ArticleiScience2024
The value of single biomarkers in the diagnosis of silicosis: A meta-analysis.
Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aims to establish a scientific foundation for early detection and diagnosis of silicosis by conducting meta-analysis on the role of single biomarkers in independent diagnosis. The combined sensitivity (Sen), specificity (Spe), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic score, and diagnostic odds ratio (DOR) were 0.84 (95% confidence interval (CI): 0.77-0.90), 0.83 (95% CI: 0.78-0.88), 5.08 (95% CI: 3.92-6.59), 0.19 (95% CI: 0.13-0.27), 3.31 (95% CI: 2.88-3.74) and 27.29 (95% CI: 17.77-41.91), respectively. The area under the curve (AUC) was 0.90 (95% CI: 0.88-0.93). The Fagan plot shows a positive posterior probability of 82% and a negative posterior probability of 15%. This study establishes an academic basis for the swift identification, mitigation, and control of silicosis through scientific approaches. The assessed biomarkers offer precision and dependability in silicosis diagnosis, opening novel paths for early detection and intervention, thereby mitigating the disease burden associated with silicosis.
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Registered trials
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