Development and validation of a prediction model for the early occurrence of acute kidney injury in patients with acute pancreatitis

Abstract

Background

Acute pancreatitis (AP) is associated with a high incidence of acute kidney injury (AKI). This study aimed to develop a nomogram for predicting the early onset of AKI in AP patients admitted to the intensive care unit.

Method

Clinical data for 799 patients diagnosed with AP were extracted from the Medical Information Mart for Intensive Care IV database. Eligible AP patients were randomly divided into training and validation cohorts. The independent prognostic factors for the early development of AKI in AP patients were determined using the all-subsets regression method and multivariate logistic regression. A nomogram was constructed for predicting the early occurrence of AKI in AP patients. The performance of the nomogram was evaluated based on the area under the receiver operating characteristic curve (AUC), calibration curves and decision curve analysis (DCA).

Results

Seven independent prognostic factors were identified as predictive factors for early onset AKI in AP patients. The AUC of the nomogram in the training and validation cohorts were 0.795 (95% CI, 0.758–0.832) and 0.772 (95% CI, 0.711–0.832), respectively. The AUC of the nomogram was higher compared with that of the BISAP, Ranson, APACHE II scores. Further, the calibration curve revealed that the predicted outcome was in agreement with the actual observations. Finally, the DCA curves showed that the nomogram had a good clinical applicability value.

Conclusion

The constructed nomogram showed a good predictive ability for the early occurrence of AKI in AP patients.

Keywords:

• Acute pancreatitis
• acute kidney injury
• nomogram
• MIMIC
• risk factors

Acknowledgements

The authors are absolutely grateful for the publicly available MIMIC database. The authors also wish to sincerely thank my friend Fei Zhao, for his guidance on peer review comments. The authors thank the Home for Researchers editorial team (www.home-for-researchers.com) for the language editing service. The authors would like to express our special gratitude to the preprint published by Research Square, which was published on researchsquare.com website on 2022/08/14 and can be accessed through the internet link (https://www.researchsquare.com/article/rs-1961177/v1) or DOI (10.21203/rs.3.rs-1961177/v1).

Ethics approval and consent to participate

All procedures performed in the present study were in accordance with the principles outlined in the 1964 Helsinki Declaration and its later amendments. The collection of patient information and creation of the research resource was reviewed by the Institutional Review Board at the Beth Israel Deaconess Medical Center, which granted a waiver of informed consent and approved the data-sharing initiative. Because the MIMIC III database has received ethical approval from the Massachusetts Institute of Technology (Cambridge, MA) and Beth Israel Deaconess Medical Center (Boston, MA) and its data is publicly available and all patient data are deidentied.

Author contributions

XJD contributed to the collection of the data and creation of models, performed the study, contributed to its design, the analysis of the data and revised the manuscript. SMW drafted the article, revised the manuscript for important intellectual content, oversight the research activity planning and execution, and varied research outputs. YC contributed to the formal analysis of the data and oversight the research activity planning and execution; QZ conceived the study and revised the manuscript. All authors contributed substantially to the manuscript. All authors approved the final version submitted for publication.

Disclosure statement

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

Data availability statement

The data that support the findings of this study are openly available on the MIMIC-IV website at https://physionet.org/content/mimiciv/1.0/.

Additional information

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.