Development and validation of a procedure-based organ failure assessment model for patients in the intensive care
Hiroyuki Ohbe1, Hayato Yamana1, Hiroki Matsui1
1Department of Clinical Epidemiology and Health Economics, School of Public Health The University of Tokyo Tokyo Japan.
Aim:
To develop a procedure-based organ failure assessment model for intensive care unit (ICU) patients and to examine the ability of this model to predict in-hospital mortality, with reference to the Sequential Organ Failure Assessment (SOFA) score.
Methods:
Using the Japanese nationwide Diagnosis Procedure Combination database, we identified patients aged ≥15 years who were admitted to the ICUs April 2018-March 2019. Since April 2018, Japanese health care providers have been required to input ICU patients' SOFA scores into this database. We extracted data on the following procedures on ICU admission: oxygen supplementation, invasive mechanical ventilation, blood transfusions, catecholamines, chest compression, extracorporeal membrane oxygenation, and renal replacement therapy. A procedure-based organ failure assessment model (Model 1) for in-hospital mortality was developed using therapeutic procedures for organ failure on the day of ICU admission in the derivation cohort. We also constructed a model using the SOFA score (Model 2). Discriminatory ability was assessed using area under the receiver operating characteristic curve (AUROC) in the validation cohort, and the discriminatory abilities of the models were compared.
Results:
In total, 69,019 patients were included. Overall in-hospital mortality was 7.2%. The AUROCs for Model 1 (0.810) and Model 2 (0.817) in the validation cohort did not show a statistically significant difference (P = 0.20).
Conclusion:
The models established using procedure-based organ failure assessment showed no statistically significant differences from those using the SOFA score, suggesting that procedure records in administrative databases can be used for risk adjustment in clinical studies on ICU mortality.
