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用于预测急性发热性呼吸道疾病成人患者肺炎的临床预测规则。

Clinical prediction rule to predict pneumonia in adult presented with acute febrile respiratory illness.

机构信息

Accident & Emergency Department, Princess Margaret Hospital, Hospital Authority, Hong Kong.

Accident & Emergency Department, Tuen Mun Hospital, Hospital Authority, Hong Kong.

出版信息

Am J Emerg Med. 2019 Aug;37(8):1433-1438. doi: 10.1016/j.ajem.2018.10.039. Epub 2018 Oct 20.

Abstract

OBJECTIVE

To derive a clinical prediction rule to predict pneumonia in patients with acute febrile respiratory illness to emergency departments.

METHOD

This was a prospective multicentre study. 537 adults were recruited. Those requiring resuscitation or were hypoxaemic on presentation were excluded. Pneumonia was defined as new onset infiltrates on chest X-ray (CXR), or re-attendance within 7 days and diagnosed clinically as having pneumonia. A predictive model, the Acute Febrile Respiratory Illness (AFRI) rule was derived by logistic regression analysis based on clinical parameters. The AFRI rule was internally validated with bootstrap resampling and was compared with the Diehr and Heckerling rule.

RESULTS

In the 363 patients who underwent CXR, 100 had CXR confirmed pneumonia. There were 7 weighted factors within the ARFI rule, which on summation, gave the AFRI score: age ≥ 65 (1 point), peak temperature within 24 h ≥ 40 °C (2 points), fever duration ≥3 days (2 points), sore throat (-2 points), abnormal breath sounds (1 point), history of pneumonia (1 point) and SpO2 ≤ 96% (1 point). With the bootstrap resampling, the AFRI rule was found to be more accurate than the Diehr and Heckerling rule (area under ROC curve 0.816, 0.721 and 0.566 respectively, p < 0.001). At a cut-off of AFRI≥0, the rule was found to have 95% sensitivity, with a negative predictive value of 97.2%. Using the AFRI score, we found CXR could be avoided for patients having a score of <0.

CONCLUSION

AFRI score could assist emergency physicians in identifying pneumonia patients among all adult patients presented to ED for acute febrile respiratory illness.

摘要

目的

为急诊科急性发热性呼吸道疾病患者制定预测肺炎的临床预测规则。

方法

这是一项前瞻性多中心研究。共招募了 537 名成年人。排除需要复苏或入院时存在低氧血症的患者。肺炎的定义为胸片(CXR)上出现新的浸润影,或 7 天内再次就诊并临床诊断为肺炎。通过基于临床参数的逻辑回归分析,得出预测模型——急性发热性呼吸道疾病(AFRI)规则。使用 bootstrap 重采样对内部分验证,与 Diehr 和 Heckerling 规则进行比较。

结果

在接受 CXR 的 363 名患者中,有 100 名患者的 CXR 证实患有肺炎。ARFI 规则中有 7 个加权因素,相加得到 AFRI 评分:年龄≥65 岁(1 分),24 小时内体温峰值≥40°C(2 分),发热持续时间≥3 天(2 分),咽痛(-2 分),异常呼吸音(1 分),肺炎史(1 分)和 SpO2≤96%(1 分)。通过 bootstrap 重采样,发现 AFRI 规则比 Diehr 和 Heckerling 规则更准确(ROC 曲线下面积分别为 0.816、0.721 和 0.566,p<0.001)。在 AFRI≥0 的切点处,该规则的敏感度为 95%,阴性预测值为 97.2%。使用 AFRI 评分,我们发现评分<0 的患者可以避免进行 CXR。

结论

AFRI 评分可帮助急诊医师识别急诊科所有急性发热性呼吸道疾病患者中的肺炎患者。

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