对门诊患者流感风险评分 FluScore 进行前瞻性外部验证。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-04-15 DOI:10.1093/fampra/cmae014
Mark H Ebell, Ariella Dale, Dan J Merenstein, Bruce Barrett, Cassie Hulme, Sarah Walters, Alea Sabry, Michelle Bentivegna
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引用次数: 0

摘要

背景:对急性下呼吸道感染(LRTI)患者进行流感检测很常见,在某些情况下,对所有 LRTI 患者都进行检测。更有选择性的检测方法可能更有效:我们使用了两项前瞻性研究的数据,这两项研究都是在美国基层医疗机构和紧急医疗机构进行的,共招募了急性下呼吸道感染(LRTI)或流感样疾病患者。数据收集于 2016、2019、2021 和 2022 年流感季节。所有患者都接受了聚合酶链反应(PCR)流感检测,并根据患者首次就诊时报告的症状计算出流感评分。报告了每个风险组的流感概率以及每个风险等级的分层可能性比(SSLRs):结果:根据流感季节和人群的总体差异,各风险组的流感流行率有所不同。然而,根据 SSLRs,FluScore 在不同季节和人群中表现出一致的性能。流感评分的 SSLR 范围一致:低风险组为 0.20 至 0.23,中风险组为 0.63 至 0.99,高风险组为 1.46 至 1.67。根据这些范围的中点得出的诊断几率比为 7.25:流感评分可简化患者分类,确定可免于检测的患者,同时确定快速流感检测的候选者。这有可能比 "一刀切 "的检测策略更有效,因为它能战略性地将检测用于最有可能受益的患者。它有可能在远程保健环境中使用。
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Prospective external validation of the FluScore risk score for influenza in outpatients.

Background: Testing for influenza in patients with acute lower respiratory tract infection (LRTI) is common and in some cases is performed for all patients with LRTI. A more selective approach to testing could be more efficient.

Methods: We used data from two prospective studies in the US primary and urgent care settings that enrolled patients with acute LRTI or influenza-like illness. Data were collected in the 2016, 2019, 2021, and 2022 flu seasons. All patients underwent polymerase chain reaction (PCR) testing for influenza and the FluScore was calculated based on patient-reported symptoms at their initial visit. The probability of influenza in each risk group was reported, as well as stratum-specific likelihood ratios (SSLRs) for each risk level.

Results: The prevalence of influenza within risk groups varied based on overall differences in flu seasons and populations. However, the FluScore exhibited consistent performance across various seasons and populations based on the SSLRs. The FluScore had a consistent SSLR range of 0.20 to 0.23 for the low-risk group, 0.63 to 0.99 for the moderate-risk group, and 1.46 to 1.67 for the high-risk group. The diagnostic odds ratio based on the midpoints of these ranges was 7.25.

Conclusions: The FluScore could streamline patient categorization, identifying patients who could be exempted from testing, while identifying candidates for rapid influenza tests. This has the potential to be more efficient than a "one size fits all" test strategy, as it strategically targets the use of tests on patients most likely to benefit. It is potentially usable in a telehealth setting.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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