A retrospective observational study on the discordance rate of antibiotic dosing among critically ill patients: Considerations for using KDIGO guideline

Worapong Sungsana Chotirat Nakaranurack Weerachai Chaijamorn Nattachai Srisawat   

Open Access   

Published:  Oct 15, 2025

DOI: 10.7324/JAPS.2026.259994
Abstract

Optimizing antibiotic dosing in critically ill patients is challenging. This study evaluated the discordance rate of antibiotic dosing between the Cockcroft-gault (CG) and chronic kidney disease-epidemiology collaboration (CKD-EPI) estimated glomerular filtration rate (eGFR) equations in medical intensive care units (MICUs) patients. We also assessed the concordance analysis of estimated kidney function and stage of dosing for each antibiotic agent between equations. A retrospective study was conducted on patients in MICUs who received commonly used antibiotic agents between August 2020 and July 2023. The agreement was assessed using a weighted kappa statistic. A total of 171 patients with 266 cystatin C sampling points were included. The mean age and median sarcopenia index were 67.23 years and 0.45, respectively. The CKD-EPI eGFRcys 2012 equation showed the highest discordance in antibiotic dosing. Discordance rate of antibiotic dosing based on CG and CKD-EPI eGFR based on creatinine ranged from 10% to 30%. Compared with cystatin C-based equations, Piperacillin/tazobactam had the highest negative discordance rates, while ertapenem had the lowest. The acute kidney injury group exhibited a reduced correlation and an increased discordance rate of antibiotic agents between creatinine-based and cystatin C-based equations. Various equations for estimating renal clearance from the Kidney Disease: Improving Global Outcomes guideline result in different antibiotic dosages. Further research is required for appropriate dose adjustment.


Keyword:     Antibiotic creatinine critically ill cystatin C drug dosage


Citation:

Sungsana W, Nakaranurack C, Chaijamorn W, Srisawat N. A retrospective observational study on the discordance rate of antibiotic dosing among critically ill patients: Considerations for using KDIGO guideline. J Appl Pharm Sci. 2025. Article in Press. http://doi.org/10.7324/JAPS.2026.259994

Copyright: © The Author(s). This is an open-access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

HTML Full Text

Reference

1. Cotta MO, Roberts JA, Lipman J.Antibiotic dose optimization in critically ill patients. Med Intens. 2015;39(9):563–72. doi: https://doi.org/10.1016/j.medin.2015.07.009

2. Li XX, Zheng SQ, Gu JH, Huang T, Liu F, Ge QG, et al. Drug-related problems identified during pharmacy intervention and consultation: implementation of an intensive care unit pharmaceutical care model. Front Pharmacol. 2020;11:571906. doi: https://doi.org/10.3389/fphar.2020.571906

3. Inker LA, Titan S. Measurement and estimation of GFR for use in clinical practice: core curriculum 2021. Am J Kidney Dis. 2021;78(5):736–49. doi: https://doi.org/10.1053/j.ajkd.2021.04.016

4. FDA. Label: MERREM IV (meropenem for injection): United States Food and Drug Administration (US. FDA); 2016 [updated 12/2016]. Available from: https://www.accessdata.fda.gov/drugsatfda_docs/label/2016/050706s037lbl.pdf

5. FDA/CDER. Vancomycin hydrochloride for injection: United States Food and Drug Administration (US. FDA) and The Center for Drug Evaluation and Research (CDER); 2018 [updated 7/2018]. Available from: https://www.accessdata.fda.gov/drugsatfda_docs/label/2018/209481s000lbl.pdf

6. FDA. Coly-Mycin M parenteral (Colistimethate for Injection, USP): United States Food and Drug Administration (US. FDA); 2017. Available from: https://www.accessdata.fda.gov/drugsatfda_docs/label/2017/050108s033lbl.pdf

