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Validation and development of a clinical prediction rule in clinically suspected community-acquired pneumonia.

机译:临床怀疑的社区获得性肺炎的临床预测规则的验证和发展。

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OBJECTIVES: To develop a mathematical model to predict the probability of having community-acquired pneumonia and to evaluate an already developed prediction rule that has not been validated in a clinical scenario. METHODS: Children who presented with fever and had presumptive clinical diagnosis of pneumonia were evaluated in 4 institutions of different complexity during 1 year. The variables assessed were sex, age, respiratory rate, days with fever, maximum body temperature, presence of tachypnea, cough, chest pain, intercostal retraction, nasal flaring, abdominal pain, vomiting, grunting, rales, decreased breath sounds, wheezing, fatigue, loss of appetite, loss of sleep, and season of the year. The chest radiographs were photographed and then interpreted by 2 pediatric radiologists. RESULTS: A total of 257 children were evaluated: 179 (69%) had clinical and radiological diagnosis of community-acquired pneumonia, and 78 (30%) had no radiological confirmation. A total of 96 photographs were recorded, and in 64 of the cases, there was agreement in the diagnosis between the evaluating pediatrician and the radiologists (kappa index = 0.68).With the calculated probabilities, it was possible to build a receiving operating characteristic curve and, based on the estimated coefficients we calculated, a value associated to the probability of having pneumonia. CONCLUSIONS: We developed a model including 5 variables of high level of sensitivity for the diagnosis of pneumonia. To use it, it would be useful to apply the appropriate software. In addition, we validated a clinical prediction rule of 4 variables that proved to have 93.8% sensitivity to diagnose pneumonia in children with a fever and localized rales, or decreased breath sounds, or tachypnea, or any combination of these 4 variables.
机译:目的:建立一个数学模型来预测社区获得性肺炎的可能性,并评估一个尚未制定的在临床上尚未得到验证的预测规则。方法:在1年中,在4个不同复杂程度的机构中对发烧并有临床诊断为肺炎的儿童进行了评估。评估的变量包括性别,年龄,呼吸频率,发烧天数,最高体温,呼吸急促,咳嗽,胸痛,肋间牵开,鼻扩张,腹痛,呕吐,咕gr,罗勒,呼吸音降低,喘息,疲劳,食欲不振,睡眠不足和一年四季。拍摄胸部X光片,然后由2位儿科放射科医生对其进行解释。结果:总共评估了257名儿童:179例(69%)有社区获得性肺炎的临床和影像学诊断,78例(30%)没有影像学证实。总共记录了96张照片,其中64例在评估儿科医生和放射科医生之间的诊断一致(kappa指数= 0.68)。通过计算的概率,可以建立接收操作特征曲线根据我们计算出的估计系数,得出与患肺炎的机率相关的值。结论:我们开发了一个模型,该模型包含5个高度敏感的变量,可用于诊断肺炎。要使用它,应用适当的软件将很有用。此外,我们验证了4个变量的临床预测规则,这些规则被证明对发烧,局部罗音,呼吸音降低或呼吸急促的儿童诊断肺炎敏感度高,或这4个变量的任意组合。

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