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Abstract: FR-PO084

Externally Validated Postoperative Long-Term Adverse Event Prediction Model for Non-Cardiac Surgery: An Extension of Simple Postoperative AKI Risk (SPARK) Model

Session Information

Category: Acute Kidney Injury

  • 101 AKI: Epidemiology‚ Risk Factors‚ and Prevention

Authors

  • Park, Sehoon, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)
  • Kwon, Soie, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)
  • Kim, Ji Eun, Korea University Guro Hospital, Seoul, Korea (the Republic of)
  • Hwang, Jin Ho, Chung Ang University Hospital, Seoul, Korea (the Republic of)
  • Baek, Chung Hee, Asan Medical Center, Songpa-gu, Seoul , Korea (the Republic of)
  • Lee, Jeonghwan, Seoul National University Seoul Metropolitan Government Boramae Medical Center, Dongjak-gu, Seoul , Korea (the Republic of)
  • Kim, Yong Chul, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)
  • Kim, Dong Ki, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)
  • Joo, Kwon Wook, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)
  • Kim, Yon Su, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)
  • Lee, Hajeong, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)
Background

We aimed to construct an externally validated postoperative long-term adverse event prediction model based on acute kidney (AKI) related variables. We extended our previous Simple Postoperative AKI RisK (SPARK) model to suggest a comprehensive prediction-system for postoperative adverse events related to kidney function.

Methods

This model development study retrospectively included 4 observational cohorts. The model development cohort included 33,636 non-cardiac surgery patients from Seoul National University. Three external validation cohorts were constructed: including external non-cardiac surgery cases from other hospitals or duration (N=33,943, 56,012, and 15,220). Primary study outcome was composite adverse event of dialysis or mortality within 1 year. Multivariable Cox regression model including the variables consist of the SPARK index, baseline malignancy, and postoperative AKI stage was used for model construction.

Results

The prediction model for kidney failure or mortality within one year showed acceptable performance (c-index 0.752) in the development cohort. When the model was applied to the validation cohorts, the prediction performances were also acceptable (c-index 0.735, 0.755, and 0.843). The model has been constructed as a calculator with combination of the SPARK index for comprehensive usage for nephrologists for postoperative adverse event risk assessment based on kidney related variables.

Conclusion

The prediction model for long-term adverse event after non-cardiac surgery provides a useful way to predict long-term risks based on kidney function related variables, along with the prediction for the risks of postoperative AKI.