ArticleBJS open2026
Predicting postoperative acute kidney injury after colorectal cancer surgery: development and internal validation of a clinical prediction model using a nationwide cohort.
Article in BJS open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundPostoperative acute kidney injury (PO-AKI) occurs in 8-20% of patients undergoing colorectal cancer surgery and is associated with increased mortality and morbidity. A prediction model can help in the identification of high-risk patients and guide clinicians in implementing preventive measures. The present study aimed to develop and validate internally a clinical prediction model for the risk of PO-AKI within 7 days after an elective resection of colorectal cancer, using predictors known before surgery.
methodsUsing a nationwide clinical quality database, all patients with stage I-IV colorectal cancer undergoing an elective colorectal resection from 2015 to 2021 in Denmark were identified. Patient characteristics, comorbidities, medications, and laboratory values were obtained through linkage across national health registries. The outcome was PO-AKI within 7 days after surgery, defined according to the Kidney Disease Improving Global Outcomes criteria. A logistic regression model was fitted using preoperative predictors, backward selection was applied to derive the final model, and internal validation was performed through two-fold bootstrapping. The performance was assessed using discrimination and calibration measures.
resultsAmong 26 104 identified patients, 20 277 patients were included, and 1747 (8.6%) developed AKI within 7 days. Fifty-four per cent were men, and the median age was 71 years (interquartile range, 64-78 years). The final model included 14 preoperative predictors. The model showed moderate discriminative performance with an optimism-corrected c-statistic of 0.70 (95% confidence interval 0.68 to 0.71) and was well calibrated at PO-AKI risks between 0% and 20% but somewhat overestimated higher risks (overall slope 0.95; intercept -0.001). The prediction model is available as a calculator at https://po-aki.streamlit.app.
conclusionThe model predicted PO-AKI with moderate accuracy and may support the implementation of preventive measures. However, external validation is required to confirm its applicability.
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