ReviewBeijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences2025
[Application of salivary micro-ecosystem in early prevention and control of oral and systemic diseases].
Review in Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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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Authors and funding
5 authors.
Funding
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Abstract
Saliva is an important body fluid in the oral cavity containing lots of biomarkers, whose inherent micro-ecosystem holds significant value for early diagnosis and monitoring of oral diseases. Simultaneously, saliva has particular advantages, such as ease of sampling, painless and non-invasive collection, and suitability for repeated sampling, making it highly appropriate for surveillance and follow-up of diseases. In a series of studies conducted by the research group for preventive dentistry in Peking University School and Hospital of Stomatology, we compared different segments of saliva and those samples collected
Indexed as
Identifiers
41131755PMC12549368What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.