ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2019
Dissemination of Tuberculosis Clinical Evidence - An Application of Network Analysis to Publicly Available Resources.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Development of a Study Protocol for Evaluation of a Novel Measure to Incorporate Information Freshness into Network Analysis of Online Resources for COVID-19.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Effective dissemination of Tuberculosis (TB) clinical evidence to healthcare providers is essential to address this pandemic. To identify, organize, and aggregate online TB information resources, we analyzed the websites of four CDC-funded TB Centers of Excellence (COE), identified the hosted resources, examined the outward linkages, and collected the external resources. We obtained 154 primary resources from TB COEs and 1521 linkages to external resources. We leveraged a network analysis approach to construct resource networks at the individual resource and parent site levels. We computed the degree of connectivity and PageRank for each node in the networks. Based on these analyses, we successfully identified important TB information hosting sites beyond the four TB COEs and individual TB resources widely cited. The initial results indicate that it is promising to use network analysis approaches to identify online clinical information resources. The generalizability of this approach needs to be examined in future research.
Indexed as
Identifiers
32308811PMC7153153What 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.