Evidence map›Paper›PMID 30046212›Full record

ArticleIranian journal of medical sciences2018

An Epidemiological Study of Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis during 2010-2015 at Shahid Faghihi Hospital, Shiraz, Iran.

Roghayeh Talebi, Nasrin Saki, Hadi Raeisi Shahraki, Seyed Hossein Owji

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In one paragraph

Article in Iranian journal of medical sciences, 2018. 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
0.3field-weighted citation impact, top 36% 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. 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

4 authors at 1 institution in 1 country.

Roghayeh TalebiStudent Research Committee, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
Nasrin SakiDepartment of Dermatology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
Hadi Raeisi ShahrakiDepartment of Biostatistics, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
Seyed Hossein OwjiStudent Research Committee, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
Shiraz University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are two ends of the spectrum of severe immunobullous state characterized by keratinocyte apoptosis. The present study aimed to draw attention to various epidemiological features of SJS and TEN diseases such as causative drugs, underlying diseases, duration of hospitalization, and types of treatment. The records of all patients with the diagnosis of SJS, TEN, and SJS/TEN overlap during 2010-2015 were retrospectively reviewed. The records belonged to patients who were admitted to the Dermatology Tertiary Referral Center of Shahid Faghihi Hospital affiliated to the Shiraz University of Medical Sciences, Shiraz, Iran. From a total of 97 patients with such skin disorders, we identified SJS in 89 (91.8 %), TEN in 5 (5.1%), and SJS/TEN overlap in 3 (3.1%) patients. The most commonly consumed drug was Lamotrigine (21.6%) and the most common drug category was anticonvulsants (46.4%). In line with many studies, especially in Iran, Lamotrigine and anticonvulsant drugs were the most common causative drug and epilepsy was the most common underlying disease. Patients with SJS/TEN overlap or TEN were treated with combination therapy, whereas SJS patients received systemic corticosteroids.

Indexed as

Drug eruptionsEpidemiologyIranStevens-Johnson syndrome

Identifiers

PMID30046212
PMCPMC6055217
OpenAlexW2889388009

What OpenQuestion holds

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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.