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Background: Pleural infection is a common clinical problem. Its successful treatment depends on rapid diagnosis and early initiation of antibiotics. The measurement of soluble triggering receptor expressed in myeloid cells-1 (sTREM-1) level in pleural effusions has proven to be a valuable diagnostic tool for differentiating bacterial effusions from effusions of other etiologies. Herein, we performed a meta-analysis to assess the accuracy of pleural fluid sTREM-1 in the diagnosis of bacterial infection.
Methods: We searched Web of Knowledge and Medline from 1990 through March 2011 for studies reporting diagnostic accuracy data regarding the use of sTREM-1 in the diagnosis of bacterial pleural effusions. Pooled sensitivity and specificity and summary measures of accuracy and Q* were calculated.
Results: Overall, the sensitivity of sTREM-1was 78% (95% CI: 72%-83%); the specificity was 84% (95% CI: 80%-87%); the positive likelihood ratio was 6.0 (95% CI: 3.3-10.7); and the negative likelihood ratio was 0.22 (95% CI: 0.12-0.40). The area under the SROC curve for sTREM-1 was 0.92. Statistical heterogeneity and inconsistency were found for sensitivity (p = 0.015, χ2 = 15.73, I2 = 61.9%), specificity (p = 0.000, χ2 = 29.90, I2 = 79.9%), positive likelihood ratio (p = 0.000, χ2 = 33.09, I2 = 81.9%), negative likelihood ratio (p = 0.008, χ2 = 17.25, I2 = 65.2%), and diagnostic odds ratio (p = 0.000, χ2 = 28.49, I2 = 78.9%). A meta-regression analysis performed showed that the Quality Assessment of Diagnostic Accuracy Studies score (p = 0.3245; RDOR, 4.34; 95% CI, 0.11 to 164.01), the Standards for Reporting of Diagnostic Accuracy score (p = 0.3331; RDOR, 1.70; 95% CI, 0.44 to 6.52), lack of blinding (p = 0.7439; RDOR, 0.60; 95% CI, 0.01 to 33.80), and whether the studies were prospective or retrospective studies (p = 0.2068; RDOR, 7.44; 95% CI, 0.18 to 301.17) did not affect the test accuracy. A funnel plot for publication bias suggested a remarkable trend of publication bias.
Conclusions: Our findings suggest that sTREM-1 has a good diagnostic accuracy and may provide a useful adjunctive tool for the diagnosis of bacterial pleural effusions. However, further studies are needed in order to identify any differences in the diagnostic performance of sTREM-1 of parapneumonic effusions and empyemas.
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http://dx.doi.org/10.1186/1471-2334-11-280 | DOI Listing |
J Environ Pathol Toxicol Oncol
January 2025
Department of General Surgery, Xiangshan First People's Hospital Medical and Health Group, Ningbo 315700, China.
Breast cancer (BC) is one of the main causes of cancer-related death in women. The purpose of this study was to evaluate the expression of miR-605-5p in BC and its diagnostic and prognostic value. BC patients and healthy individuals who met the study criteria were included.
View Article and Find Full Text PDFNeural Netw
September 2025
Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China. Electronic address:
Automatic segmentation of retinal vessels from retinography images is crucial for timely clinical diagnosis. However, the high cost and specialized expertise required for annotating medical images often result in limited labeled datasets, which constrains the full potential of deep learning methods. Recent advances in self-supervised pretraining using unlabeled data have shown significant benefits for downstream tasks.
View Article and Find Full Text PDFJMIR Med Inform
September 2025
Department of Hepatobiliary and Vascular Surgery, First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Background: Primary liver cancer, particularly hepatocellular carcinoma (HCC), poses significant clinical challenges due to late-stage diagnosis, tumor heterogeneity, and rapidly evolving therapeutic strategies. While systematic reviews and meta-analyses are essential for updating clinical guidelines, their labor-intensive nature limits timely evidence synthesis.
Objective: This study proposes an automated literature screening workflow powered by large language models (LLMs) to accelerate evidence synthesis for HCC treatment guidelines.
Neurology
October 2025
Alzheimer's Disease and Other Cognitive Disorders Unit, Department of Neurology, Hospital Clínic de Barcelona, Fundació Recerca Clínic Barcelona-IDIBAPS, Spain.
Background And Objectives: α-Synuclein seed amplification assays (αSAAs) can improve the diagnosis of synucleinopathies and detect α-synuclein (αSyn) copathology in vivo in clinical practice. We aimed to evaluate the diagnostic performance of αSAA for detecting αSyn in CSF for diagnosing dementia with Lewy bodies (DLB) in a clinical cohort of cognitively impaired individuals. We explored how the coexistence of Alzheimer disease (AD) and αSyn pathology influences biomarker levels and clinical profiles.
View Article and Find Full Text PDFPLoS One
September 2025
Korea University College of Medicine, Seoul, Republic of Korea.
Purpose: To develop and validate a deep learning-based model for automated evaluation of mammography phantom images, with the goal of improving inter-radiologist agreement and enhancing the efficiency of quality control within South Korea's national accreditation system.
Materials And Methods: A total of 5,917 mammography phantom images were collected from the Korea Institute for Accreditation of Medical Imaging (KIAMI). After preprocessing, 5,813 images (98.