Evidence map›Paper›PMID 38084934›Full record

ArticleThe Indian journal of medical research2023

A descriptive study of hepatitis C in people who inject drugs.

Prakrithi Shivaprakash, Vinit Patel, Darshan Shadakshari, Rahul Verma, Lekhansh Shukla, Jayant Mahadevan, Arun Kandasamy, Prabhat Kumar Chand, Vivek Benegal, Lakshmanan Sethuraman and 2 more

Abstract read
In one paragraph

Article in The Indian journal of medical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

12 authors.

Prakrithi ShivaprakashCentre for Addiction Medicine, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India.
Vinit PatelCentre for Addiction Medicine, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India.
Darshan ShadakshariCentre for Addiction Medicine, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India.
Rahul VermaCentre for Addiction Medicine, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India.
Lekhansh ShuklaCentre for Addiction Medicine, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India.
Jayant MahadevanCentre for Addiction Medicine, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India.
Arun KandasamyCentre for Addiction Medicine, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India.
Prabhat Kumar ChandCentre for Addiction Medicine, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India.
Vivek BenegalCentre for Addiction Medicine, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India.
Lakshmanan SethuramanCentre for Addiction Medicine, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India.
Priyamvada SharmaDepartment of Clinical Psychopharmacology & Neurotoxicology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India.
Pratima MurthyCentre for Addiction Medicine, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND

objectivesThe seroprevalence of the hepatitis C virus (HCV) in general population is higher than that of human immunodeficiency virus (HIV) in India. People who inject drugs (PWIDs) constitute a high-risk group for all blood-borne infections. Multiple behavioural surveillance surveys have provided a rich typology of HIV-infected PWIDs, but this information is missing for HCV infection. We describe awareness, transmission risk factors and the treatment continuum for HCV infection among PWID. We also report spatial clustering of HCV infection in PWIDs residing in Bengaluru.

methodsInformation from clinical records was collected and telephonic interviews of retrospectively identified PWIDs who received treatment at a tertiary-level addiction treatment facility between 2016 and 2021 were conducted.

resultsWe identified 391 PWIDs; 220 (56.26%) received an anti-HCV antibody test (4 th Generation HCV-Tridot). Individuals reporting unsafe injection practices were more often tested than those who did not ( χ2 =44.9, df=1, P <0.01). Almost half of the tested and more than a quarter of the whole sample (109/220, 49.9%; 109/391, 27.9%) were seropositive for HCV infection. The projected seropositivity in this group was between 27.9 per cent (best case scenario, all untested assumed negative) and 71.6 per cent (worst case scenario, all untested assumed positive). Only a minority of participants interviewed were aware of HCV (27/183, 14.7%). HCV infection and its associated risk behaviour (PWID) were clustered in certain localities (Diggle and Chetwynd Test; P =0.001) in Bengaluru in the southern district of Karnataka. INTERPRETATION

conclusionsUndetected HCV infection is common in PWIDs; awareness and treatment uptake is poor in this group. Spatial clustering of infections in a district shows transmission in close networks and provides opportunities for targeted interventions.

Indexed as

Drug UsersHepatitis CHIV InfectionsSubstance Abuse, IntravenousHepacivirusHIVHumansIndiaPrevalenceRetrospective StudiesSeroepidemiologic Studies

Identifiers

PMID38084934
PMCPMC10878480

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LicenceCC BY-NC-SA
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Registered trials

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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.