Dynamic nomogram for predicting acute kidney injury in patients with acute ischemic stroke: A retrospective study

Abstract

BackgroundThis study sought to develop and validate a dynamic nomogram chart to assess the risk of acute kidney injury (AKI) in patients with acute ischemic stroke (AIS).MethodsThese data were drawn from the Medical Information Mart for Intensive Care III (MIMIC-III) database, which collects 47 clinical indicators of patients after admission to the hospital. The primary outcome indicator was the occurrence of AKI within 48 h of intensive care unit (ICU) admission. Independent risk factors for AKI were screened from the training set using univariate and multifactorial logistic regression analyses. Multiple logistic regression models were developed, and nomograms were plotted and validated in an internal validation set. Based on the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) to estimate the performance of this nomogram.ResultsNomogram indicators include blood urea nitrogen (BUN), creatinine, red blood cell distribution width (RDW), heart rate (HR), Oxford Acute Severity of Illness Score (OASIS), the history of congestive heart failure (CHF), the use of vancomycin, contrast agent, and mannitol. The predictive model displayed well discrimination with the area under the ROC curve values of 0.8529 and 0.8598 for the training set and the validator, respectively. Calibration curves revealed favorable concordance between the actual and predicted incidence of AKI (p > 0.05). DCA indicates the excellent net clinical benefit of nomogram in predicting AKI.ConclusionIn summary, we explored the incidence of AKI in patients with AIS during ICU stay and developed a predictive model to help clinical decision-making.

A novel risk model based on white blood cell-related biomarkers for acute kidney injury prediction in patients with ischemic stroke admitted to the intensive care unit

“…Previous studies reported the different risk models to predict AKI in patients with IS. Zhu et al developed a nomogram that includes blood urea nitrogen (BUN), creatinine, red blood cell distribution width (RDW), heart rate (HR), Oxford Acute Severity of Illness Score (OASIS), the history of congestive heart failure (CHF), the use of vancomycin, contrast agent, and mannitol and found that nomogram showed good predictive ability ( 34 ). For ICU patients, the SIRS, OASIS, APS III, SAPS II, and CCI scores are fundamental individualized risk assessments for characterizing disease severity and degree of organ dysfunction.…”

Development of a nomogram to predict the incidence of acute kidney injury among ischemic stroke individuals during ICU hospitalization

“…Prior studies have endeavored to construct a nomogram for AKI incidence in ischemic stroke patients using the Medical Information Mart for Intensive Care (MIMIC) III database [ 10 ]. Regrettably, this model relies on the Oxford Acute Severity of Illness Score (OASIS), which introduces clinical intricacy and restricts its broader applicability.…”

“…Regrettably, this model relies on the Oxford Acute Severity of Illness Score (OASIS), which introduces clinical intricacy and restricts its broader applicability. Moreover, the existing model solely forecast AKI within 48 h of ICU admission, lacking the ability to accurately predict AKI throughout the entire ICU stay [ 10 ]. Therefore, it is imperative to devise a simplified nomogram based on readily accessible clinical features, enabling prompt and effective assessment of the risk of AKI incidence during the ICU hospitalization of individuals with ischemic stroke.…”