Acute kidney injury is a well-known complication of acute pancreatitis. It occurs in almost 70% of cases of severe acute pancreatitis .The development of acute kidney injury in patients with severe acute pancreatitis significantly increases the risk of hospital mortality [3, 19, 20] and carries a very poor prognosis[21, 22]. In recent years, blood purification treatment plays a significant role in the comprehensive treatment of acute pancreatitis[23, 24]. It has been reported that early hemofiltration could improve the treatment efficacy and decrease mortality rate in patients with pancreatitis complicated by acute renal failure[25, 26]. Therefore, early identification of acute kidney injury in the course of acute pancreatitis would be of great value in helping clinicians triage patients to the appropriate level of care and guide clinical practice in the management of acute pancreatitis.
A nomogram is accepted as a reliable tool to predict risk by illustrating important predictors for clinical events. To our knowledge, there are still no studies on the prediction of acute kidney injury in acute pancreatitis at present. We therefore conducted this study to develop and validate a nomogram for the prediction of acute kidney injury associated with acute pancreatitis, which can visually score individual risk and allow early identification of patients at high risk.
As is shown in our study, the overall prevalence of acute kidney injury is 15.5%, in which the incidence of the training set is 16.3%, and the incidence of the validation set is 13.6%, in line with the literature reports [27, 28]. This nomogram includes five readily available indices, including BMI, RANSON score, serum uric acid, triglycerides and lactate. The proposed model achieved sufficient accuracy and good clinical usefulness.
The mechanisms underlying acute kidney injury complicating acute pancreatitis have not been completely understood,but appears to result from initial hypovolemia followed by complex interactions between inflammatory, vascular, and humoral factors. Many studies have identified that obesity is associated with an increased risk of kidney failure, local complications and mortality in patients with acute pancreatitis. The body mass index (BMI) is a measure of obesity and a higher BMI was independently associated with increased risks of acute kidney injury. Hyperlipidemia, especially high circulating concentrations of triglycerides, can lead to the development of severe and systemic complications in patients with acute pancreatitis[31, 32]. Hyperuricemia is linked to metabolic syndrome and has been shown to predict kidney disease onset and progression[34, 35]. A recent study has shown that an elevated lactate level is closely related to persistent organ failure in acute pancreatitis. Over the past few decades, several multi-factorial scoring systems based on clinical and biochemical data have been used for assessing the severity of acute pancreatitis[37, 38]. These include Ranson’s score, BISAP, CTSI and APACHE II to name a few. In agreement with these observations, which are based on extensive clinical data, this nomogram incorporated five factors as predictors of acute kidney injury: BMI, RANSON score, serum uric acid, triglycerides and lactate.
To develop a simple but efficient predictive model, we utilized the LASSO method to data dimension reduction and screen the optimized predictors. This method surpasses the methods using the strength of univariate differences with outcome and enhance the accuracy and interpretability of the predictive model [17, 40]. Validation of the nomogram is important to avoid overfitting and to determine generalizability. In this study, the AUROC in the training and validation cohorts demonstrated adequate discrimination power (0.994 and 0.996, respectively). Calibration curve showed optimal agreement between predicted and actual observations, which suggested that the nomogram was quite predictive. Decision curve analysis was performed to determine the clinical usefulness and demonstrated that, if the threshold probability is between 1% and 99%, using the nomogram for prediction of acute kidney injury added more benefit than treating either all or no patients. The clinical value of the nomogram is to make a comprehensive evaluation of risk and provides insights into personalized decision-making, especially for high-risk population.
Our analysis has a few advantages. First, the nomogram is practical because all the variables included are easily and routinely collected in clinical practice and it may take less time to calculate individual risk score. Second, the data was collected on a relatively large population of acute pancreatitis cohort and candidate risk factors included were very comprehensive, which improves the application value of the prediction model. In addition, the discrimination and calibration validation of the model ensured our model of strong evidence to predict the acute kidney injury in acute pancreatitis. Decision curve analysis demonstrated our prediction model have good clinical usefulness.
As the first study of this kind, there is no similar model for reference, the current study also has several limitations. Firstly, as a retrospective study, we cannot avoid potential biases. Secondly, this study was conducted in a single center, with a relatively small sample size and only internal validation, the results may not be widely generalizable in other regions and races. In the next step, we will focus on conducting a prospective multi-center research for enrolling much larger sample cases. Finally, we didn’t include novel biomarkers reported in recent studies because they are not yet widely used clinically. The proposed nomogram may be further optimized after incorporating more valuable variables such as serum uromodulin, neutrophil gelatinase-associated lipocalin (NGAL).