PDF(Pubmed)
Abstract：
BACKGROUND: Most surveillance systems for catheter-related bloodstream infections (CRBSI) and central line-associated bloodstream infections (CLABSI) are based on manual chart review. Our objective was to validate a fully automated algorithm for CRBSI and CLABSI surveillance in intensive care units (ICU).
METHODS: We developed a fully automated algorithm to detect CRBSI, CLABSI and ICU-onset bloodstream infections (ICU-BSI) in patients admitted to the ICU of a tertiary care hospital in Switzerland. The parameters included in the algorithm were based on a recently performed systematic review. Structured data on demographics, administrative data, central vascular catheter and microbiological results (blood cultures and other clinical cultures) obtained from the hospital\'s data warehouse were processed by the algorithm. Validation for CRBSI was performed by comparing results with prospective manual BSI surveillance data over a 6-year period. CLABSI were retrospectively assessed over a 2-year period.
RESULTS: From January 2016 to December 2021, 854 positive blood cultures were identified in 346 ICU patients. The median age was 61.7 years [IQR 50-70]; 205 (24%) positive samples were collected from female patients. The algorithm detected 5 CRBSI, 109 CLABSI and 280 ICU-BSI. The overall CRBSI and CLABSI incidence rates determined by automated surveillance for the period 2016 to 2021 were 0.18/1000 catheter-days (95% CI 0.06-0.41) and 3.86/1000 catheter days (95% CI: 3.17-4.65). The sensitivity, specificity, positive predictive and negative predictive values of the algorithm for CRBSI, were 83% (95% CI 43.7-96.9), 100% (95% CI 99.5-100), 100% (95% CI 56.5-100), and 99.9% (95% CI 99.2-100), respectively. One CRBSI was misclassified as an ICU-BSI by the algorithm because the same bacterium was identified in the blood culture and in a lower respiratory tract specimen. Manual review of CLABSI from January 2020 to December 2021 (n = 51) did not identify any errors in the algorithm.
CONCLUSIONS: A fully automated algorithm for CRBSI and CLABSI detection in critically-ill patients using only structured data provided valid results. The next step will be to assess the feasibility and external validity of implementing it in several hospitals with different electronic health record systems.
METHODS: We developed a fully automated algorithm to detect CRBSI, CLABSI and ICU-onset bloodstream infections (ICU-BSI) in patients admitted to the ICU of a tertiary care hospital in Switzerland. The parameters included in the algorithm were based on a recently performed systematic review. Structured data on demographics, administrative data, central vascular catheter and microbiological results (blood cultures and other clinical cultures) obtained from the hospital\'s data warehouse were processed by the algorithm. Validation for CRBSI was performed by comparing results with prospective manual BSI surveillance data over a 6-year period. CLABSI were retrospectively assessed over a 2-year period.
RESULTS: From January 2016 to December 2021, 854 positive blood cultures were identified in 346 ICU patients. The median age was 61.7 years [IQR 50-70]; 205 (24%) positive samples were collected from female patients. The algorithm detected 5 CRBSI, 109 CLABSI and 280 ICU-BSI. The overall CRBSI and CLABSI incidence rates determined by automated surveillance for the period 2016 to 2021 were 0.18/1000 catheter-days (95% CI 0.06-0.41) and 3.86/1000 catheter days (95% CI: 3.17-4.65). The sensitivity, specificity, positive predictive and negative predictive values of the algorithm for CRBSI, were 83% (95% CI 43.7-96.9), 100% (95% CI 99.5-100), 100% (95% CI 56.5-100), and 99.9% (95% CI 99.2-100), respectively. One CRBSI was misclassified as an ICU-BSI by the algorithm because the same bacterium was identified in the blood culture and in a lower respiratory tract specimen. Manual review of CLABSI from January 2020 to December 2021 (n = 51) did not identify any errors in the algorithm.
CONCLUSIONS: A fully automated algorithm for CRBSI and CLABSI detection in critically-ill patients using only structured data provided valid results. The next step will be to assess the feasibility and external validity of implementing it in several hospitals with different electronic health record systems.
摘要：
背景：大多数导管相关性血流感染（CRBSI）和中线相关性血流感染（CLABSI）的监测系统都是基于人工图表审查。我们的目标是验证重症监护病房（ICU）中CRBSI和CLABSI监测的全自动算法。
方法：我们开发了一种全自动算法来检测CRBSI，瑞士三级医院ICU患者的CLABSI和ICU发作血流感染（ICU-BSI）。算法中包含的参数基于最近进行的系统评价。关于人口统计的结构化数据，行政数据，该算法处理了从医院数据仓库获得的中心血管导管和微生物结果（血培养和其他临床培养物）。CRBSI的验证是通过将结果与6年期间的前瞻性手动BSI监测数据进行比较来进行的。CLABSI进行了为期2年的回顾性评估。
结果：从2016年1月至2021年12月，在346名ICU患者中发现854名血培养阳性。中位年龄为61.7岁[IQR50-70]；从女性患者中收集了205个（24％）阳性样本。该算法检测到5个CRBSI，109CLABSI和280ICU-BSI。通过自动监测确定的2016年至2021年期间的CRBSI和CLABSI总体发生率为0.18/1000导管天（95％CI0.06-0.41）和3.86/1000导管天（95％CI：3.17-4.65）。敏感性,特异性，CRBSI算法的阳性预测值和阴性预测值，为83%（95%CI43.7-96.9），100%（95%CI99.5-100），100%（95%CI56.5-100），和99.9%（95%CI99.2-100），分别。通过算法将一个CRBSI错误分类为ICU-BSI,因为在血液培养物和下呼吸道样本中鉴定了相同的细菌。从2020年1月到2021年12月对CLABSI的手动审查（n=51）未发现算法中的任何错误。
结论：仅使用结构化数据对危重患者进行CRBSI和CLABSI检测的全自动算法提供了有效的结果。下一步将是评估在具有不同电子健康记录系统的几家医院中实施该计划的可行性和外部有效性。
方法：我们开发了一种全自动算法来检测CRBSI，瑞士三级医院ICU患者的CLABSI和ICU发作血流感染（ICU-BSI）。算法中包含的参数基于最近进行的系统评价。关于人口统计的结构化数据，行政数据，该算法处理了从医院数据仓库获得的中心血管导管和微生物结果（血培养和其他临床培养物）。CRBSI的验证是通过将结果与6年期间的前瞻性手动BSI监测数据进行比较来进行的。CLABSI进行了为期2年的回顾性评估。
结果：从2016年1月至2021年12月，在346名ICU患者中发现854名血培养阳性。中位年龄为61.7岁[IQR50-70]；从女性患者中收集了205个（24％）阳性样本。该算法检测到5个CRBSI，109CLABSI和280ICU-BSI。通过自动监测确定的2016年至2021年期间的CRBSI和CLABSI总体发生率为0.18/1000导管天（95％CI0.06-0.41）和3.86/1000导管天（95％CI：3.17-4.65）。敏感性,特异性，CRBSI算法的阳性预测值和阴性预测值，为83%（95%CI43.7-96.9），100%（95%CI99.5-100），100%（95%CI56.5-100），和99.9%（95%CI99.2-100），分别。通过算法将一个CRBSI错误分类为ICU-BSI,因为在血液培养物和下呼吸道样本中鉴定了相同的细菌。从2020年1月到2021年12月对CLABSI的手动审查（n=51）未发现算法中的任何错误。
结论：仅使用结构化数据对危重患者进行CRBSI和CLABSI检测的全自动算法提供了有效的结果。下一步将是评估在具有不同电子健康记录系统的几家医院中实施该计划的可行性和外部有效性。
