Evidence map›Paper›PMID 31497747›Full record

ArticleHepatology communications2019

Twitter As a Noninvasive Bio-Marker for Trends in Liver Disease.

Ben L Da, Pallavi Surana, Samuel A Schueler, Niloofar Y Jalaly, Natasha Kamal, Sonia Taneja, Anusha Vittal, Christy L Gilman, Theo Heller, Christopher Koh

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Hepatology communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Ben L DaDigestive Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases National Institutes of Health Bethesda MD.ORCID https://orcid.org/0000-0002-7750-240X
Pallavi SuranaLiver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases National Institutes of Health Bethesda MD.
Samuel A SchuelerDigestive Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases National Institutes of Health Bethesda MD.
Niloofar Y JalalyLiver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases National Institutes of Health Bethesda MD.
Natasha KamalDigestive Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases National Institutes of Health Bethesda MD.
Sonia TanejaDigestive Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases National Institutes of Health Bethesda MD.
Anusha VittalLiver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases National Institutes of Health Bethesda MD.
Christy L GilmanLiver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases National Institutes of Health Bethesda MD.
Theo HellerLiver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases National Institutes of Health Bethesda MD.
Christopher KohLiver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases National Institutes of Health Bethesda MD.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the success of hepatitis C virus (HCV) direct-acting antiviral therapies, there has been a shift in research focus to the other major chronic liver diseases (CLDs). The use of social media, specifically Twitter, has become a popular platform for understanding public health trends and for performing health care research. To evaluate this, we studied the areas of public interest and social media trends of the following three major CLDs: hepatitis B virus (HBV), HCV, and nonalcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH). Twitter activity data from January 1, 2013, through January 1, 2019, for HBV, HCV, and NAFLD/NASH were collected using the social media analytic tool Symplur Signals (Symplur LLC) software. Content and regression analyses were performed to understand and predict Twitter activity for each of the CLDs. Over the study period, there were 810,980 tweets generating 4,452,939,516 impressions. HCV tweet activity peaked in 2015 at 243,261 tweets, followed by a decline of 52.4% from 2015 to 2016 with a subsequent plateau through 2018. Meanwhile, NAFLD/NASH and HBV tweet activity has continued to increase, with projections that these two CLDs will surpass HCV by the second half of 2023 and 2024, respectively. Treatment and Management was the most popular content category for HCV and NAFLD/NASH, while Prevention was the most popular content category for HBV.

Identifiers

PMID31497747
PMCPMC6719740

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.