Surveillance of catheter-associated bloodstream infections: development and validation of a fully automated algorithm

Gaud Catho, Loïc Fortchantre, Daniel Teixeira, Murielle Galas-Haddad, Filippo Boroli, Marie-Noëlle Chraïti, Mohamed Abbas, Stephan Harbarth, Niccolò Buetti
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Abstract

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). 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. 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. 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.
导管相关血流感染监测:全自动算法的开发与验证
导管相关血流感染(CRBSI)和中心管路相关血流感染(CLABSI)的监控系统大多基于人工病历审查。我们的目标是验证一种用于重症监护病房(ICU)CRBSI 和 CLABSI 监控的全自动算法。我们开发了一种全自动算法,用于检测瑞士一家三甲医院重症监护室住院患者的 CRBSI、CLABSI 和 ICU 引起的血流感染(ICU-BSI)。该算法所包含的参数是基于最近进行的一项系统综述。该算法处理了从医院数据仓库中获取的有关人口统计学、管理数据、中央血管导管和微生物学结果(血液培养和其他临床培养)的结构化数据。通过将结果与 6 年间前瞻性人工 BSI 监控数据进行比较,对 CRBSI 进行了验证。对 CLABSI 进行了为期两年的回顾性评估。从 2016 年 1 月到 2021 年 12 月,在 346 名 ICU 患者中发现了 854 份阳性血培养。中位年龄为 61.7 岁 [IQR 50-70];205 份(24%)阳性样本来自女性患者。该算法检测出 5 例 CRBSI、109 例 CLABSI 和 280 例 ICU-BSI。通过自动监测确定的 2016 年至 2021 年期间 CRBSI 和 CLABSI 总发生率分别为 0.18/1000 个导管日(95% CI 0.06-0.41)和 3.86/1000 个导管日(95% CI:3.17-4.65)。该算法对 CRBSI 的敏感性、特异性、阳性预测值和阴性预测值分别为 83% (95% CI 43.7-96.9)、100% (95% CI 99.5-100)、100% (95% CI 56.5-100) 和 99.9% (95% CI 99.2-100)。由于在血液培养和下呼吸道标本中发现了相同的细菌,因此该算法将 1 例 CRBSI 误判为 ICU-BSI。对 2020 年 1 月至 2021 年 12 月的 CLABSI(n = 51)进行人工审核后,未发现算法中的任何错误。仅使用结构化数据对重症患者进行 CRBSI 和 CLABSI 检测的全自动算法提供了有效的结果。下一步将评估在几家拥有不同电子健康记录系统的医院实施该算法的可行性和外部有效性。
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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