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Multicenter Study
. 2025 Sep;34(9):e70205.
doi: 10.1002/pds.70205.

Vancomycin-Induced Acute Kidney Injury in Intensive Care Patients: A Target Trial Emulation Study Using Multicenter Routinely Collected Data

Izak A R Yasrebi-de Kom  1   2 , Kitty J Jager  1   2 , Vianda S Stel  1   2 , Nicholas C Chesnaye  2   3 , Ameen Abu-Hanna  1   2 , Nicolette F de Keizer  1   2 , Dylan W de Lange  4 , Dave A Dongelmans  2   5 , Joanna E Klopotowska  1   2 , Giovanni Cinà  1   2   6 ; RESCUE Study Group
Collaborators, Affiliations
Multicenter Study

Vancomycin-Induced Acute Kidney Injury in Intensive Care Patients: A Target Trial Emulation Study Using Multicenter Routinely Collected Data

Izak A R Yasrebi-de Kom et al. Pharmacoepidemiol Drug Saf. 2025 Sep.

Abstract

Purpose: The potential of vancomycin to cause acute kidney injury (AKI) in adult intensive care patients is subject to debate due to suboptimal designs of past studies. Therefore, we aimed to estimate the effect of initiating vancomycin versus one of several minimally nephrotoxic alternative antibiotics on the 14-day risk of AKI using the target trial emulation framework.

Methods: A hypothetical trial was emulated using routinely collected data from 15 Dutch intensive care units (ICUs) spanning 2010-2019. We used an active comparator control group with the following alternative antibiotics: clindamycin, linezolid, teicoplanin, meropenem, cefazolin, and daptomycin. AKI was diagnosed according to the KDIGO serum creatinine (SCr) criteria. Cumulative incidence curves were estimated using the Aalen-Johansen method and adjusted for confounding and selection bias through inverse probability of treatment and censoring weighting. Given the time lag of 24-48 h between changes in renal function and SCr, we summarized the estimates by calculating the absolute risks and risk differences at both 2 and 14 days after initiation.

Results: We included 1809 ICU admissions. After adjustment, vancomycin was associated with a higher risk of AKI at 14 days of follow-up compared to the alternative antibiotics (0.28 [95% confidence interval (CI) 0.21-0.34] vs. 0.17 [95% CI 0.14-0.20]; risk difference 0.11 [95% CI 0.04-0.19]), but not at 2 days of follow-up (0.10 [95% CI 0.06-0.12] vs. 0.10 [95% CI 0.08-0.11]; risk difference 0.00 [95% CI -0.03-0.03]).

Conclusions: Our findings indicate that vancomycin causes a higher risk of AKI compared to the alternative antibiotics. We recommend clinicians to be compliant with vancomycin-induced AKI prevention strategies, such as therapeutic drug monitoring or the consideration of an alternative antibiotic if possible.

Keywords: acute kidney injury; adverse drug event; intensive care; target trial emulation; vancomycin.

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Conflict of interest statement

For the duration of this research, Giovanni Cinà has held a partial appointment at the company Pacmed, as well as stock appreciation options. The other authors declare no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Graphical depiction of the study design. The gray line represents time zero. Areas with diagonal blue lines represent periods with varying durations across ICU admissions, as time zero could have started anywhere between 24 h and 7 days post ICU admission, whilst the preceding exposure washout window and exclusion assessment window ended at 24 h after admission to the ICU.
FIGURE 2
FIGURE 2
Description of the number of included ICU admissions after application of the eligibility and exclusion criteria.
FIGURE 3
FIGURE 3
Adjusted (IPTW and IPCW) cumulative incidence curves with pointwise 95% CIs, stratified by treatment.
See this image and copyright information in PMC

References

    1. Karimzadeh I., Barreto E. F., Kellum J. A., et al., “Moving Toward a Contemporary Classification of Drug‐Induced Kidney Disease,” Critical Care 27, no. 1 (2023): 435, 10.1186/s13054-023-04720-2. - DOI - PMC - PubMed
    1. Ronco C., Bellomo R., and Kellum J. A., “Acute Kidney Injury,” Lancet 394, no. 10212 (2019): 1949–1964, 10.1016/S0140-6736(19)32563-2. - DOI - PubMed
    1. Mehta R. L., Awdishu L., Davenport A., et al., “Phenotype Standardization for Drug‐Induced Kidney Disease,” Kidney International 88, no. 2 (2015): 226–234, 10.1038/ki.2015.115. - DOI - PMC - PubMed
    1. Awdishu L., “Drug‐Induced Kidney Disease in the ICU: Mechanisms, Susceptibility, Diagnosis and Management Strategies,” Current Opinion in Critical Care 23, no. 6 (2017): 484–490, 10.1097/MCC.0000000000000453. - DOI - PubMed
    1. Ostermann M., Bellomo R., Burdmann E. A., et al., “Controversies in Acute Kidney Injury: Conclusions From a Kidney Disease: Improving Global Outcomes (KDIGO) Conference,” Kidney International 98, no. 2 (2020): 294–309, 10.1016/j.kint.2020.04.020. - DOI - PMC - PubMed

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