7. St. Peter WL, Bzowyckyj AS, Anderson-Haag T, Awdishu L, Blackman M, Bland A, et al. Moving forward from Cockcroft-Gault creatinine clearance to race-free estimated glomerular filtration rate to improve medication-related decision-making in adults across healthcare settings: a consensus of the National Kidney Foundation Workgroup for implementation of race-free eGFR-based medication-related decisions. Am J Health Syst Pharm. 2025;82(12):644–59. doi: https://doi.org/10.1093/ajhp/zxae317

8. Kidney disease: improving global outcomes (KDIGO) CKD work group. KDIGO 2024 Clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int. 2024;105(4S):S117–314. doi: https://doi.org/10.1016/j.kint.2023.10.018

9. Awdishu L, Maxson R, Gratt C, Rubenzik T, Battistella M. KDIGO 2024 clinical practice guideline on evaluation and management of chronic kidney disease: a primer on what pharmacists need to know. Am J Health Syst Pharm. 2025;82(12):660–71. doi: https://doi.org/10.1093/ajhp/zxaf044

10. Center for Drug Evaluation and Research. Pharmacokinetics in patients with impaired renal function — study design, data analysis, and impact on dosing: United States Food and Drug Administration (US. FDA); 2024 [Clinical – Pharmacology]. Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/pharmacokinetics-patients-impaired-renal-function-study-design-data-analysis-and-impact-dosing

11. Carlier M, Dumoulin A, Janssen A, Picavet S, Vanthuyne S, Van Eynde R, et al. Comparison of different equations to assess glomerular filtration in critically ill patients. Intensive Care Med. 2015;41(3):427–35. doi: https://doi.org/10.1007/s00134-014-3641-9

12. Inker LA, Eneanya ND, Coresh J, Tighiouart H, Wang D, Sang Y, et al. New creatinine- and cystatin C–based equations to estimate GFR without race. N Engl J Med. 2021;385(19):1737–49. doi: https://doi.org/10.1056/NEJMoa2102953

13. Eiamcharoenying J, Kulvichit W, Lumlertgul N, Chaiwatanarat T, Peerapornratana S, Srisawat N. The role of serum cystatin C in estimation of renal function in survivors of critical illness. J Crit Care. 2020;59:201–6. doi: https://doi.org/10.1016/j.jcrc.2020.07.005

14. Jodlowski TZ, Sym D, Marziliano A, LaPan-Dennis G, Ashby CR, Jr., Ruhe JJ.A survey of pharmacists in academia on the current practice of estimation of kidney function for antimicrobial dosing in adults. J Pharm Pract. 2016;29(4):382–5. doi: https://doi.org/10.1177/0897190014566310

15. Khwaja A. KDIGO clinical practice guidelines for acute kidney injury. Nephron Clin Pract. 2012;120(4):c179–84. doi: https://doi.org/10.1159/000339789

16. Peters BJ, Rule AD, Kashani KB, Lieske JC, Mara KC, Dierkhising RA, et al. Impact of serum cystatin C-based glomerular filtration rate estimates on drug dose selection in hospitalized patients. Pharmacotherapy. 2018;38(10):1068–73. doi: https://doi.org/10.1002/phar.2175

17. Williams VL, Gerlach AT. Establishing discordance rate of estimated glomerular filtration rate between serum creatinine-based calculations and cystatin-C-based calculations in critically ill patients. Pharmacotherapy. 2025;45(3):161–8. doi: https://doi.org/10.1002/phar.70000

18. Khader NA, Kamath VG, Kamath SU, Rao IR, Prabhu AR. Kidney function estimation equations: a narrative review. Ir J Med Sci. 2025;194(2):725–43. doi: https://doi.org/10.1007/s11845-025- 03874-y

19. Wang Y, Adingwupu OM, Shlipak MG, Doria A, Estrella MM, Froissart M, et al. Discordance Between creatinine-based and cystatin C-based estimated GFR: interpretation according to performance compared to measured GFR. Kidney Med. 2023;5(10):100710. doi: https://doi.org/10.1016/j.xkme.2023.100710

