人工神经网络作为慢性肾病患者感染风险的诊断工具

The Artificial Neural Network as a Diagnostic Tool of the Risk of Infection among Patients with Chronic Kidney Disease.

作者信息

Stojanowski Jakub, Konieczny Andrzej, Lis Łukasz, Frosztęga Weronika, Brzozowska Patrycja, Ciszewska Anna, Rydzyńska Klaudia, Sroka Michał, Krakowska Kornelia, Gołębiowski Tomasz, Hruby Zbigniew, Kusztal Mariusz, Krajewska Magdalena

机构信息

Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Borowska 213, 50-556 Wroclaw, Poland.

Department of Nephrology with Transplantation and Internal Medicine Subunits, Regional Specialistic Hospital, Kamienskiego 73a, 51-124 Wroclaw, Poland.

出版信息

J Clin Med. 2023 Jul 18;12(14):4751. doi: 10.3390/jcm12144751.

DOI:10.3390/jcm12144751

PMID:37510869

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10380971/

Abstract

The majority of recently published studies indicate a greater incidence and mortality due to infection (CDI) in patients with chronic kidney disease (CKD). Hospitalization, older age, the use of antibiotics, immunosuppression, proton pump inhibitors (PPI), and chronic diseases such as CKD are responsible for the increased prevalence of infections. The aim of the study is to identify clinical indicators allowing, in combination with artificial intelligence (AI) techniques, the most accurate assessment of the patients being at elevated risk of CDI.

摘要

最近发表的大多数研究表明，慢性肾脏病（CKD）患者因感染（CDI）导致的发病率和死亡率更高。住院、高龄、使用抗生素、免疫抑制、质子泵抑制剂（PPI）以及CKD等慢性疾病是感染患病率增加的原因。本研究的目的是确定临床指标，结合人工智能（AI）技术，对CDI风险升高的患者进行最准确的评估。