Abstract
Background
Acute kidney injury is a serious complication of moderately severe and severe acute pancreatitis, which significantly increases mortality. There are currently no reliable tools for early identification of AKI especially severe AKI in these patients. We aim to develop a predictive model so that physicians can assess the risk of AKI and severe AKI, thus take further preventive measures.
Methods
Patients with a diagnosis of MSAP and SAP admitted to our hospital from January 2018 to December 2021 were retrospectively included in the study. The participants were divided into the training and validation cohorts randomly, in a 2:1 ratio. A clinical signature was built based on reproducible features, using the least absolute shrinkage and selection operator method and machine learning. Multivariate logistic regression analysis was used to develop the prediction model. Nomogram performance was determined by its discrimination, calibration, and clinical usefulness.
Results
A total of 996 eligible patients were enrolled. 698 patients were allocated in the training cohort and 298 in the validation cohort. AKI occurred in 148 patients (21%) in the training cohort and 54 (18%) in the validation cohort, respectively. The clinical features, including C-reactive protein, intra-abdominal pressure and serum cysC, were significantly associated with AKI as well as severe AKI. The nomogram showed favorable discrimination, calibration and clinical usefulness.
Conclusions
The novel risk score model has good performance for predicting AKI and severe AKI in MSAP and SAP patients. Application of this model can help clinicians stratify patients for primary prevention, surveillance and early therapeutic intervention to improve care and prognosis.
Similar content being viewed by others
References
Kryvoruchko IA, Kopchak VM, Usenko O, Honcharova NM, Balaka SM, Teslenko SM, et al. Classification of an acute pancreatitis: revision by international consensus in 2012 of classification, adopted in Atlanta. Klin Khir. 2014;9:19–24.
Lankisch PG, Apte M, Banks PA. Acute pancreatitis. Lancet. 2015;386(9988):85–96. https://doi.org/10.1016/S0140-6736(14)60649-8.
Zhou J, Li Y, Tang Y, Liu F, Yu S, Zhang L, et al. Effect of acute kidney injury on mortality and hospital stay in patient with severe acute pancreatitis. Nephrology. 2015;20(7):485–91. https://doi.org/10.1111/nep.12439.
Chai X, Huang HB, Feng G. Baseline Serum Cystatin C Is a Potential Predictor for Acute Kidney Injury in Patients with Acute Pancreatitis. Dis Mark. 2018;2018:8431219. https://doi.org/10.1155/2018/8431219.
Xu JM, Yang HD, Tian XP. Effects of early hemofiltration on organ function and intra-abdominal pressure in severe acute pancreatitis patients with abdominal compartment syndrome. Clin Nephrol. 2019;92(5):243–9. https://doi.org/10.5414/cn109435.
Xu JM, Yang HD, Tian XP. Effects of early hemofiltration on organ function and intra-abdominal pressure in severe acute pancreatitis patients with abdominal compartment syndrome. Clin Nephrol. 2019;92(5):243–9. https://doi.org/10.5414/CN109435.
Wajda J, Dumnicka P, Maraj M, Ceranowicz P, Kuzniewski M, Kusnierz-Cabala B. Potential Prognostic Markers of Acute Kidney Injury in the Early Phase of Acute Pancreatitis. Int J Mol Sci. 2019. https://doi.org/10.3390/ijms20153714.
Dominguez-Olmedo JL, Gragera-Martinez A, Mata J, Pachon AV. Machine Learning Applied to Clinical Laboratory Data in Spain for COVID-19 Outcome Prediction: Model Development and Validation. J Med Internet Res. 2021;23(4):e26211. https://doi.org/10.2196/26211.
Luo XQ, Yan P, Zhang NY, Luo B, Wang M, Deng YH, et al. Machine learning for early discrimination between transient and persistent acute kidney injury in critically ill patients with sepsis. Sci Rep. 2021;11(1):20269. https://doi.org/10.1038/s41598-021-99840-6.
Khwaja A. KDIGO clinical practice guidelines for acute kidney injury. Nephron Clin Pract. 2012;120(4):c179–84. https://doi.org/10.1159/000339789.
Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JG, Coats AJ, et al. ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur J Heart Fail. 2016;18(8):891–975. https://doi.org/10.1002/ejhf.592.
Ranson JH, Pasternack BS. Statistical methods for quantifying the severity of clinical acute pancreatitis. J Surg Res. 1977;22(2):79–91.
Ueda T, Takeyama Y, Yasuda T, Kamei K, Satoi S, Sawa H, et al. Utility of the new Japanese severity score and indications for special therapies in acute pancreatitis. J Gastroenterol. 2009;44(5):453–9. https://doi.org/10.1007/s00535-009-0026-x.
Balthazar EJ, Ranson JH, Naidich DP, Megibow AJ, Caccavale R, Cooper MM. Acute pancreatitis: prognostic value of CT. Radiology. 1985;156(3):767–72. https://doi.org/10.1148/radiology.156.3.4023241.
Wu BU, Johannes RS, Sun X, Tabak Y, Conwell DL, Banks PA. The early prediction of mortality in acute pancreatitis: a large population-based study. Gut. 2008;57(12):1698–703. https://doi.org/10.1136/gut.2008.152702.
Sauerbrei W, Royston P, Binder H. Selection of important variables and determination of functional form for continuous predictors in multivariable model building. Stat Med. 2007;26(30):5512–28. https://doi.org/10.1002/sim.3148.