20. Hanna PE, Wang Q, Strohbehn IA, Moreno D, Harden D, Ouyang T, et al. Medication-related adverse events and discordancies in cystatin C-based vs serum creatinine-based estimated glomerular filtration rate in patients with cancer. JAMA Netw Open. 2023;6(7):e2321715. doi: https://doi.org/10.1001/jamanetworkopen.2023.21715

21. Rybak MJ, Le J, Lodise TP, Levine DP, Bradley JS, Liu C, et al. Therapeutic monitoring of vancomycin for serious methicillin-resistant Staphylococcus aureus infections: a revised consensus guideline and review by the American Society of Health-System Pharmacists, the Infectious Diseases Society of America, the Pediatric Infectious Diseases Society, and the Society of Infectious Diseases Pharmacists. Am J Health Syst Pharm. 2020;77(11):835– 64. doi: https://doi.org/10.1093/ajhp/zxaa036

22. Jaruratanasirikul S, Nitchot W, Wongpoowarak W, Samaeng M, Nawakitrangsan M. Population pharmacokinetics and Monte Carlo simulations of sulbactam to optimize dosage regimens in patients with ventilator-associated pneumonia caused by Acinetobacter baumannii. Eur J Pharm Sci. 2019;136:104940. doi: https://doi.org/10.1016/j.ejps.2019.05.018

23. Kanchanasurakit S, Santimaleeworagun W, McPherson CE, Piriyachananusorn N, Boonsong B, Katwilat P, et al. Fosfomycin dosing regimens based on Monte Carlo simulation for treated carbapenem-resistant enterobacteriaceae infection. Infect Chemother. 2020;52(4):516–29. doi: https://doi.org/10.3947/ic.2020.52.4.516 24.

24. Saelim W, Changpradub D, Thunyaharn S, Juntanawiwat P, Nulsopapon P, Santimaleeworagun W. Colistin plus sulbactam or fosfomycin against carbapenem-resistant Acinetobacter baumannii: improved efficacy or decreased risk of nephrotoxicity? Infect Chemother. 2021;53(1):128–40. doi: https://doi.org/10.3947/ic.2021.0007

25. Santimaleeworagun W, Leelasupasri S, Sitaruno S. Optimization of fosfomycin doses for treating pseudomonas aeruginosa infection in critically Ill patients by using Monte Carlo simulation. Thai J Pharm Prac. 2019;11(4):869–78.

26. Asuphon O, Montakantikul P, Houngsaitong J, Kiratisin P, Sonthisombat P. Optimizing intravenous fosfomycin dosing in combination with carbapenems for treatment of Pseudomonas aeruginosa infections in critically ill patients based on pharmacokinetic/pharmacodynamic (PK/PD) simulation. Int J Infect Dis. 2016;50:23–9. doi: https://doi.org/10.1016/j.ijid.2016.06.017

27. Leelawattanachai P, Wattanavijitkul T, Paiboonvong T, Plongla R, Chatsuwan T, Usayaporn S, et al. Evaluation of intravenous fosfomycin disodium dosing regimens in critically ill patients for treatment of carbapenem-resistant enterobacterales infections using Monte Carlo simulation. Antibiotics (Basel). 2020;9(9):615. doi: https://doi.org/10.3390/antibiotics9090615.

28. Tlemsani C, Durand JP, Raynard B, Revel MP, Deluche E, Di Palma M, et al. Relationship between the creatinine/cystatin C ratio and muscle mass measured by CT-scan in cancer patients. Clin Nutr ESPEN. 2022;51:412–8. doi: https://doi.org/10.1016/j.clnesp.2022.07.010

29. Sungsana W, Nakaranurack C. The difference of antibiotic dosing based on serum creatinine versus cystatin C in critically ill patients. The 22nd Asian Conference on Clinical Pharmacy; July 13th - 15th, 2023; Haiphong City, Vietnam 2023.

