神经重症监护病房耐碳青霉烯类鲍曼不动杆菌感染风险预测提名图的开发与应用:一项混合方法研究。

IF 4.8 2区 医学 Q1 INFECTIOUS DISEASES
Yuping Li, Xianru Gao, Haiqing Diao, Tian Shi, Jingyue Zhang, Yuting Liu, Qingping Zeng, JiaLi Ding, Juan Chen, Kai Yang, Qiang Ma, Xiaoguang Liu, Hailong Yu, Guangyu Lu
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引用次数: 0

摘要

目的:本研究旨在开发并应用一种具有良好准确性的提名图,以预测神经重症患者发生 CRAB 感染的风险。此外,还调查了在临床实践中应用这种工具的困难和期望:方法:我们采用了混合方法序列解释性研究设计。我们首先进行了一项回顾性研究,以确定神经重症患者发生 CRAB 感染的风险因素,并进一步开发和验证了一个提名图预测模型。然后,根据所开发的预测工具,对神经重症监护室的医务人员进行深入访谈,调查他们在临床实践中使用预测工具的意见和障碍。访谈记录由 Maxqda 进行分析:在我们的队列中,CRAB 感染的发生率为 8.63%(47/544)。多变量回归分析表明,神经重症监护病房住院时间长、男性、糖尿病、红细胞(RBC)计数低、降钙素原(PCT)水平高和抗生素使用次数≥2次是神经重症监护病房患者发生 CRAB 感染的独立风险因素。我们的提名图模型在训练集和验证集上都表现出了良好的校准性和区分度,AUC 值分别为 0.816 和 0.875。此外,该模型还具有良好的临床实用性。访谈中发现的主要障碍包括 "对模型准确性的怀疑"、"神经重症监护病房住院时间指标对早期预测的延迟 "以及 "缺乏适当的临床应用方案":我们建立并验证了一个包含临床实践中易于获取的六项指标(神经重症监护室住院时间、男性、糖尿病、红细胞、PCT 水平和抗生素使用次数)的提名图,用于预测神经重症监护室患者 CRAB 感染的风险。医务人员普遍对使用该工具预测 CRAB 风险感兴趣,但在常规临床实践中提供临床预测工具仍具有挑战性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development and application of a risk nomogram for the prediction of risk of carbapenem-resistant Acinetobacter baumannii infections in neuro-intensive care unit: a mixed method study.

Objective: This study aimed to develop and apply a nomogram with good accuracy to predict the risk of CRAB infections in neuro-critically ill patients. In addition, the difficulties and expectations of application such a tool in clinical practice was investigated.

Methods: A mixed methods sequential explanatory study design was utilized. We first conducted a retrospective study to identify the risk factors for the development of CRAB infections in neuro-critically ill patients; and further develop and validate a nomogram predictive model. Then, based on the developed predictive tool, medical staff in the neuro-ICU were received an in-depth interview to investigate their opinions and barriers in using the prediction tool during clinical practice. The model development and validation is carried out by R. The transcripts of the interviews were analyzed by Maxqda.

Results: In our cohort, the occurrence of CRAB infections was 8.63% (47/544). Multivariate regression analysis showed that the length of neuro-ICU stay, male, diabetes, low red blood cell (RBC) count, high levels of procalcitonin (PCT), and number of antibiotics ≥ 2 were independent risk factors for CRAB infections in neuro-ICU patients. Our nomogram model demonstrated a good calibration and discrimination in both training and validation sets, with AUC values of 0.816 and 0.875. Additionally, the model demonstrated good clinical utility. The significant barriers identified in the interview include "skepticism about the accuracy of the model", "delay in early prediction by the indicator of length of neuro-ICU stay", and "lack of a proper protocol for clinical application".

Conclusions: We established and validated a nomogram incorporating six easily accessed indicators during clinical practice (the length of neuro-ICU stay, male, diabetes, RBC, PCT level, and the number of antibiotics used) to predict the risk of CRAB infections in neuro-ICU patients. Medical staff are generally interested in using the tool to predict the risk of CRAB, however delivering clinical prediction tools in routine clinical practice remains challenging.

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来源期刊
Antimicrobial Resistance and Infection Control
Antimicrobial Resistance and Infection Control PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH -INFECTIOUS DISEASES
CiteScore
9.70
自引率
3.60%
发文量
140
审稿时长
13 weeks
期刊介绍: Antimicrobial Resistance and Infection Control is a global forum for all those working on the prevention, diagnostic and treatment of health-care associated infections and antimicrobial resistance development in all health-care settings. The journal covers a broad spectrum of preeminent practices and best available data to the top interventional and translational research, and innovative developments in the field of infection control.
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