Evidence map›Paper›PMID 36147124›Full record

ArticleAnnals of medicine and surgery (2012)2022

Management of drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome in a female Indonesian with pulmonary tuberculosis: A rare case report.

Aghnia Permatasari, Gatot Soegiarto

Open access · diamondAbstract readCase Reports
In one paragraph

Article in Annals of medicine and surgery (2012), 2022. 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
0.5field-weighted citation impact, top 33% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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.

Aghnia PermatasariDepartment of Internal Medicine, Faculty of Medicine, Universitas Airlangga - Dr. Soetomo General Academic, Surabaya, Indonesia.
Gatot SoegiartoDepartment of Internal Medicine, Faculty of Medicine, Universitas Airlangga - Dr. Soetomo General Academic, Surabaya, Indonesia.
Airlangga University · ID

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Anti-tuberculosis drugs (ATD) induced DRESS syndrome is rarely reported, and its diagnosis and management are very challenging. Case presentation: A 33-year-old woman presented with fever, maculopapular rashes, hypereosinophilia, and hepatic involvement, which occurred 4 weeks after a fixed-dose combination of first-line ATD containing rifampicin, isoniazid, pyrazinamide, and ethambutol. The patient's condition improved after the withdrawal of the drugs and administration of systemic steroids. Furthermore, active pulmonary tuberculosis was treated with second-line ATD containing streptomycin, levofloxacin, and ethambutol with no adverse reaction. Discussion: Early identification of the causal drug for ATD-induced DRESS syndrome is essential, and it helps to facilitate the treatment process. In some cases, the change from first-line ATD to second-line in pulmonary tuberculosis patients with the syndrome can be considered after recovery with strict follow-up. Furthermore, the administration of systemic corticosteroids for tuberculosis treatment is still debatable, but it had positive effects in this study. Conclusion: Early recognition and withdrawal of all suspected drugs are crucial in managing DRESS because the delayed diagnosis can be life-threatening. The administration of systemic steroids is effective against DRESS in pulmonary tuberculosis infection.

Indexed as

Anti-tuberculosis drugDRESSPulmonary tuberculosisSystemic steroid

Identifiers

PMID36147124
PMCPMC9486734
OpenAlexW4293563310

What OpenQuestion holds

Textmetadata
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.