Wang Shu, Li Jing, Dai Jinghong, Zhang Xuemin, Tang Wenjuan, Li Jing, Liu Yu, Wu Xufeng, Fan Xiaoyun
The Department of Geriatric Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, People's Republic of China.
Department of Geriatrics, The Third Affiliated Hospital of Anhui Medical University (The First People's Hospital of Hefei), Hefei, Anhui Province, People's Republic of China.
Infect Drug Resist. 2023 Oct 5;16:6549-6566. doi: 10.2147/IDR.S422564. eCollection 2023.
The aim of this study was to establish risk prediction and prognosis models for multidrug-resistant bacterial infections (MDRB) in elderly patients with pulmonary infections in a multicenter setting.
This study is a retrospective cohort analysis in Anhui province of China. Data dimension reduction and feature selection were performed using the lasso regression model. Multifactorial regression analysis to identify risk factors associated with MDRB infection and prognosis. The relevant risks of each patient in the prognostic training cohort were scored based on prognostic independent risk factors. Subsequently, patients were classified into high-risk and low-risk groups, and survival differences were compared between them. Finally, models were established based on independent risk factors for infection, risk groups, and independent prognostic factors, and were presented on nomograms. The predictive accuracy of the model was assessed using corresponding external validation set data.
The study cohort comprised 994 elderly patients with pulmonary infection. Multivariate analysis revealed that endotracheal intubation, previous antibiotic use beyond 2 weeks, and concurrent respiratory failure or cerebrovascular disease were independent risk factors associated with the incidence of MDRB infection. Cox regression analysis identified respiratory failure, malnutrition, an APACHE II score of at least 20, and higher blood creatinine levels as independent prognostic risk factors. The models were validated using an external validation dataset from multiple centers, which demonstrated good diagnostic ability and a good fit with a fair benefit.
In conclusion, our study provides an appropriate and generalisable assessment of risk factors affecting infection and prognosis in patients with MDRB, contributing to improved early identification of patients at higher risk of infection and death, and appropriately guiding clinical management.
本研究旨在建立多中心环境下老年肺部感染患者多重耐药菌感染（MDRB）的风险预测和预后模型。
本研究是在中国安徽省进行的一项回顾性队列分析。使用套索回归模型进行数据降维和特征选择。进行多因素回归分析以确定与MDRB感染及预后相关的危险因素。根据预后独立危险因素对预后训练队列中每位患者的相关风险进行评分。随后，将患者分为高风险组和低风险组，并比较两组之间的生存差异。最后，基于感染的独立危险因素、风险组和独立预后因素建立模型，并以列线图呈现。使用相应的外部验证集数据评估模型的预测准确性。
研究队列包括994例老年肺部感染患者。多变量分析显示，气管插管、既往使用抗生素超过2周以及并发呼吸衰竭或脑血管疾病是与MDRB感染发生率相关的独立危险因素。Cox回归分析确定呼吸衰竭、营养不良、APACHE II评分至少为20以及较高的血肌酐水平为独立的预后风险因素。使用来自多个中心的外部验证数据集对模型进行验证，结果表明该模型具有良好的诊断能力和较好的拟合度及获益。
总之，我们的研究为影响MDRB患者感染和预后的危险因素提供了合适且可推广的评估，有助于更好地早期识别感染和死亡风险较高的患者，并合理指导临床管理。
