: Inclusion and exclusion of urine collections. †SCr undetectable, height <60 inches, undocumented height/weight. CG: Cockcroft–Gault

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Table 2: Patient characteristics at the time of urine collection

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The most common active medication orders at the time of urine collection were vancomycin (52), cefepime (37), piperacillin/tazobactam (33), levetiracetam (22), enoxaparin (22), and meropenem (15) [Table 3]. Seventeen percent of all medications resulted in a different drug dose which was similar for the top six most common drugs, with the exception of piperacillin/tazobactam and enoxaparin which had 3% and 0% discordances, respectively. The analysis of differing drug doses by individual medication is included in [Table 3]. The primary outcome resulted in a 25% discordance rate, meaning 25% of the urine collections would have resulted in at least one different drug dose for active medications when using CrCl8h versus CrClCG. The correlation between CrCl8h and CrClCG was 0.76 (P < 0.001), with an R2 = 0.581. Only 31% of CrClCG values were within ± 20% of the CrCl8h value. Over half (51%) of CrClCG values were >120% of CrCl8h and 18% were below 80% of CrCl8h[Figure 2].
Table 3: Active medication orders on the day of urine collection

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Figure 2: CrClCG and CrCl8h Comparison. CrCl (CG): Cockcroft–Gault creatinine clearance, CrCl (8h): Eight-hour creatinine clearance

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   Discussion Top

Our comparison of CrClCG and CrCl8h resulted in at least one discordant renal drug dose for one in every four patients who had a U8h. Previous studies comparing CrCl8h and CrClCG focused on correlation, bias, and precision or limited CrCl8h use to identify ARC.[14],[15],[16],[17] Our study is unique because we evaluated the effect on drug dosing at the time of urine collection.

It is not surprising that antibiotics were the most common class of renally eliminated medications at the time of urine collection, especially in a cohort of predominantly critical care patients. There are increasing data suggesting that dosing of antibiotics, especially beta-lactams, needs to be individualized in ICU patients.[18],[19] We found that the rates of discordance for the most commonly observed active medication orders [Table 3] were similar to the overall medication discordance, except for piperacillin/tazobactam (3%) and enoxaparin (0%). Lower discordance rates with these medications are likely related to only having a single CrCl cutoff versus a medication like cefepime with three dosing adjustments based on CrCl. Regardless, the use of U8h to calculate CrCl8h may be an appropriate surrogate for dose adjustments that would otherwise require therapeutic drug monitoring (for example, with beta-lactam antibiotics).

Differences between the CrCl8h and the CrClCG were not readily apparent based on the correlation in our study. The correlation we observed (0.76) was only slightly lower than that observed in the CG study (0.83) and still represents a fair correlation.[1] However, looking at the distribution of the data revealed that 69% of the CrClCG values fell outside ±20% of the urine CrCl values as opposed to only 33% in the original CG study.[1] A few variances in our study may explain our different results. For one, 88% of our patients were in the ICU, whereas the CG study reported their patients were “mainly on medical wards” without further elaboration.[1] Our patients were evenly balanced between male and female patients, compared to almost an entirely male population (96%) in the CG study. Recommendations for the use of the 0.85 correction factor for females in the CG equation came from an estimate of fat and muscle differences between the sexes mentioned in the discussion of the CG study, but this proposed adjustment was not evaluated.[1] The use of this correction could lead to inaccuracies in the estimation of CrCl, especially for female patients, and may lead to inadequate medication adjustments.

A number of limitations need to be considered for our study. First, the CrCl8h is not the established gold standard for estimating CrCl. Furthermore, our study was retrospective and conducted at a single center using a small study population. The decision to order U8h was not standardized and left to clinician discretion. Applying our exclusion criteria also removed 50 collections of the 150 records reviewed from the analysis. We collected apriori list of medications and did not record other active orders for renally adjusted medications. Furthermore, the CrCl8h calculation in our EMR assumes a urine collection time interval of 8 h. The nurse does not record the actual amount of time for the collections, which could lead to over or underestimation of CrCl8h. The CG study selected patients with renal function at a steady state by excluding patients with SCr values that differed by >20%. Based on our median SCr of 0.76 (0.52–1.06) and only 13% having a ≥0.3 mg/dL SCr increase in 48 h before collection, few had an acute kidney injury.[1] Furthermore, our study did not assess the clinical outcomes for our patients.

   Conclusion Top

We determined that there was 25% discordance in drug dosing between CrCl8h and CrClCG in our study population. We also determined that over two-thirds of U8h resulted in CrClCG values falling outside ± 20% of the CrCl8h. Our findings support the need for subsequent studies comparing CrClCG to CrCl8h for renal drug dosing and resulting clinical outcomes.

Research quality and ethics statement

The authors of this manuscript declare that this scientific work complies with reporting quality, formatting, and reproducibility guidelines set forth by the EQUATOR Network. The authors also attest that this clinical investigation was determined to require Institutional Ethics Committee, Research Cell, King George's Medical University, Lucknow and appropriate approval (84th ECM II-B-Thesis) was granted by the Research Cell, King George's Medical University, Lucknow.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

Ethical conduct of research

This study was approved by the Institutional Review Board / Ethics Committee. The authors followed applicable EQUATOR Network (http://www.equator-network.org/) guidelines during the conduct of this research project.

