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将就诊时的临床体征与临床医生的非分析性推理纳入急诊科发热儿童严重细菌感染预测模型中。

Integrating Clinical Signs at Presentation and Clinician's Non-analytical Reasoning in Prediction Models for Serious Bacterial Infection in Febrile Children Presenting to Emergency Department.

作者信息

Urbane Urzula Nora, Petrosina Eva, Zavadska Dace, Pavare Jana

机构信息

Department of Pediatrics, Riga Stradins University, Riga, Latvia.

Department of Pediatrics, Children's Clinical University Hospital, Riga, Latvia.

出版信息

Front Pediatr. 2022 Apr 25;10:786795. doi: 10.3389/fped.2022.786795. eCollection 2022.

Abstract

OBJECTIVE

Development and validation of clinical prediction model (CPM) for serious bacterial infections (SBIs) in children presenting to the emergency department (ED) with febrile illness, based on clinical variables, clinician's "gut feeling," and "sense of reassurance.

MATERIALS AND METHODS

Febrile children presenting to the ED of Children's Clinical University Hospital (CCUH) between April 1, 2017 and December 31, 2018 were enrolled in a prospective observational study. Data on clinical signs and symptoms at presentation, together with clinician's "gut feeling" of something wrong and "sense of reassurance" were collected as candidate variables for CPM. Variable selection for the CPM was performed using stepwise logistic regression (forward, backward, and bidirectional); Akaike information criterion was used to limit the number of parameters and simplify the model. Bootstrapping was applied for internal validation. For external validation, the model was tested in a separate dataset of patients presenting to six regional hospitals between January 1 and March 31, 2019.

RESULTS

The derivation cohort consisted of 517; 54% ( = 279) were boys, and the median age was 58 months. SBI was diagnosed in 26.7% ( = 138). Validation cohort included 188 patients; the median age was 28 months, and 26.6% ( = 50) developed SBI. Two CPMs were created, namely, CPM1 consisting of six clinical variables and CPM2 with four clinical variables plus "gut feeling" and "sense of reassurance." The area under the curve (AUC) for receiver operating characteristics (ROC) curve of CPM1 was 0.744 (95% CI, 0.683-0.805) in the derivation cohort and 0.692 (95% CI, 0.604-0.780) in the validation cohort. AUC for CPM2 was 0.783 (0.727-0.839) and 0.752 (0.674-0.830) in derivation and validation cohorts, respectively. AUC of CPM2 in validation population was significantly higher than that of CPM1 [ = 0.037, 95% CI (-0.129; -0.004)]. A clinical evaluation score was derived from CPM2 to stratify patients in "low risk," "gray area," and "high risk" for SBI.

CONCLUSION

Both CPMs had moderate ability to predict SBI and acceptable performance in the validation cohort. Adding variables "gut feeling" and "sense of reassurance" in CPM2 improved its ability to predict SBI. More validation studies are needed for the assessment of applicability to all febrile patients presenting to ED.

摘要

目的

基于临床变量、临床医生的“直觉”和“安心感”,开发并验证用于急诊科(ED)发热性疾病患儿严重细菌感染(SBI)的临床预测模型(CPM)。

材料与方法

2017年4月1日至2018年12月31日期间在儿童临床大学医院(CCUH)急诊科就诊的发热患儿被纳入一项前瞻性观察研究。收集就诊时的临床体征和症状数据,以及临床医生对异常情况的“直觉”和“安心感”,作为CPM的候选变量。使用逐步逻辑回归(向前、向后和双向)进行CPM的变量选择;采用赤池信息准则来限制参数数量并简化模型。应用自抽样法进行内部验证。为进行外部验证,该模型在2019年1月1日至3月31日期间到六家地区医院就诊的另一组患者数据集中进行测试。

结果

推导队列由517名患者组成;54%(n = 279)为男性,中位年龄为58个月。26.7%(n = 138)被诊断为SBI。验证队列包括188名患者;中位年龄为28个月,26.6%(n = 50)发生SBI。创建了两个CPM,即由六个临床变量组成的CPM1和由四个临床变量加上“直觉”和“安心感”组成的CPM2。CPM1在推导队列中受试者工作特征(ROC)曲线的曲线下面积(AUC)为0.744(95%CI,0.683 - 0.805),在验证队列中为0.692(95%CI,0.604 - 0.780)。CPM2在推导队列和验证队列中的AUC分别为0.783(0.727 - 0.839)和0.752(0.674 - 0.830)。CPM2在验证人群中的AUC显著高于CPM1[P = 0.037,95%CI(-0.129;-0.004)]。从CPM2得出一个临床评估分数,将患者分为SBI的“低风险”、“灰色区域”和“高风险”。

结论

两个CPM在预测SBI方面都有中等能力,在验证队列中的表现可接受。在CPM2中加入“直觉”和“安心感”变量提高了其预测SBI的能力。需要更多的验证研究来评估其对所有到急诊科就诊的发热患者的适用性。

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