Ladd AM, Conwell D, Burroughs TE, Satish M. Prior Exposure to Nonsteroidal Anti-inflammatory Drugs Reduces the Rate of Organ Failure and In-Hospital Mortality in Acute Pancreatitis. Am J Med. 2021. https://doi.org/10.1016/j.amjmed.2021.10.020.
Nassar TI, Qunibi WY. AKI Associated with Acute Pancreatitis. Clin J of the American Society of Nephrology : CJASN. 2019;14(7):1106–15. https://doi.org/10.2215/CJN.13191118.
Han D, Xu F, Li C, Zhang L, Yang R, Zheng S, et al. A Novel Nomogram for Predicting Survival in Patients with Severe Acute Pancreatitis: An Analysis Based on the Large MIMIC-III Clinical Database. Emerg Med Int. 2021;2021:9190908. https://doi.org/10.1155/2021/9190908.
Sidey-Gibbons JAM, Sidey-Gibbons CJ. Machine learning in medicine: a practical introduction. BMC Med Res Methodol. 2019;19(1):64. https://doi.org/10.1186/s12874-019-0681-4.
Wang T, Liu LY, Luo H, Dai RW, Liang HY, Chen T, et al. Intra-Abdominal Pressure Reduction After Percutaneous Catheter Drainage Is a Protective Factor for Severe Pancreatitis Patients With Sterile Fluid Collections. Pancreas. 2016;45(1):127–33. https://doi.org/10.1097/mpa.0000000000000420.
Ruan Q, Lu H, Zhu H, Guo Y, Bai Y. A network-regulative pattern in the pathogenesis of kidney injury following severe acute pancreatitis. Biomed Pharmacother = Biomed Pharmacother. 2020. https://doi.org/10.1016/j.biopha.2020.109978.
Prowle JR, Kirwan CJ, Bellomo R. Fluid management for the prevention and attenuation of acute kidney injury. Nat Rev Nephrol. 2014;10(1):37–47. https://doi.org/10.1038/nrneph.2013.232.
Fani F, Regolisti G, Delsante M, Cantaluppi V, Castellano G, Gesualdo L, et al. Recent advances in the pathogenetic mechanisms of sepsis-associated acute kidney injury. J Nephrol. 2018;31(3):351–9. https://doi.org/10.1007/s40620-017-0452-4.
Dancu GM, Popescu A, Sirli R, Danila M, Bende F, Tarta C, et al. The BISAP score, NLR, CRP, or BUN: Which marker best predicts the outcome of acute pancreatitis? Medicine. 2021;100(51): e28121. https://doi.org/10.1097/MD.0000000000028121.
Ahmad R, Bhatti KM, Ahmed M, Malik KA, Rehman S, Abdulgader A, et al. C-Reactive Protein as a Predictor of Complicated Acute Pancreatitis: Reality or a Myth? Cureus. 2021;13(11): e19265. https://doi.org/10.7759/cureus.19265.
Maiwall R, Chandel SS, Wani Z, Kumar S, Sarin SK. SIRS at Admission Is a Predictor of AKI Development and Mortality in Hospitalized Patients with Severe Alcoholic Hepatitis. Dig Dis Sci. 2016;61(3):920–9. https://doi.org/10.1007/s10620-015-3921-4.
Bateman RM, Sharpe MD, Jagger JE, Ellis CG, Solé-Violán J, López-Rodríguez M, et al. 36th International Symposium on Intensive Care and Emergency Medicine : Brussels. Belgium: Critical care; 2016. https://doi.org/10.1186/s13054-016-1208-6.
Wasung ME, Chawla LS, Madero M. Biomarkers of renal function, which and when? Clinica Chimica Acta Int J Clin Chem. 2015. https://doi.org/10.1016/j.cca.2014.08.039.
van den Berg MF, Schoeman JP, Defauw P, Whitehead Z, Breemersch A, Goethals K, et al. Assessment of acute kidney injury in canine parvovirus infection: Comparison of kidney injury biomarkers with routine renal functional parameters. Vet J. 2018;242:8–14. https://doi.org/10.1016/j.tvjl.2018.10.002.
Basu RK, Wong HR, Krawczeski CD, Wheeler DS, Manning PB, Chawla LS, et al. Combining functional and tubular damage biomarkers improves diagnostic precision for acute kidney injury after cardiac surgery. J Am Coll Cardiol. 2014;64(25):2753–62. https://doi.org/10.1016/j.jacc.2014.09.066.
Francoz C, Glotz D, Moreau R, Durand F. The evaluation of renal function and disease in patients with cirrhosis. J Hepatol. 2010;52(4):605–13. https://doi.org/10.1016/j.jhep.2009.11.025.
Funding
Natural science foundation of liaoning province, LZ2020068, Yuling Li
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors have declared that no conflict of interest exists.
Ethical standard
This study protocol was approved by the Ethic Committee of the First Affiliated Hospital of Dalian Medical University. The tests were conducted in compliance with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
Informed consent
Informed consent was obtained from all individual participants included in the study.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Yang, D., Zhao, L., Kang, J. et al. Development and validation of a predictive model for acute kidney injury in patients with moderately severe and severe acute pancreatitis. Clin Exp Nephrol 26, 770–787 (2022). https://doi.org/10.1007/s10157-022-02219-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10157-022-02219-8