Chen Guan1, Chenyu Li1, Lingyu Xu1, Li Zhen1, Yue Zhang1, Long Zhao1, Bin Zhou1, Lin Che1, Yanfei Wang1, Yan Xu2. 1. Department of Nephrology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, 266003, China. 2. Department of Nephrology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, 266003, China. xuyanqyfy@126.com.
Abstract
OBJECTIVE: Cardiac surgery-associated acute kidney injury (CSA-AKI), one of the most severe complications in patients with cardiac surgery, is associated with considerable morbidity, mortality and high costs thus placing a heavy burden to society. Therefore, we aimed to build a predictive model based on preoperative features in order to early recognize and intervene for patients with high risk of CSA-AKI. METHODS: In this retrospective cohort study, baseline perioperative hospitalization information of patients who underwent cardiac surgery from October 2012 to October 2017 were screened. After multivariate logistic regression, identified independent predictive factors associated with CSA-AKI were incorporated into the nomogram and the discriminative ability and predictive accuracy of the model was assessed by concordance index (C-Index). Additionally, internal validation was performed by using bootstrapping technology with 1000 resamples to reduce the over-fit bias. RESULTS: In all 4395 patients with cardiac surgery October 2012-October 2017, no patients were excluded for the continuous renal replacement therapy (CRRT) before surgery while 2495 patients were excluded due to only one or less than one Scr assay post-surgery. In the end, a total of 1900 patients were enrolled in the study, of which 698 patients (74.89%) developed AKI stage 1, 158 (16.96%) AKI stage 2 and 76 (8.15%) AKI stage 3. After multivariate logistic regression, age, perioperative estimated glomerular filtration rate (eGFR), lactate dehydrogenase (LDH), prothrombin time (PT), with a history of surgery, transfusion, cardiac arrhythmia, coronary heart disease (CHD), or chronic kidney disease (CKD), using calcium channel blocker (CCB), proton pump inhibitors (PPI), non-steroidal anti-inflammatory drugs (NSAID), antibiotic or statin before surgery were predictive factors of CSA-AKI. In addition, the nomogram demonstrated a good accuracy in estimating CSA-AKI, with an C-Index and a bootstrap-corrected one of 0.796 (SD = 0.018, 95% CI 0.795-0.797) and 0.789 (SD = 0.015, 95% CI 0.788-0.790), respectively. Moreover, calibration plots showed an optimal consistency with the actual presence of CSA-AKI. CONCLUSION: The novel predictive nomogram achieved a good preoperative prediction of CSA-AKI within the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Though the model, the risk of an individual patient with "subclinical AKI" undergoing cardiac surgery could be determined earlier and such application was helpful for timely intervention in order to improve patient's prognosis.
OBJECTIVE: Cardiac surgery-associated acute kidney injury (CSA-AKI), one of the most severe complications in patients with cardiac surgery, is associated with considerable morbidity, mortality and high costs thus placing a heavy burden to society. Therefore, we aimed to build a predictive model based on preoperative features in order to early recognize and intervene for patients with high risk of CSA-AKI. METHODS: In this retrospective cohort study, baseline perioperative hospitalization information of patients who underwent cardiac surgery from October 2012 to October 2017 were screened. After multivariate logistic regression, identified independent predictive factors associated with CSA-AKI were incorporated into the nomogram and the discriminative ability and predictive accuracy of the model was assessed by concordance index (C-Index). Additionally, internal validation was performed by using bootstrapping technology with 1000 resamples to reduce the over-fit bias. RESULTS: In all 4395 patients with cardiac surgery October 2012-October 2017, no patients were excluded for the continuous renal replacement therapy (CRRT) before surgery while 2495 patients were excluded due to only one or less than one Scr assay post-surgery. In the end, a total of 1900 patients were enrolled in the study, of which 698 patients (74.89%) developed AKI stage 1, 158 (16.96%) AKI stage 2 and 76 (8.15%) AKI stage 3. After multivariate logistic regression, age, perioperative estimated glomerular filtration rate (eGFR), lactate dehydrogenase (LDH), prothrombin time (PT), with a history of surgery, transfusion, cardiac arrhythmia, coronary heart disease (CHD), or chronic kidney disease (CKD), using calcium channel blocker (CCB), proton pump inhibitors (PPI), non-steroidal anti-inflammatory drugs (NSAID), antibiotic or statin before surgery were predictive factors of CSA-AKI. In addition, the nomogram demonstrated a good accuracy in estimating CSA-AKI, with an C-Index and a bootstrap-corrected one of 0.796 (SD = 0.018, 95% CI 0.795-0.797) and 0.789 (SD = 0.015, 95% CI 0.788-0.790), respectively. Moreover, calibration plots showed an optimal consistency with the actual presence of CSA-AKI. CONCLUSION: The novel predictive nomogram achieved a good preoperative prediction of CSA-AKI within the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Though the model, the risk of an individual patient with "subclinical AKI" undergoing cardiac surgery could be determined earlier and such application was helpful for timely intervention in order to improve patient's prognosis.
Entities:
Keywords:
Cardiac surgery-associated acute kidney injury; Nomogram; Predictive model