Analysis of Characteristic Factors of Nursing Safety Incidents in ENT Surgery by Deep Learning-Based Medical Data Association Rules Method

基于深度学习的医学数据关联规则方法分析耳鼻喉科手术护理安全事件的特征因素

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Abstract

It is of great significance to explore the characteristic factors of postoperative nursing safety events in patients with otolaryngology surgery and to understand the characteristics of postoperative nursing safety events in otolaryngology surgery patients. This paper carried out preoperative safety protection for 385 inpatients, and the results showed that there were 52 cases of postoperative safety nursing events. This experiment found that the coinfected lesions (P = 0.001, HR = 14.283, 95.0% C1: 9.365~21.038), the treatment period (P = 0.001, HR = 13.716, 95.0% CI: 7.147~20.275), during hospital treatment (P = 0.002, HR = 15.208, 95.0% CI: 8.918-24.237), antibiotic use (P = 0.001, HR = 14.054, 95.0% CI: 8.163-21.739), and hypertension (P = 0.001, HR = 13.976, 95.0% CI: 7.926-22.385) are the important factors affecting postoperative care; using the association rule method to control and analyze the main risk factors of postoperative infection and bleeding in ENT patients can significantly improve the prognosis.

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