Healthcare Systems Engineering Institute, Northeastern University, Boston, Massachusetts.
College of Engineering, Northeastern University, Boston, Massachusetts.
Infect Control Hosp Epidemiol. 2020 Mar;41(3):306-312. doi: 10.1017/ice.2019.327. Epub 2019 Dec 19.
The reported incidence of Clostridoides difficile infection (CDI) has increased in recent years, partly due to broadening adoption of nucleic acid amplification tests (NAATs) replacing enzyme immunoassay (EIA) methods. Our aim was to quantify the impact of this switch on reported CDI rates using a large, multihospital, empirical dataset.
We analyzed 9 years of retrospective CDI data (2009-2017) from 47 hospitals in the southeastern United States; 37 hospitals switched to NAAT during this period, including 24 with sufficient pre- and post-switch data for statistical analyses. Poisson regression was used to quantify the NAAT-over-EIA incidence rate ratio (IRR) at hospital and network levels while controlling for longitudinal trends, the proportion of intensive care unit patient days, changes in surveillance methodology, and previously detected infection cluster periods. We additionally used change-point detection methods to identify shifts in the mean and/or slope of hospital-level CDI rates, and we compared results to recorded switch dates.
For hospitals that transitioned to NAAT, average unadjusted CDI rates increased substantially after the test switch from 10.9 to 23.9 per 10,000 patient days. Individual hospital IRRs ranged from 0.75 to 5.47, with a network-wide IRR of 1.75 (95% confidence interval, 1.62-1.89). Reported CDI rates significantly changed 1.6 months on average after switching to NAAT testing (standard deviation, 1.9 months).
Hospitals that switched from EIA to NAAT testing experienced an average postswitch increase of 75% in reported CDI rates after adjusting for other factors, and this increase was often gradual or delayed.
近年来，艰难梭菌感染（CDI）的报告发病率有所增加，部分原因是核酸扩增检测（NAAT）的广泛应用取代了酶免疫测定（EIA）方法。我们的目的是使用大型多医院经验性数据集来量化这种转变对报告 CDI 率的影响。
我们分析了来自美国东南部 47 家医院的 9 年回顾性 CDI 数据（2009-2017 年）；在此期间，37 家医院转换为 NAAT，其中 24 家具有足够的转换前后数据进行统计分析。使用泊松回归来量化医院和网络级别上的 NAAT 优于 EIA 的发病率比（IRR），同时控制了纵向趋势、重症监护病房患者天数的比例、监测方法的变化以及先前检测到的感染群集期。我们还使用变化点检测方法来识别医院级别 CDI 率的平均值和/或斜率的变化，并将结果与记录的转换日期进行比较。
对于过渡到 NAAT 的医院，在测试转换后，未经调整的 CDI 率从每 10000 个患者天的 10.9 增加到 23.9。个别医院的 IRR 范围从 0.75 到 5.47，网络范围内的 IRR 为 1.75（95%置信区间，1.62-1.89）。在转换为 NAAT 检测后，报告的 CDI 率平均变化 1.6 个月（标准差，1.9 个月）。
在调整其他因素后，从 EIA 转换为 NAAT 检测的医院在报告的 CDI 率方面平均增加了 75%，并且这种增加通常是渐进的或延迟的。