30. Bujang MA, Baharum N. Guidelines of the minimum sample size requirements for Cohen’s Kappa. Epidemiol Biostat Public Health. 2017;14:e12267–1. doi: https://doi.org/10.2427/12267

31. Altman DG. Practical statistics for medical research: Chapman and Hall/CRC; 1990.

32. Akoglu H. User’s guide to correlation coefficients. Turk J Emerg Med. 2018;18(3):91–3. doi: https://doi.org/10.1016/j.tjem.2018.08.001

33. Knight EL, Verhave JC, Spiegelman D, Hillege HL, de Zeeuw D, Curhan GC, et al. Factors influencing serum cystatin C levels other than renal function and the impact on renal function measurement. Kidney Int. 2004;65(4):1416–21. doi: https://doi.org/10.1111/j.1523- 1755.2004.00517.x

34. Teaford HR, Barreto JN, Vollmer KJ, Rule AD, Barreto EF. Cystatin C: a primer for pharmacists. Pharmacy (Basel). 2020;8(1):35. doi: https://doi.org/10.3390/pharmacy8010035.

35. Spencer S, Desborough R, Bhandari S. Should cystatin C eGFR become routine clinical practice? Biomolecules. 2023;13(7):1075. doi: https://doi.org/10.3390/biom13071075.

36. Levey AS, Coresh J, Tighiouart H, Greene T, Inker LA. Measured and estimated glomerular filtration rate: current status and future directions. Nat Rev Nephrol. 2020;16(1):51–64. doi: https://doi.org/10.1038/s41581-019-0191-y

37. Dahlén E, Björkhem-Bergman L. Comparison of creatinine and cystatin C to estimate renal function in geriatric and frail patients. Life (Basel). 2022;12(6):846. doi: https://doi.org/10.3390/life12060846.

38. Golik MV, Lawrence KR. Comparison of dosing recommendations for antimicrobial drugs based on two methods for assessing kidney function: Cockcroft-Gault and modification of diet in renal disease. Pharmacotherapy. 2008;28(9):1125–32. doi: https://doi.org/https://doi.org/10.1592/phco.28.9.1125

39. Kim M-C, Kim SO, Kim S-H, Shin J-h, Choi S-H, Chung J-W, et al. Efficacy and safety of cystatin C-guided renal dose adjustment of cefepime treatment in hospitalized patients with pneumonia. J Clin Med. 2020;9(9):2803. doi: https://doi.org/10.3390/jcm9092803

40. Frazee E, Rule AD, Lieske JC, Kashani KB, Barreto JN, Virk A, et al. Cystatin C-guided vancomycin dosing in critically ill patients: a quality improvement project. Am J Kidney Dis. 2017;69(5):658–66. doi: https://doi.org/10.1053/j.ajkd.2016.11.016

41. Hermsen ED, Maiefski M, Florescu MC, Qiu F, Rupp ME. Comparison of the modification of diet in renal disease and Cockcroft- Gault equations for dosing antimicrobials. Pharmacotherapy. 2009;29(6):649–55. doi: https://doi.org/10.1592/phco.29.6.649

42. Moranville MP, Jennings HR. Implications of using modification of diet in renal disease versus Cockcroft-Gault equations for renal dosing adjustments. Am J Health Syst Pharm. 2009;66(2):154–61. doi: https://doi.org/10.2146/ajhp0800

43. Stevens LA, Nolin TD, Richardson MM, Feldman HI, Lewis JB, Rodby R, et al. Comparison of drug dosing recommendations based on measured GFR and kidney function estimating equations. Am J Kidney Dis. 2009;54(1):33–42. doi: https://doi.org/10.1053/j.ajkd.2009.03.008

Article Metrics
8 Views 1 Downloads 9 Total

Year

Month

Related Search

By author names