优化儿科化脓性链球菌感染的诊断:临床预测模型

F.C. Ihenetu , C.I. Okoro , M.M. Ozoude , K.E. Dunga , C. Nwaoha
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引用次数: 0

摘要

由化脓性链球菌引起的 A 组链球菌(GAS)感染是 12 岁以下儿童的主要健康问题,可导致扁桃体炎、风湿热和链球菌性肾小球肾炎后遗症等疾病。准确诊断对于有效治疗和预防至关重要。本研究旨在开发和验证一种临床预测规则(CPR),用于预测 12 岁以下儿童咽拭子中是否存在化脓性链球菌。我们分析了2019年1月至2022年12月期间在伊莫州奥韦里联邦大学教学医院就诊的1015名出现GAS感染症状的儿科患者的临床和实验室数据。首先从在血琼脂上培养的咽拭子中分离出化脓性链球菌,然后使用针对 Spy 1258 基因的聚合酶链式反应(PCR)进一步鉴定了 233 个阳性分离物,并通过煮沸提取 DNA 和表型方法进行确认。这 233 个已确定病例的数据被用于开发和验证 CPR。研究变量包括性别、年龄、入院病房、临床诊断和抗生素敏感性。逻辑回归模型确定了化脓性链球菌存在的重要预测因素,并通过系统的病例审查、标准化数据提取和多位审查员的交叉核对将潜在的偏差降至最低。在分析的 233 个病例中,平均年龄为 4 ± 0.25 岁,其中 62.7% 的病例年龄在 3 岁以下。扁桃体炎是主要的诊断依据,GAS 感染率从 56.7% 到 69.3% 不等。抗生素药敏试验结果各不相同,重要的预测因素包括败血症/扁桃体炎和耳道分泌物/扁桃体炎(p < 0.001)。CPR 模型的灵敏度为 95.4%,特异性为 36.8%,突出表明了该模型在加强 GAS 感染的临床诊断和管理方面的潜力。这项研究为预测儿科患者的化脓性链球菌感染提供了有价值的见解,并凸显了 CPR 在改善临床诊断和管理方面的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimizing diagnosis of pediatric Streptococcus pyogenes infections: A clinical prediction model
Group A Streptococcus (GAS) infections, caused by Streptococcus pyogenes, are a major health concern among children under 12 years, leading to conditions such as tonsillitis, rheumatic fever, and post-streptococcal glomerulonephritis. Accurate diagnosis is essential for effective treatment and prevention. This study aimed to develop and validate a Clinical Prediction Rule (CPR) for predicting the presence of S. pyogenes in throat swabs from children under 12. We analyzed clinical and laboratory data from 1015 pediatric patients presenting with symptoms suggestive of GAS infection at Federal University Teaching Hospital, Owerri, Imo State, between January 2019 and December 2022. S. pyogenes was first isolated from throat swabs cultured on blood agar, and 233 positive isolates were further identified using Polymerase Chain Reaction (PCR) targeting the Spy 1258 gene, with DNA extracted via boiling and confirmed through phenotypic methods. Data from these 233 identified cases were used to develop and validate the CPR. Variables examined included gender, age, ward of admission, clinical diagnosis, and antibiotic susceptibility. Logistic regression modeling identified significant predictors of S. pyogenes presence, with potential biases minimized through systematic case review, standardized data extraction and cross-checking by multiple reviewers. Among the 233 cases analyzed, the mean age was 4 ± 0.25 years, with 62.7 % under age 3. Tonsillitis was the predominant diagnosis, with GAS prevalence ranging from 56.7 % to 69.3 %. Antibiotic susceptibility test result varied, with significant predictors including Sepsis/Tonsillitis and ear discharge/tonsillitis (p < 0.001). The CPR model demonstrated a sensitivity of 95.4 % and a specificity of 36.8 %, highlighting its potential to enhance clinical diagnosis and management of GAS infections. This study offers valuable insights into predictors of S. pyogenes infection in pediatric patients and highlights the CPR’s potential for improving clinical diagnosis and management.
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