Comparison of the accuracy of hematological parameters in the diagnosis of neonatal sepsis: a network meta-analysis.

IF 5.4 2区医学 Q1 INFECTIOUS DISEASES

Infection Pub Date : 2024-08-02 DOI:10.1007/s15010-024-02354-2

Rong Huang, Tai-Liang Lu, Ri-Hui Liu

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引用次数: 0

Abstract

Background: Currently, there are hundreds of hematological parameters used for rapid diagnosis of neonatal sepsis, but there is no network meta-analysis to compare the diagnostic efficacy of these parameters.

Methods: We searched for literature on the diagnostic neonatal sepsis and selected 20 of the most common parameters to compare their diagnostic efficacy. We used Bayesian network meta-analysis, Frequentist network meta-analysis, and individual traditional diagnostic meta-analysis to analyze the data and verify the stability of the results. Based on the above analysis, we ranked the diagnostic efficacy of 20 parameters and searched for the optimal indicator. We also conducted subgroup analysis based on different designs. GRADE was used to evaluate the quality of evidence.

Results: 311 articles were included in the analysis, of which 206 articles were included in the network meta-analysis. Bayesian models fond the top three of the advantage index were P-SEP, SAA, and CD64. In Individual model, P-SEP, SAA, and CD64 had the best sensitivity; ABC, SAA, and P-SEP had the best specificity. Frequentist model showed that CD64, P-SEP, and IL-10 ranked in the top three for sensitivity, while P-SEP, ABC, and I/M in specificity. Overall, P-SEP, SAA, CD64, and PCT have good sensitivity and specificity among all the three methods. The results of subgroup analysis were consistent with the overall analysis. All evidence was mostly of moderate or low quality.

Conclusions: P-SEP, SAA, CD64, and PCT have good diagnostic efficacy for neonatal sepsis. However, further studies are required to confirm these findings.

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比较血液学参数诊断新生儿败血症的准确性：一项网络荟萃分析。

背景：目前，用于快速诊断新生儿败血症的血液学参数有数百种，但没有网络荟萃分析比较这些参数的诊断效果：目前，用于快速诊断新生儿败血症的血液学参数有数百种，但还没有网络荟萃分析来比较这些参数的诊断效果：我们检索了有关新生儿败血症诊断的文献，并选择了 20 个最常见的参数来比较它们的诊断效果。我们采用贝叶斯网络荟萃分析、频数网络荟萃分析和个体传统诊断荟萃分析对数据进行分析，并验证结果的稳定性。在上述分析的基础上，我们对 20 个参数的诊断效果进行了排序，并寻找最佳指标。我们还根据不同的设计进行了亚组分析。采用 GRADE 评估证据质量：311篇文章被纳入分析，其中206篇文章被纳入网络荟萃分析。贝叶斯模型认为优势指数前三名分别是P-SEP、SAA和CD64。在个体模型中，P-SEP、SAA和CD64的敏感性最好；ABC、SAA和P-SEP的特异性最好。频数模型显示，CD64、P-SEP 和 IL-10 的灵敏度排在前三位，而 P-SEP、ABC 和 I/M 的特异性排在前三位。总体而言，在所有三种方法中，P-SEP、SAA、CD64 和 PCT 具有良好的灵敏度和特异性。亚组分析结果与总体分析结果一致。所有证据大多为中等或低质量：结论：P-SEP、SAA、CD64 和 PCT 对新生儿败血症具有良好的诊断效果。然而，还需要进一步的研究来证实这些发现。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Infection 医学-传染病学

CiteScore

12.50

自引率

1.30%

发文量

224

审稿时长

6-12 weeks

期刊介绍： Infection is a journal dedicated to serving as a global forum for the presentation and discussion of clinically relevant information on infectious diseases. Its primary goal is to engage readers and contributors from various regions around the world in the exchange of knowledge about the etiology, pathogenesis, diagnosis, and treatment of infectious diseases, both in outpatient and inpatient settings. The journal covers a wide range of topics, including: Etiology: The study of the causes of infectious diseases. Pathogenesis: The process by which an infectious agent causes disease. Diagnosis: The methods and techniques used to identify infectious diseases. Treatment: The medical interventions and strategies employed to treat infectious diseases. Public Health: Issues of local, regional, or international significance related to infectious diseases, including prevention, control, and management strategies. Hospital Epidemiology: The study of the spread of infectious diseases within healthcare settings and the measures to prevent nosocomial infections. In addition to these, Infection also includes a specialized "Images" section, which focuses on high-quality visual content, such as images, photographs, and microscopic slides, accompanied by brief abstracts. This section is designed to highlight the clinical and diagnostic value of visual aids in the field of infectious diseases, as many conditions present with characteristic clinical signs that can be diagnosed through inspection, and imaging and microscopy are crucial for accurate diagnosis. The journal's comprehensive approach ensures that it remains a valuable resource for healthcare professionals and researchers in the field of infectious diseases.