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评估 ICU 中血液培养采集的标准化决策算法。

Assessing a standardized decision-making algorithm for blood culture collection in the intensive care unit.

机构信息

Memorial Sloan Kettering Cancer Center, Department of Medicine, USA; Montefiore Medical Center, Department of Medicine, USA.

Montefiore Medical Center, Department of Medicine, USA.

出版信息

J Crit Care. 2023 Jun;75:154255. doi: 10.1016/j.jcrc.2023.154255. Epub 2023 Feb 10.

DOI:10.1016/j.jcrc.2023.154255
PMID:36773367
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10548340/
Abstract

PURPOSE

Blood cultures are commonly ordered for patients with low risk of bacteremia. Indications for obtaining blood cultures are often broad and ill defined, and decision algorithms for appropriate blood cultures have not been comprehensively evaluated in critically-ill populations.

METHODS

We conducted a retrospective analysis to assess the frequency of inappropriate blood cultures in the ICUs at Montefiore Medical Center based on an evidence-based guidance algorithm. Blood cultures were reviewed against this algorithm to determine their appropriateness. We calculated the prevalence of inappropriate blood culture and explored the reasons for these collected cultures.

RESULTS

300 patients were randomly selected from an initial cohort of 3370 patients. 294 patients were included and of these, 167 patients had at least 1 blood culture drawn. 125 patients had one or more inappropriate blood culture. 61.4% of blood cultures drawn were assessed to be inappropriate. The most common reason for inappropriate cultures was a culture drawn as a result of isolated fever or leukocytosis.

CONCLUSION

In a cohort of critically-ill patients, inappropriate blood cultures were common. The indications for blood cultures are often not evidence-based, and evidence-based algorithms to guide the collection of blood cultures may offer a way to decrease inappropriate culture orders.

摘要

目的

通常为低菌血症风险患者采集血培养。获取血培养的适应证通常较广泛且不明确,尚未对危重症患者进行全面评估获取血培养的适宜决策算法。

方法

我们进行了一项回顾性分析,基于循证指导算法,评估了 Montefiore 医疗中心 ICU 中血培养的不适当频率。根据该算法对血培养进行了评估,以确定其适宜性。我们计算了不适当血培养的患病率,并探讨了这些采集培养物的原因。

结果

从最初的 3370 例患者中随机选择了 300 例患者。纳入了 294 例患者,其中 167 例患者至少抽取了 1 份血培养。125 例患者有 1 份或多份血培养不适当。抽取的血培养中 61.4%被评估为不适当。不适当培养的最常见原因是发热或白细胞增多时单独进行培养。

结论

在一组危重症患者中,不适当的血培养很常见。血培养的适应证通常不是基于证据的,基于证据的算法可用于指导血培养的采集,从而可能减少不适当的培养物。

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JAMA Pediatr. 2022 Jul 1;176(7):690-698. doi: 10.1001/jamapediatrics.2022.1024.
2
Using machine learning to predict blood culture outcomes in the emergency department: a single-centre, retrospective, observational study.使用机器学习预测急诊科血培养结果:一项单中心、回顾性、观察性研究。
BMJ Open. 2022 Jan 4;12(1):e053332. doi: 10.1136/bmjopen-2021-053332.
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J Clin Microbiol. 2020 Sep 22;58(10). doi: 10.1128/JCM.01053-20.
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