Lung transplantation (LTx) has become a critical treatment for end-stage lung disease, achieving remarkable progress in recent years. However, postoperative complications continue to significantly affect patient outcomes. Among these, acute kidney injury (AKI) is a frequent and clinically significant complication. In some cases, AKI progresses to severe renal failure requiring continuous renal replacement therapy (CRRT), which markedly increases mortality risk and the healthcare burden.
In critically ill patients and those undergoing solid organ transplantation, the indications and optimal timing for CRRT remain controversial. Clinical decisions often rely on experience rather than objective criteria, and reliable quantitative tools are lacking. Early identification of patients at high risk for CRRT following LTx is therefore a key unmet need.
A study was conducted by a team of researchers led by Dr. Man Huang from The Second Affiliated Hospital of Zhejiang University School of Medicine, China, and Zhejiang University, Ministry of Education, China, to address this clinical gap in early risk stratification for CRRT following LTx. Their findings were published online in the Journal of Intensive Medicine on March 11, 2026. This study analyzed data from a single-center retrospective cohort of 448 lung transplant recipients, focusing on those who developed AKI. Potential predictive factors were first screened using least absolute shrinkage and selection operator (LASSO) regression to reduce overfitting in high-dimensional data, followed by multivariable logistic regression to construct a CRRT risk prediction model. The model was visualized as a nomogram, and its discrimination, calibration, and clinical utility were evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).
Results showed that 23.2% of AKI patients required CRRT. Independent predictors included older age, increased intraoperative blood loss, intraoperative positive fluid balance, bilateral LTx, prolonged postoperative extracorporeal membrane oxygenation (ECMO) support, delayed serum creatinine (sCr) peak, accelerated sCr rise rate, and greater sCr elevation. Preoperative mechanical ventilation was identified as a protective factor. The resulting model demonstrated excellent discrimination in both training and validation cohorts (area under the ROC curve (AUC) = 0.972 and 0.882, respectively) and showed good calibration, highlighting its reliability.
Compared with other surgeries or solid organ transplants, lung transplant recipients present unique perioperative physiological characteristics, including routine ECMO support, heightened inflammatory responses, and differences between single- and double-LTx. These factors collectively influence the onset and progression of renal dysfunction. The model integrates these lung transplant-specific indicators with early postoperative sCr dynamics, allowing for precise estimation of CRRT risk.
“ The innovation of this study lies in its first-ever development and validation of a CRRT prediction model for AKI following lung transplantation, combining preoperative, intraoperative, and early postoperative dynamic indicators for early identification of high-risk patients ,” says Dr. Huang. “ Compared with conventional experience-based decisions, the nomogram is easy to use, visually intuitive, and provides a quantitative risk assessment prior to CRRT initiation .”
Clinically, this tool can guide individualized early interventions, such as optimizing fluid management, adjusting hemodynamic status, minimizing nephrotoxic drug exposure, and arranging early nephrology consultation. By supporting timely intervention, the model has the potential to delay renal deterioration, reduce CRRT demand, and improve patient outcomes.
“ In summary, this study provides a valuable risk assessment tool for managing AKI after lung transplantation, promoting precise, proactive clinical decision-making and improving the care of these complex patients ,” concludes Dr. Huang.
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Reference
DOI: https://doi.org/10.1016/j.jointm.2026.01.007
Journal of Intensive Medicine
Data/statistical analysis
People
Risk prediction of continuous renal replacement therapy in patients with acute kidney injury after lung transplantation
11-Mar-2026
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.