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Performance of prediction rules and guidelines in detecting serious bacterial infections among Tanzanian febrile children

机译:预测规则的表现和指导检测坦桑尼亚多斯密儿童严重细菌感染

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Health-workers in developing countries rely on clinical algorithms, such as the Integrated Management of Childhood Illnesses (IMCI), for the management of patients, including diagnosis of serious bacterial infections (SBI). The diagnostic accuracy of IMCI in detecting children with SBI is unknown. Prediction rules and guidelines for SBI from well-resourced countries at outpatient level may help to improve current guidelines; however, their diagnostic performance has not been evaluated in resource-limited countries, where clinical conditions, access to care, and diagnostic capacity differ. The aim of this study was to estimate the diagnostic accuracy of existing prediction rules and clinical guidelines in identifying children with SBI in a cohort of febrile children attending outpatient health facilities in Tanzania. Structured literature review to identify available prediction rules and guidelines aimed at detecting SBI and retrospective, external validation on a dataset containing 1005 febrile Tanzanian children with acute infections. The reference standard, SBI, was established based on rigorous clinical and microbiological criteria. Four prediction rules and five guidelines, including IMCI, could be validated. All examined rules and guidelines had insufficient diagnostic accuracy for ruling-in or ruling-out SBI with positive and negative likelihood ratios ranging from 1.04-1.87 to 0.47-0.92, respectively. IMCI had a sensitivity of 36.7% (95% CI 29.4-44.6%) at a specificity of 70.3% (67.1-73.4%). Rules that use a combination of clinical and laboratory testing had better performance compared to rules and guidelines using only clinical and or laboratory elements. Currently applied guidelines for managing children with febrile illness have insufficient diagnostic accuracy in detecting children with SBI. Revised clinical algorithms including simple point-of-care tests with improved accuracy for detecting SBI targeting in tropical resource-poor settings are needed. They should undergo careful external validation against clinical outcome before implementation, given the inherent limitations of gold standards for SBI.
机译:发展中国家的卫生工作者依赖于临床算法,例如儿童疾病的综合管理(IMCI),用于管理患者,包括诊断严重的细菌感染(SBI)。 IMCI在检测SBI儿童中的诊断准确性未知。从资源级别的资源级别的SBI预测规则和指南可能有助于改善现有指导方针;然而,他们的诊断性能尚未在资源有限的国家中进行评估,其中临床条件,获得护理和诊断能力不同。本研究的目的是估算现有预测规则的诊断准确性和临床指南,在坦桑尼亚出席坦桑尼亚的门诊卫生设施的发热儿童队列中识别SBI儿童。结构化文献综述以确定旨在检测SBI和回顾性的可用预测规则和准则,在包含1005名具有急性感染的DataSet上的外部验证。基于严格的临床和微生物标准,建立了参考标准SBI。可以验证四个预测规则和五项指南,包括IMCI,可以验证。所有审查的规则和指南都没有足够的诊断准确性,以分别为0.04-1.87至​​0.47-0.92的正负似然率的判定或排列的SBI诊断准确性。 IMCI的敏感性为36.7%(95%CI 29.4-44.6%),特异性为70.3%(67.1-73.4%)。与仅使用临床和或实验室元素的规则和指南相比,使用临床和实验室测试的组合的规则具有更好的性能。目前,用于管理发热疾病的儿童的应用指南在检测SBI儿童的诊断准确性不足。需要修订的临床算法,包括简单的护理点测试,其具有改进的精度来检测在热带资源差的设置中的SBI靶向。鉴于SBI的金标准的固有局限性,他们应该在实施之前进行仔细的外部验证,以防止临床结果。

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