ArticleEuropean journal of medical research2025
Individualized drug therapy and survival prediction in ICU patients with acute kidney injury: construction and validation of a nomogram.
Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Ergosterol alleviates lipopolysaccharide-induced acute kidney injury in rats via a mechanistic modulation of TLR4/p-p38/NF-κB, iNOS/NO and Nrf2/HO-1 signaling pathways.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
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7 authors.
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Abstract
backgroundAcute kidney injury (AKI) is defined by a sharp decrease in the estimated glomerular filtration rate (eGFR). However, the impact of medication history on the survival of AKI patients has received little attention. Hence, it is necessary to investigate the potential of medication history as a predictor of survival outcomes among AKI patients in the intensive care unit (ICU).
methodsCritically ill AKI patients were sourced from the MIMIC-IV database. To ascertain significant, drug-related, independent predictors of survival, univariate Cox analysis and stepwise Cox regression were performed. Based on the identified predictor, a nomogram was developed to estimate the individualized survival probability for AKI patients. Additionally, to address potential confounders among patients with medications referenced in the nomogram, a propensity score matching procedure was applied. Ultimately, a comparative analysis was performed to elucidate the prognostic disparities among these patient subgroups.
resultsThis study enrolled 1,208 patients and developed a nomogram incorporating oxygen flow rate, respiratory frequency, continuous venovenous hemodiafiltration status, age, and medication use (including ibuprofen, epinephrine, cefazolin, warfarin, and vasopressin). The predictive model demonstrated diagnostic accuracy, with AUC values for 1-year, 3-year, and 5-year survival among AKI patients of 0.827, 0.799, and 0.777 in the training dataset, and 0.760, 0.743, and 0.740 in the internal validation dataset, respectively. Kaplan-Meier survival analyses revealed significant differences in survival outcomes among AKI patients based on their exposure to different medications.
conclusionsIn summary, the developed prediction model demonstrated accuracy for AKI patients in the ICU and helped clinical decision-making. However, future studies will require external validation to confirm these findings.
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