Development of a Multivariable Prediction Model for Citrate Accumulation in Liver Transplant Patients Undergoing Continuous Renal Replacement Therapy with Regional Citrate Anticoagulation

Abstract

<b><i>Introduction:</i></b> Patients with impaired citrate metabolism may experience citrate accumulation (CA), which causes life-threatening metabolic acidosis and hypocalcemia. CA poses a challenge for clinicians when deciding on the use of regional citrate anticoagulation (RCA) for patients with liver dysfunction. This study aimed to develop a prediction model integrating multiple clinical variables to assess the risk of CA in liver transplant patients. <b><i>Methods:</i></b> This single-center prospective cohort study included postoperative liver transplant patients who underwent continuous renal replacement therapy (CRRT) with RCA. The study end point was CA. A prediction model was developed using a generalized linear mixed-effect model based on the Akaike information criterion. The predictive values were assessed using the receiver operating characteristic curve and bootstrap resampling (times = 500) to estimate the area under the curve (AUC) and the corresponding 95% confidence interval (CI). A nomogram was used to visualize the model. <b><i>Results:</i></b> This study included 32 patients who underwent 133 CRRT sessions with RCA. CA occurred in 46 CRRT sessions. The model included lactate, norepinephrine >0.1 μg/kg/min, alanine aminotransferase, total bilirubin, and standard bicarbonate, which were tested before starting each CRRT session and body mass index, diabetes mellitus, and chronic kidney disease as predictors. The AUC of the model was 0.867 (95% CI 0.786–0.921), which was significantly higher than that of the single predictor (<i>p</i> < 0.05). A nomogram visualized the prediction model. <b><i>Conclusions:</i></b> The prediction model integrating multiple clinical variables showed a good predictive value for CA. A nomogram visualized the model for easy application in clinical practice.

Construction and validation of a prediction model for the risk of citrate accumulation in patients with hepatic insufficiency receiving continuous renal replacement therapy with citrate anticoagulation

“…In our study, female patients were more likely to develop citrate accumulation, possible because women have less muscle, which affects citrate metabolism [ 28 , 29 ]. Similar to previous studies, a norepinephrine dosage ≥0.1 μg/kg/min, which represents hemodynamic instability and inadequate tissue perfusion [ 30 ], was an independent risk factor for citrate accumulation in our study. Oxygen is a key factor in the tricarboxylic acid cycle, and a state of hypoxia can lead to a decrease in citrate metabolism when the efficiency of the tricarboxylic acid cycle decreases, which ultimately causes citrate accumulation [ 31 ].…”

“…Few studies have provided simple and convenient prediction models for citrate accumulation, and most recent studies have been focused on the analysis of safety and risk factors for citrate accumulation in hepatic failure patients treated with citrate anticoagulation. X. Xin et al constructed a model for predicting the risk of accumulation in liver transplant patients receiving citrate anticoagulation [ 30 ], the results of which might be biased and lack external validation, making the model less generalized, especially because only 32 patients were included. We developed a new prediction model based on variables that can be obtained quickly in routine clinical examinations and the outcome of which can be easily calculated at the bedside through electronic medical records, which would significantly improve the application of the prediction model in clinical practice.…”