Real-time estimated Sequential Organ Failure Assessment (SOFA) score with intervals: improved risk monitoring with estimated uncertainty in health condition for patients in intensive care units
- PMID: 39748912
- PMCID: PMC11688259
- DOI: 10.1007/s13755-024-00331-5
Real-time estimated Sequential Organ Failure Assessment (SOFA) score with intervals: improved risk monitoring with estimated uncertainty in health condition for patients in intensive care units
Abstract
Purpose: Real-time risk monitoring is critical but challenging in intensive care units (ICUs) due to the lack of real-time updates for most clinical variables. Although real-time predictions have been integrated into various risk monitoring systems, existing systems do not address uncertainties in risk assessments. We developed a novel framework based on commonly used systems like the Sequential Organ Failure Assessment (SOFA) score by incorporating uncertainties to improve the effectiveness of real-time risk monitoring.
Methods: This study included 5351 patients admitted to the Cardiothoracic ICU in the National University Hospital in Singapore. We developed machine learning models to predict long lead-time variables and computed real-time SOFA scores using predictions. We calculated intervals to capture uncertainties in risk assessments and validated the association of the estimated real-time scores and intervals with mortality and readmission.
Results: Our model outperforms SOFA score in predicting 24-h mortality: Nagelkerke's R-squared (0.224 vs. 0.185, p < 0.001) and the area under the receiver operating characteristic curve (AUC) (0.870 vs. 0.843, p < 0.001), and significantly outperforms quick SOFA (Nagelkerke's R-squared = 0.125, AUC = 0.778). Our model also performs better in predicting 30-day readmission. We confirmed a positive net reclassification improvement (NRI) of our model over the SOFA score (0.184, p < 0.001). Similarly, we enhanced two additional scoring systems.
Conclusions: Incorporating uncertainties improved existing scores in real-time monitoring, which could be used to trigger on-demand laboratory tests, potentially improving early detection, reducing unnecessary testing, and thereby lowering healthcare expenditures, mortality, and readmission rates in clinical practice.
Supplementary information: The online version contains supplementary material available at 10.1007/s13755-024-00331-5.
Keywords: 24-h mortality; Readmission rate; Risk monitoring; SOFA score; qSOFA score.
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
Conflict of interest statement
Conflict of interestThe funders had no role in the study design, data collection, analysis, decision to publish, or the preparation of the manuscript.
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