Evidence map›Paper›PMID 26279986›Full record

ReviewWorld journal of virology2015

Insights into human immunodeficiency virus-hepatitis B virus co-infection in India.

Runu Chakravarty, Ananya Pal

Open access · diamondAbstract readReview
In one paragraph

Review in World journal of virology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact, top 98% of its field
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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
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

2 authors at 1 institution in 1 country.

Runu ChakravartyRunu Chakravarty, Ananya Pal, ICMR Virus Unit, Kolkata, ID and BG Hospital Campus, GB 4, Kolkata 700010, West Bengal, India.
Ananya PalRunu Chakravarty, Ananya Pal, ICMR Virus Unit, Kolkata, ID and BG Hospital Campus, GB 4, Kolkata 700010, West Bengal, India.
Virus Unit · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Shared routes of transmission lead to frequent human immunodeficiency virus (HIV)-hepatitis B virus (HBV) co-infection in a host which results in about 10% of HIV positive individuals to have chronic hepatitis B infection worldwide. In post-antiretroviral therapy era, liver diseases have emerged as the leading cause of morbidity and mortality in HIV-infected individuals and HBV co-infection have become the major health issue among this population particularly from the regions with endemic HBV infection. In setting of HIV-HBV co-infection, HIV significantly impacts the natural history of HBV infection, its disease profile and the treatment outcome in negative manner. Moreover, the epidemiological pattern of HBV infection and the diversity in HBV genome (genotypic and phenotypic) are also varied in HIV co-infected subjects as compared to HBV mono-infected individuals. Several reports on the abovementioned issues are available from developed parts of the world as well as from sub-Saharan African countries. In contrast, most of these research areas remained unexplored in India despite having considerable burden of HIV and HBV infections. This review discusses present knowledge from the studies on HIV-HBV co-infection in India and relevant reports from different parts of the world. Issues needed for the future research relevant to HIV-HBV co-infection in India are also highlighted here, including a call for further investigations on this field of study.

Indexed as

Genetic diversityHuman immunodeficiency virus-hepatitis B virus co-infectionIndiaLiver diseases

Identifiers

PMID26279986
PMCPMC4534816
OpenAlexW1191988346

What OpenQuestion holds

Textmetadata
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.