Development of a nomogram for the prediction of acute kidney injury after liver transplantation: a model based on clinical parameters and postoperative cystatin C level

Abstract

Background

Acute kidney injury (AKI) is common after liver transplantation (LT). We developed a nomogram model to predict post-LT AKI.

Methods

A total of 120 patients were eligible for inclusion in the study. Clinical information was extracted from the institutional electronic medical record system. Blood samples were collected prior to surgery and immediately after surgery. Univariable and multivariate logistic regression were used to identify independent risk factors. Finally, a nomogram was developed based on the final multivariable logistic regression model.

Results

In total, 58 (48.3%) patients developed AKI. Multivariable logistic regression revealed four independent risk factors for post-LT AKI: operation duration [odds ratio (OR) = 1.728, 95% confidence interval (CI) = 1.121–2.663, p = 0.013], intraoperative hypotension (OR = 3.235, 95% CI = 1.316–7.952, p = 0.011), postoperative cystatin C level (OR = 1.002, 95% CI = 1.001–1.004, p = 0.005) and shock (OR = 4.002, 95% CI = 0.893–17.945, p = 0.070). Receiver operating characteristic curve analysis was used to evaluate model discrimination. The area under the curve value was 0.815 (95% CI = 0.737–0.894).

Conclusion

The model based on combinations of clinical parameters and postoperative cystatin C levels had a higher predictive performance for post-LT AKI than the model based on clinical parameters or postoperative cystatin C level alone. Additionally, we developed an easy-to-use nomogram based on the final model, which could aid in the early detection of AKI and improve the prognosis of patients after LT.

KEY MESSAGES

• Acute kidney injury (AKI) is one of the most common and important complications after liver transplantation (LT).

• We developed a nomogram model to predict post-LT AKI based on clinical parameters and postoperative cystatin C level.

• The model based on combinations of clinical parameters and postoperative cystatin C levels had a higher predictive performance, which could aid in the early detection of AKI and improve the prognosis of patients after LT.

Keywords:

• Acute kidney injury
• liver transplantation
• nomogram
• prediction model
• clinical parameters
• postoperative cystatin C level

Acknowledgement

The authors would like to thank Beijing Youan Hospital for allowing us to access the computerized health records.

Ethical approval

All authors approved the publication of this manuscript.

Author contributions

Study design: YM, GL, XW, ZW and YW; Data collection: LH, BJ and QY; Blood specimens collected: QY, YW and XW; ELISA experiments: ZW and YW; Data analysis: ZW and YW and Manuscript writing: ZW, YW and XW. All authors read and approved the final manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Additional information

Funding

This work was supported by Scientific Research Project of Beijing Youan Hospital [Grant No. BJYAYY-YN2022-22, CCMU, 2022], Beijing Natural Science Foundation [Grant No. 7232079] and key medical professional development plan of Beijing Hospital Authority [Grant No. ZYLX202124] and Beijing Natural Science Foundation [Grant No. 7222096].