   References Top

Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron 1976;16:31-41.  Back to cited text no. 1
US Department of Health and Human Services; Food and Drug Administration. Guidance for industry: Pharmacokinetics in Patients with Impaired Renal Function – Study Design, Data Analysis, and Impact on Dosing and Labeling, May 1998. Available from: https://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM072127.pdf. [Last accessed on 2018 Sep 30].  Back to cited text no. 2
US Food and Drug Administration. Draft guidance for industry: Pharmacokinetics in Patients with Impaired Renal Function – Study Design Data Analysis, and Impact on Dosing and Labeling. https://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM204959.pdf. [Last accessed on 2018 Sep 30].  Back to cited text no. 3
Vabomere [Package Insert]. Teramo, Italy: Facta Farmaceutici: Melinta Therapeutics, Inc.; 2017.  Back to cited text no. 4
Awdishu L, Connor AI, Bouchard J, Macedo E, Chertow GM, Mehta RL. Use of estimating equations for dosing antimicrobials in patients with acute kidney injury not receiving renal replacement therapy. J Clin Med 2018;7. pii: E211.  Back to cited text no. 5
Hudson JQ, Bean JR, Burger CF, Stephens AK, McFarland MS. Estimated glomerular filtration rate leads to higher drug dose recommendations in the elderly compared with creatinine clearance. Int J Clin Pract 2015;69:313-20.  Back to cited text no. 6
Markantonis SL, Agathokleous-Kioupaki E. Can two-, four- or eight-hour urine collections after voluntary voiding be used instead of twenty-four-hour collections for the estimation of creatinine clearance in healthy subjects? Pharm World Sci 1998;20:258-63.  Back to cited text no. 7
Cherry RA, Eachempati SR, Hydo L, Barie PS. Accuracy of short-duration creatinine clearance determinations in predicting 24-hour creatinine clearance in critically ill and injured patients. J Trauma 2002;53:267-71.  Back to cited text no. 8
O'Connell MB, Wong MO, Bannick-Mohrland SD, Dwinell AM. Accuracy of 2- and 8-hour urine collections for measuring creatinine clearance in the hospitalized elderly. Pharmacotherapy 1993;13:135-42.  Back to cited text no. 9
Keppra Injection (Levetiracetam) [Prescribing Information]. Smyrna, GA: UCB Inc.; 2017.  Back to cited text no. 10
Vimpat (Lacosamide) [Prescribing Information]. Smyrna, GA: UCB Inc.; 2018.  Back to cited text no. 11
January CT, Wann LS, Alpert JS, Calkins H, Cigarroa JE, Cleveland JC Jr., et al. 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: Executive summary: A report of the American College of Cardiology/American Heart Association Task Force on practice guidelines and the Heart Rhythm Society. Circulation 2014;130:2071-104.  Back to cited text no. 12
Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap) – A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009;42:377-81.  Back to cited text no. 13
Declercq P, Gijsen M, Meijers B, Schetz M, Nijs S, D'Hoore A, et al. Reliability of serum creatinine-based formulae estimating renal function in non-critically ill surgery patients: Focus on augmented renal clearance. J Clin Pharm Ther 2018;43:695-706.  Back to cited text no. 14
Baptista JP, Neves M, Rodrigues L, Teixeira L, Pinho J, Pimentel J. Accuracy of the estimation of glomerular filtration rate within a population of critically ill patients. J Nephrol 2014;27:403-10.  Back to cited text no. 15
Udy AA, Varghese JM, Altukroni M, Briscoe S, McWhinney BC, Ungerer JP, et al. Subtherapeutic initial β-lactam concentrations in select critically ill patients: Association between augmented renal clearance and low trough drug concentrations. Chest 2012;142:30-9.  Back to cited text no. 16
Udy AA, Dulhunty JM, Roberts JA, Davis JS, Webb SAR, Bellomo R, et al. Association between augmented renal clearance and clinical outcomes in patients receiving β-lactam antibiotic therapy by continuous or intermittent infusion: A nested cohort study of the BLING-II randomised, placebo-controlled, clinical trial. Int J Antimicrob Agents 2017;49:624-30.  Back to cited text no. 17
De Waele JJ, Lipman J, Akova M, Bassetti M, Dimopoulos G, Kaukonen M, et al. Risk factors for target non-attainment during empirical treatment with β-lactam antibiotics in critically ill patients. Intensive Care Med 2014;40:1340-51.  Back to cited text no. 18
Zander J, Döbbeler G, Nagel D, Maier B, Scharf C, Huseyn-Zada M, et al. Piperacillin concentration in relation to therapeutic range in critically ill patients – A prospective observational study. Crit Care 2016;20:79.  Back to cited text no. 19


  [Figure 1], [Figure 2]

  [Table 1], [Table 2], [Table 3]

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