Development and validation of an automated antimicrobial surveillance system based on indications for antimicrobial administration.

IF 1.9 4区 医学 Q3 INFECTIOUS DISEASES Journal of Infection and Chemotherapy Pub Date : 2024-07-14 DOI:10.1016/j.jiac.2024.07.012
Mikiyasu Sakai, Takamasa Sakai, Toshitaka Watariguchi, Atsushi Kawabata, Fumiko Ohtsu
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Abstract

Introduction: We developed an antimicrobial and patient background surveillance system (APBSS), an automated surveillance system that can calculate surveillance data such as antimicrobial use and detection of antimicrobial resistance for each indication of antimicrobial administration. We evaluated the validity of the APBSS data.

Methods: Eligible patients were hospitalized at the Toyota Kosei Hospital on July 7, 2022. Evaluated surveillance data included antimicrobial administration, indications for antimicrobial administration, and diagnosis. In the APBSS, surveillance data were calculated using the Diagnosis Procedure Combination data and Japan Nosocomial Infections Surveillance laboratory data. Using surveillance data collected by the Point Prevalence Survey (PPS) as a reference standard, the agreement between the results calculated based on the APBSS was evaluated using Cohen's kappa coefficient. Indications for antimicrobial administration and diagnosis were analyzed in patients identified for antimicrobial administration in PPS or APBSS.

Results: A total of 582 patients were included in this study, 223 of whom were evaluated for indications for antimicrobial administration and diagnosis. For the indications of antimicrobial administration, the Cohen's kappa coefficient was almost perfect (0.81-1.00) for all items. Cohen's kappa coefficient for the diagnosis of healthcare-associated infections was low. However, in major diseases (pneumonia and intra-abdominal, and symptomatic upper urinary tract infections) among community-acquired infections (CAIs) diagnosis, Cohen's kappa coefficient was substantial (0.61-0.80).

Conclusions: The APBSS can identify indications for antimicrobial administration and major CAIs with high accuracy. Therefore, the APBSS can calculate surveillance data, such as antimicrobial use and detection of antimicrobial resistance, for each of these items.

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开发并验证基于抗菌药使用适应症的自动抗菌药监控系统。
介绍:我们开发了一个抗菌药物和患者背景监测系统(APBSS),这是一个自动监测系统,可以计算监测数据,如抗菌药物的使用和每个抗菌药物给药适应症的抗菌药物耐药性检测。我们对 APBSS 数据的有效性进行了评估:符合条件的患者于 2022 年 7 月 7 日在丰田佼成医院住院。评估的监控数据包括抗菌药物用量、抗菌药物用量适应症和诊断。在 APBSS 中,监测数据是通过诊断程序组合数据和日本非社会性感染监测实验室数据计算得出的。以点流行率调查(PPS)收集的监测数据为参考标准,使用科恩卡帕系数(Cohen's kappa coefficient)评估了根据 APBSS 计算出的结果之间的一致性。对在 PPS 或 APBSS 中确定需要使用抗菌药物的患者的抗菌药物使用指征和诊断进行了分析:本研究共纳入了 582 例患者,其中 223 例患者接受了抗菌药物治疗和诊断适应症评估。在抗菌药使用指征方面,所有项目的科恩卡帕系数几乎都是完美的(0.81-1.00)。医疗相关感染诊断的科恩卡帕系数较低。然而,在社区获得性感染(CAIs)诊断的主要疾病(肺炎、腹腔内感染和无症状上尿路感染)中,科恩卡帕系数很高(0.61-0.80):结论:APBSS能高度准确地识别抗菌药物使用指征和主要的社区获得性感染。因此,APBSS 可以计算每个项目的监测数据,如抗菌药物的使用和抗菌药物耐药性的检测。
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来源期刊
Journal of Infection and Chemotherapy
Journal of Infection and Chemotherapy INFECTIOUS DISEASES-PHARMACOLOGY & PHARMACY
CiteScore
4.10
自引率
4.50%
发文量
303
审稿时长
47 days
期刊介绍: The Journal of Infection and Chemotherapy (JIC) — official journal of the Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases — welcomes original papers, laboratory or clinical, as well as case reports, notes, committee reports, surveillance and guidelines from all parts of the world on all aspects of chemotherapy, covering the pathogenesis, diagnosis, treatment, and control of infection, including treatment with anticancer drugs. Experimental studies on animal models and pharmacokinetics, and reports on epidemiology and clinical trials are particularly welcome.
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