Examining the impact of the COVID-19 pandemic on hospital-associated Clostridioides difficile infection.

IF 3 4区 医学 Q2 INFECTIOUS DISEASES
Michael J Ray, Jon P Furuno, Luke C Strnad, Eric T Lofgren, Jessina C McGregor
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引用次数: 0

Abstract

Objective: To evaluate the impact of changes in the size and characteristics of the hospitalized patient population during the COVID-19 pandemic on the incidence of hospital-associated Clostridioides difficile infection (HA-CDI).

Design: Interrupted time-series analysis.

Setting: A 576-bed academic medical center in Portland, Oregon.

Methods: We established March 23, 2020 as our pandemic onset and included 24 pre-pandemic and 24 pandemic-era 30-day intervals. We built an autoregressive segmented regression model to evaluate immediate and gradual changes in HA-CDI rate during the pandemic while controlling for changes in known CDI risk factors.

Results: We observed 4.5 HA-CDI cases per 10,000 patient-days in the two years prior to the pandemic and 4.7 cases per 10,000 patient-days in the first two years of the pandemic. According to our adjusted segmented regression model, there were neither significant changes in HA-CDI rate at the onset of the pandemic (level-change coefficient = 0.70, P-value = 0.57) nor overtime during the pandemic (slope-change coefficient = 0.003, P-value = 0.97). We observed significant increases in frequency and intensity of antibiotic use, time at risk, comorbidities, and patient age before and after the pandemic onset. Frequency of C. difficile testing did not significantly change during the pandemic (P= 0.72).

Conclusions: Despite large increases in several CDI risk factors, we did not observe the expected corresponding changes in HA-CDI rate during the first two years of the COVID-19 pandemic. We hypothesize that infection prevention measures responding to COVID-19 played a role in CDI prevention.

研究 COVID-19 大流行对医院相关艰难梭菌感染的影响。
目的评估 COVID-19 大流行期间住院病人规模和特征的变化对医院相关艰难梭菌感染(HA-CDI)发病率的影响:设计:间断时间序列分析:方法:我们将 2020 年 3 月 23 日设定为医院相关艰难梭菌感染(HA-CDI)的发病日:我们将 2020 年 3 月 23 日定为大流行开始日,并纳入了 24 个大流行前和 24 个大流行时期的 30 天时间间隔。我们建立了一个自回归分段回归模型,以评估大流行期间 HA-CDI 感染率的即时和渐进变化,同时控制已知 CDI 风险因素的变化:在大流行前两年,我们观察到每 10,000 个患者日中有 4.5 例 HA-CDI 病例,而在大流行的前两年,每 10,000 个患者日中有 4.7 例 HA-CDI 病例。根据我们的调整分段回归模型,HA-CDI 感染率在大流行开始时(水平变化系数 = 0.70,P 值 = 0.57)和大流行期间(斜率变化系数 = 0.003,P 值 = 0.97)都没有显著变化。我们观察到,在大流行开始前后,抗生素使用频率和强度、风险时间、合并症和患者年龄都有明显增加。艰难梭菌检测的频率在大流行期间没有明显变化(P= 0.72):结论:尽管几种 CDI 风险因素大幅增加,但在 COVID-19 大流行的头两年中,我们并未观察到预期的 HA-CDI 感染率的相应变化。我们假设,应对 COVID-19 的感染预防措施在预防 CDI 方面发挥了作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.40
自引率
6.70%
发文量
289
审稿时长
3-8 weeks
期刊介绍: Infection Control and Hospital Epidemiology provides original, peer-reviewed scientific articles for anyone involved with an infection control or epidemiology program in a hospital or healthcare facility. Written by infection control practitioners and epidemiologists and guided by an editorial board composed of the nation''s leaders in the field, ICHE provides a critical forum for this vital information.
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