Early Prediction of Organ Failures in Patients with Acute Pancreatitis Using Text Mining

Jiawei Luo,Mengjiao Li,Dujiang Yang,Xiaobo Zhou,Jin Yin,Lan Lan,Shixin Huang,Juan Xiao,Pengwei Wang

doi:10.1155/2021/6683942

Abstract

It is of great significance to establish an assessment model for organ failures in the early stage of admission in acute pancreatitis (AP). And the clinical notes are underutilized. To predict organ failures for AP patients using early clinical notes in hospital, early text features obtained from the pretrained Chinese Bidirectional Encoder Representations from Transformers model and attention-based LSTM were combined with early structured features (laboratory tests, vital signs, and demographic characteristics) to predict organ failures (respiratory, cardiovascular, and renal) in 12,748 AP inpatients in West China Hospital, Sichuan University, from 2008 to 2018. The text plus structured features fusion model was used to predict organ failures, compared to the baseline model with only structured features. The performance of the model with text features added is superior to the model that only includes structured features.

Highlights

Organ failure is a serious complication of patients with acute pancreatitis (AP)
To predict organ failures for AP patients using early clinical notes in hospital, early text features obtained from the pretrained Chinese Bidirectional Encoder Representations from Transformers model and attention-based long short-term memory (LSTM) were combined with early structured features to predict organ failures in 12,748 AP inpatients in West China Hospital, Sichuan University, from 2008 to 2018. e text plus structured features fusion model was used to predict organ failures, compared to the baseline model with only structured features. e performance of the model with text features added is superior to the model that only includes structured features
Patients with AP associated with congestive heart failure (CHF) have significantly higher mortality in comparison with those without CHF [4]. erefore, it is of great significance to establish an assessment model for organ failures in the early stage of admission in AP

Summary

Introduction

Organ failure is a serious complication of patients with acute pancreatitis (AP). Acute renal failure is one of the most common causes of death in patients with severe AP [1]. To predict organ failures for AP patients using early clinical notes in hospital, early text features obtained from the pretrained Chinese Bidirectional Encoder Representations from Transformers model and attention-based LSTM were combined with early structured features (laboratory tests, vital signs, and demographic characteristics) to predict organ failures (respiratory, cardiovascular, and renal) in 12,748 AP inpatients in West China Hospital, Sichuan University, from 2008 to 2018.

Results

Conclusion