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首页> 外文期刊>Journal of medical systems >An approach to model right iliac fossa pain using pain-only-parameters for screening acute appendicitis
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An approach to model right iliac fossa pain using pain-only-parameters for screening acute appendicitis

机译:使用仅疼痛参数筛选急性阑尾炎的右侧right窝疼痛模型

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摘要

Acute appendicitis (AA) is one of the commonest of multiple possible pathologies at the backdrop of Right Iliac Fossa (RIF) pain. RIFis the most common acute surgical condition of the abdomen. Even though AA is a recognized disease entity since decades, its diagnosis still lacks clinical confidence and mandates laboratory tests. Given the issue, this paper proposes a mathematical model using Pain-Only-Parameters (POP) obtained from available literature to screen AA. Weights have been assigned for each POP to create a training data matrix (N=51) and used to calculate the cumulative effect or weighted sum, which is termed as the Pain Confidence Score (PCS). Based on PCS, a group of real-world patients (N=40; AA and NA=20 each) are classified as cases of AA or non-appendicitis (NA) with satisfactory results (sensitivity 85%, specificity 75%, precision 77%, and accuracy 80%). Most rural health centers (RHC) in developing nations lack specialist services and related infrastructure. Hence, such a tool could be useful in RHC to assist general physicians in screening AA and their timely referral to higher centers.
机译:在右I窝(RIF)疼痛的背景下,急性阑尾炎(AA)是多种可能的病理中最常见的一种。 RIF是腹部最常见的急性外科疾病。尽管机管局几十年来一直是公认的疾病实体,但其诊断仍然缺乏临床信心,需要进行实验室测试。针对此问题,本文提出了一种使用仅从痛处获得的疼痛参数(POP)的数学模型来筛选AA的方法。已为每个POP分配了权重以创建训练数据矩阵(N = 51),并用于计算累积效果或加权总和,这被称为疼痛信心分数(PCS)。基于PCS,将一组真实世界的患者(N = 40; AA和NA = 20)分类为AA或非阑尾炎(NA),结果令人满意(敏感性85%,特异性75%,精密度77 %,准确性80%)。发展中国家的大多数农村卫生中心(RHC)缺乏专业服务和相关基础设施。因此,这样的工具在RHC中可能有用,可以帮助普通医师筛查AA并及时将其转诊至更高的中心。

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