The Accuracy of Infection Diagnoses Among Patients Meeting Sepsis-3 Criteria in the Emergency Department.
The Accuracy of Infection Diagnoses Among Patients Meeting Sepsis-3 Criteria in the Emergency Department.
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急诊科符合脓毒症 3 标准的患者感染诊断的准确性。
DOI：
10.1093/cid/ciad240
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Arias,CesarA
中科院分区：
文献类型：
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作者：
Adelman,MaxW;Septimus,EdwardJ;Arias,CesarA
致编辑-我们饶有兴趣地阅读了Hooper等人的文章，他们研究了急诊科符合脓毒症-3标准的患者感染诊断的准确性[1]。脓毒症是一种具有多种非感染性模拟症状的异质性综合征，很难区分感染和非感染[2，3]。推定为脓毒症的患者的感染率数据可以指导护理这些患者的临床医生，并为早期脓毒症护理提供政策参考[4]。因此，准确确定明显脓毒症患者是否有感染的研究是至关重要的。这些研究中一个关键的复杂因素是，没有感染诊断的金标准。在缺乏明确的尸检结果的情况下，专家临床医生临时裁决可能是确定患者是否感染的最准确的方法。医生，甚至是进行回顾性病例回顾的专家，对患者是否真的感染存在分歧[5]。为了试图减少这种误诊风险，其他回溯性确定感染可能性的研究使用了，例如，多学科团队(包括高级重症监护医生和传染病专家)[6]达成的共识，两名医生独立审查(由第三名审查者裁决分歧)[7]，以及由3名专家组成的小组[8]作为金标准。在这里，Hooper等人没有明确报告有多少研究人员审查了每个病例以确定主要结果(感染是否存在)[1]。然而，最初的审查似乎是由每个患者只有一名评审员进行的，10%的复审。虽然我们毫不怀疑所有的评审员都受过良好的培训，但我们担心的是，对于90%的患者来说，只有一名评审员，而且该评审员不一定是临床医生。即使是专业的临床医生也可能不同意感染的概率[5]。因此，依靠单一审查者的裁决是不够的，特别是在感染诊断的假阳性比例明显低于类似研究的情况下[3，6]。考虑到多个评价者之间的潜在分歧，对主要结果(有感染与无感染)进行敏感性分析将是有帮助的。至少，作者可以提供关于感染与非感染裁决的进一步细节，由第二审查者在10%的重新审查的案例中(除了只报告kappa统计数据)。在未来，更好的生物标志物和诊断算法有望使假定为脓毒症的患者更容易和更准确地诊断感染。目前，我们只能依靠不完善的和主观的措施，如临床医生的决定。由于这些数据推动了每年近200万美国脓毒症患者的临床和政策决策[4，9，10]，我们应该尝试使它们尽可能准确。
TO THE EDITOR—We read with interest the article by Hooper et al who studied the accuracy of infection diagnoses among patients who met Sepsis-3 criteria in the emergency department [1]. Sepsis is a heterogenous syndrome with multiple noninfectious mimics, and distinguishing infection from noninfection is difficult [2, 3]. Data on rates of infection among patients who present with presumed sepsis can guide clinicians who care for these patients as well as inform policy around early sepsis care [4]. Therefore, studies that accurately determine whether patients with apparent sepsis have infection are crucially important. A key complicating factor in these studies is that there is no gold standard for infection diagnosis. Short of definitive autopsy findings, expert clinician post hoc adjudication is likely the most accurate method to determine whether a patient was infected. Physicians, even experts who conduct retrospective case reviews, disagree on whether a patient truly had an infection or not [5]. To attempt to mitigate this risk of misdiagnosis, other studies that retrospectively determined the likelihood of infection have used, for example, consensus by a multidisciplinary team (including senior critical care physicians and infectious disease experts)[6], 2-physician independent review (with a third reviewer adjudicating disagreements)[7], and panels comprised of 3 experts [8] as the gold standard. Here, Hooper et al do not explicitly report how many investigators reviewed each case to determine the primary outcome (infection presence or absence)[1]. However, it seems that the initial review was conducted by just 1 reviewer per patient, and a 10% subset re-reviewed.While we do not doubt that all reviewers were well trained, we are concerned that for 90% of patients, there was only 1 reviewer, and that reviewer was not necessarily a clinician. Even expert clinicians may disagree regarding the probability of infection [5]. Therefore, relying on single-reviewer adjudication is insufficient, especially since the proportion of false-positive infection diagnoses was markedly lower than in similar studies [3, 6]. A sensitivity analysis of the primary outcome (infection present vs absent) considering potential disagreements among multiple reviewers would have been helpful. At the very least, the authors could provide further details on infection vs noninfection adjudication by the second reviewer (aside from just reporting the kappa statistic) in the 10% of cases that were re-reviewed. In the future, better biomarkers and diagnostic algorithms will hopefully make infection diagnosis easier and more accurate in patients with presumed sepsis. For now, we have to rely on imperfect and subjective measures such as clinician determination. Since these data drive clinical and policy decision-making for nearly 2 million Americans with sepsis per year [4, 9, 10], we should attempt to make them as accurate as possible.