Evidence map›Paper›PMID 23922559›Full record

ArticleHepatitis monthly2013

Lower intrafamilial transmission rate of hepatitis B in patients with hepatitis d coinfection: a data-mining approach.

Omid Pournik, Seyed Moayed Alavian, Leila Ghalichi, Bashir Hajibeigi, Amir Reza Razavi, Saeid Eslami

Abstract read
In one paragraph

Article in Hepatitis monthly, 2013. 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. Review
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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

6 authors.

Omid PournikDepartment of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, IR Iran ; Medical Informatics Research Center, Department of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, IR Iran.
Seyed Moayed Alavian
Leila Ghalichi
Bashir Hajibeigi
Amir Reza Razavi
Saeid Eslami

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe presence of an infected family member significantly increases the risk of HBV transmission, but many socio-demographic and viral characteristics of family members affect the transmission rate.

objectivesIn this study, we have used data mining techniques to investigate the impact of different variables in intrafamilial transmission of HBV infection. PATIENTS AND

methodsdemographic information, viral markers, and medical history of 330 patients with chronic hepatitis B and their offspring attending a referral center in Tehran were collected. Data-mining techniques were administered to detect patterns.

resultsThe overall transmission rate was 15.7% (5.4% and 27.3% for male and female index cases respectively). In female patients, HBe Ag positively affected the transmission rate (49% vs. 23.4%). There was a dominant change in transmission rate of female patients with negative results for Hbe Ag with HDV coinfection, where the transmission rate changed from 25% in patients with negative results for HDV Ab to 5% in those with positive results. In Hbe Ag negative male index cases, the transmission rate was 1.3% in cases with positive results for HDV Ab compared to 7% in those with negative findings. The overall transmission rate was statistically different between patients with positive and negative results for HDV Ab (P = 0.016).

conclusionsThere is a minor but consistent pattern change in the presence of HDV infection which reduces familial transmission of HBV, especially in female patients with negative results for HBe Ag.

Indexed as

Data MiningHepatitis B VirusHepatitis DMachine Learning

Identifiers

PMID23922559
PMCPMC3732666

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