AI-Enhanced Medication Management for Acute Kidney Injury in Critical Care Settings
DOI:
https://doi.org/10.65327/kidneys.v15i1.611Keywords:
Acute kidney injury, Artificial intelligence, Medication safety, Renal dose adjustment, Intensive care unitAbstract
Background: Acute kidney injury (AKI) is a frequent complication in critically ill patients and is often exacerbated by inappropriate medication dosing and exposure to nephrotoxic drugs. Rapid renal function changes and high medication burden in the intensive care unit (ICU) make renal-safe prescribing challenging. Artificial intelligence (AI)-assisted clinical decision support systems may aid medication optimisation during AKI.
Objective: To evaluate the association between AI-assisted medication review and renal dose appropriateness in critically ill patients with AKI, and to assess AKI progression and renal recovery during ICU admission.
Methods: A single-centre observational study was conducted in an adult ICU. Adult patients diagnosed with AKI using the Kidney Disease: Improving Global Outcomes (KDIGO) criteria and receiving at least one medication were included. Renal function was monitored using serum creatinine and urine output. Medications were assessed for renal dose appropriateness. An AI-assisted decision support tool provided dosing and nephrotoxicity recommendations without autonomous prescribing during routine clinical care settings.
Results: Patients had a mean age of 63 ± 12 years and received multiple medications during AKI. Renal dose appropriateness improved from 66% to 85% following AI-assisted review. Renal function improved in 44% of patients, while 23% experienced worsening AKI.
Conclusions: AI-assisted medication review was associated with improved renal-safe prescribing in critically ill patients with AKI, supporting its role as a clinician-centred adjunct in intensive care.
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References
Rea Chela SM, Morales Quilligana SF, Morales Olivera JA, Castaño Alarcón R, Cruz Celi VD. Advances in AI-based combination therapies versus standard treatments for heart failure in patients with advanced kidney injury. Sapienza Int J Interdiscip Stud. 2024;5(3):e24062. doi:10.51798/sijis.v5i3.789.
Patel JP, Kshatriya DR, HN R, Rane J, Jayasrikrupaa R. Artificial intelligence-driven pharmacotherapy optimization in chronic kidney disease: bridging clinical pharmacology and urology. Kidneys. 2025;14(4):337-345. doi:10.65327/kidneys.v14i4.569.
Nerella S, Guan Z, Siegel S, Zhang J, Zhu R, Khezeli K, et al. AI-enhanced intensive care unit: revolutionizing patient care with pervasive sensing. arXiv. 2023. doi:10.48550/arXiv.2303.06252.
Papareddy P, Lobo TJ, Holub M, Bouma H, Maca J, Strodthoff N, et al. Transforming sepsis management: AI-driven innovations in early detection and tailored therapies. Crit Care. 2025;29(1):366. doi:10.1186/s13054-025-05588-0.
Reddy VS, Stout DM, Fletcher R, Barksdale A, Parikshak M, Johns C, et al. Advanced artificial intelligence-guided hemodynamic management within cardiac enhanced recovery after surgery pathways: a multi-institution review. JTCVS Open. 2023;16:480-489. doi:10.1016/j.xjon.2023.06.023.
Charan GS, Charan AS, Khurana MS, Narang GS. Impact of analytics applying artificial intelligence and machine learning on enhancing intensive care unit: a narrative review. Galician Med J. 2023;30(4). doi:10.21802/e-GMJ2023-A06.
Yuan S, Guo L, Xu F. Artificial intelligence in nephrology: predicting chronic kidney disease progression and personalizing treatment. Int Urol Nephrol. 2025. doi:10.1007/s11255-025-04878-4.
Yusop N, Mat S, Mustafar R, Ismail MI. Fuzzy logic nursing tool for early acute kidney injury detection in surgical patients. Front Nephrol. 2025;5:1624880. doi:10.3389/fneph.2025.1624880.
Hammouda N, Neyra JA. Can artificial intelligence assist in delivering continuous renal replacement therapy? Adv Chronic Kidney Dis. 2022;29(5):439-449. doi:10.1053/j.ackd.2022.08.001.
Addissouky TA. From omics to artificial intelligence: revolutionizing sepsis-induced acute respiratory distress syndrome management. Avicenna J Clin Microbiol Infect. 2025;12(4):204-219. doi:10.34172/ajcmi.3663.
Nishida N. Advancements in artificial intelligence-enhanced imaging diagnostics for the management of liver disease: applications and challenges in personalized care. Bioengineering. 2024;11(12):1243. doi:10.3390/bioengineering11121243.
Siniscalchi C, Bernardi FF, Perrella A, Di Micco P. Remote monitoring model based on artificial intelligence to optimize direct oral anticoagulant therapy: a working hypothesis for safer anticoagulation. Medicina (Kaunas). 2025;61(11):1982. doi:10.3390/medicina61111982.
Aarav Kannan J, Rajalakshmi R. Improving diagnosis of kidney-related type 2 diabetes patients using AI-enhanced image processing with deep learning and NeuroX algorithmic frameworks. In: Proc 8th Int Conf Circuit Power Comput Technol (ICCPCT); 2025. p. 1722-1727. doi:10.1109/ICCPCT65132.2025.11176537.
Fahim YA, Hasani IW, Kabba S, Ragab WM. Artificial intelligence in healthcare and medicine: clinical applications, therapeutic advances, and future perspectives. Eur J Med Res. 2025;30(1):848. doi:10.1186/s40001-025-03196-w.
Alobaidi S. Emerging biomarkers and advanced diagnostics in chronic kidney disease: early detection through multi-omics and artificial intelligence. Diagnostics (Basel). 2025;15(10):1225. doi:10.3390/diagnostics15101225.
Yun G, Yi J, Han S, Seong J, Menadjiev E, Han H, et al. Validation of an acute kidney injury prediction model as a clinical decision support system. Kidney Res Clin Pract. 2025. doi:10.23876/j.krcp.24.163.
Giri R, Firdhos SH, Vida TA. Artificial intelligence in anaesthesia: enhancing precision, safety, and global access through data-driven systems. J Clin Med. 2025;14(19):6900. doi:10.3390/jcm14196900.
Schwantes IR, Axelrod DA. Technology-enabled care and artificial intelligence in kidney transplantation. Curr Transplant Rep. 2021;8:235-240. doi:10.1007/s40472-021-00336-z.
Pinto A, Pennisi F, Odelli S, De Ponti E, Veronese N, Signorelli C, et al. Artificial intelligence in the management of infectious diseases in older adults: diagnostic, prognostic, and therapeutic applications. Biomedicines. 2025;13(10):2525. doi:10.3390/biomedicines13102525.
Nimmagadda N, Aboian E, Kiang S, Fischer U. The role of artificial intelligence in vascular care. JVS Vasc Insights. 2025;3:100179. doi:10.1016/j.jvsvi.2024.100179.
Suresh V, Singh KK, Vaish E, Gurjar M, Am A, Khulbe Y, et al. Artificial intelligence in the intensive care unit: current evidence on an inevitable future tool. Cureus. 2024. doi:10.7759/cureus.59797.
Rice WM, Morris RS, Haines KL. Improving acute care surgery with artificial intelligence: a practical review. Clin Colon Rectal Surg. 2025. doi:10.1055/a-2769-0955.
ISSN 2307-1257
ISSN 2307-1265
