Forecasting Survival Rates Post-Gastrointestinal Surgery: Integrating The New Japanese Association of Acute Medicine (JAAM Score) and Neural Network Classification

Ayu Nabila Kusuma Pradana, Aprinaldi Jasa Mantau, Guo Jiea, Shuo Zhang, Masaharu Murata, Sayoko Narahara, Tomohiko Akahoshia

Abstract


Following gastrointestinal surgery, the incidence of disseminated intravascular coagulation (DIC) has a bad prognosis. Consequently, it is essential to identify the variables that can predict the prognosis of DIC. This study will examine the factors that may affect the outcome of DIC in patients who have had gastrointestinal surgery. From 2003 to 2021, 81 patients were admitted to the intensive care unit at Kyushu University Hospital following gastrointestinal surgery. DIC scores were computed using the new Japanese Association of Acute Medicine (JAAM) score from before and after surgery. Comparisons will be made between DIC values and The Sequential Organ Failure Assessment (SOFA) score, platelet count, lactate level, and a range of biochemical markers. This study utilized machine learning techniques to determine the prognosis of DIC following gastrointestinal surgery. After gastrointestinal surgery, the results of this study are anticipated to serve as an indicator for determining patient prognosis, hence increasing life expectancy and decreasing mortality rates among DIC patients.

Keywords


DIC; Gastrointestinal Gurgery; JAAM Gcore; Machine Learning; Weka Neural Network

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References


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DOI: https://doi.org/10.17509/coelite.v3i1.68500

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