Nature Communications (May 2023)

A randomized clinical trial assessing the effect of automated medication-targeted alerts on acute kidney injury outcomes

  • F. Perry Wilson,
  • Yu Yamamoto,
  • Melissa Martin,
  • Claudia Coronel-Moreno,
  • Fan Li,
  • Chao Cheng,
  • Abinet Aklilu,
  • Lama Ghazi,
  • Jason H. Greenberg,
  • Stephen Latham,
  • Hannah Melchinger,
  • Sherry G. Mansour,
  • Dennis G. Moledina,
  • Chirag R. Parikh,
  • Caitlin Partridge,
  • Jeffrey M. Testani,
  • Ugochukwu Ugwuowo

DOI
https://doi.org/10.1038/s41467-023-38532-3
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 10

Abstract

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Abstract Acute kidney injury is common among hospitalized individuals, particularly those exposed to certain medications, and is associated with substantial morbidity and mortality. In a pragmatic, open-label, National Institutes of Health-funded, parallel group randomized controlled trial (clinicaltrials.gov NCT02771977), we investigate whether an automated clinical decision support system affects discontinuation rates of potentially nephrotoxic medications and improves outcomes in patients with AKI. Participants included 5060 hospitalized adults with AKI and an active order for any of three classes of medications of interest: non-steroidal anti-inflammatory drugs, renin-angiotensin-aldosterone system inhibitors, or proton pump inhibitors. Within 24 hours of randomization, a medication of interest was discontinued in 61.1% of the alert group versus 55.9% of the usual care group (relative risk 1.08, 1.04 – 1.14, p = 0.0003). The primary outcome – a composite of progression of acute kidney injury, dialysis, or death within 14 days - occurred in 585 (23.1%) of individuals in the alert group and 639 (25.3%) of patients in the usual care group (RR 0.92, 0.83 – 1.01, p = 0.09). Trial Registration Clinicaltrials.gov NCT02771977.