Observational studyBMC anesthesiology2022
Development and validation of a risk nomogram for postoperative acute kidney injury in older patients undergoing liver resection: a pilot study.
Observational study in BMC anesthesiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04922866 (Predictive Nomogram for Postoperative Acute Kidney Injury), which is not on this map. Cited by 4 papers.
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The trial behind it
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Predictive Nomogram for Postoperative Acute Kidney Injury (AKI) in Elderly Patients Following Liver Resection
Who cites it
4 citing papers in PubMed, 10 citations in OpenAlex.
- Article
- Perioperative Myocardial Injury and Acute Kidney Injury in Patients Undergoing Hepatic Resection: Incidence, Risk Factors, and Effects on Outcomes.Journal of clinical medicine · 2025Article
- Comparison between ketorolac- and fentanyl-based patient-controlled analgesia for acute kidney injury after robot-assisted radical prostatectomy: a retrospective propensity score-matched analysis.World journal of urology · 2023Article
- Construction and Validation of a Nomogram for Predicting Acute Kidney Injury After Hip Fracture Surgery.Clinical interventions in aging · 2023Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPostoperative acute kidney injury (AKI) is associated with poor clinical outcomes. Early identification of high-risk patients of developing postoperative AKI can optimize perioperative renal management and facilitate patient survival. The present study aims to develop and validate a nomogram to predict postoperative AKI after liver resection in older patients.
methodsA retrospective observational study was conducted involving data from 843 older patients scheduled for liver resection at a single tertiary high caseload general hospital between 2012 and 2019. The data were randomly divided into training (70%, n = 599) and validation (30%, n = 244) datasets. The training cohort was used to construct a predictive nomogram for postoperative AKI with the logistic regression model which was confirmed by a validation cohort. The model was evaluated by receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis in the validation cohort. A summary risk score was also constructed for identifying postoperative AKI patients.
resultsPostoperative AKI occurred in 155 (18.4%) patients and was highly associated with in-hospital mortality (5.2% vs. 0.7%, P < 0.001). The six predictors selected and assembled into the nomogram included age, preexisting chronic kidney disease (CKD), non-steroidal anti-inflammatory drugs (NSAIDs) usage, intraoperative hepatic inflow occlusion, blood loss, and transfusion. The predictive nomogram performed well in terms of discrimination with area under ROC curve (AUC) in training (0.73, 95% confidence interval (CI): 0.68-0.78) and validation (0.71, 95% CI: 0.63-0.80) datasets. The nomogram was well-calibrated with the Hosmer-Lemeshow chi-square value of 9.68 (P = 0.47). Decision curve analysis demonstrated a significant clinical benefit. The summary risk score calculated as the sum of points from the six variables (one point for each variable) performed as well as the nomogram in identifying the risk of AKI (AUC 0.71, 95% CI: 0.66-0.76).
conclusionThis nomogram and summary risk score accurately predicted postoperative AKI using six clinically accessible variables, with potential application in facilitating the optimized perioperative renal management in older patients undergoing liver resection.
trial registrationNCT04922866 , retrospectively registered on clinicaltrials.gov on June 11, 2021.
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