Evidence map›Paper›PMID 33686591›Full record

ArticleDermatology and therapy2021

Pyoderma Gangrenosum with an Underlying Leukocyte Adhesion Deficiency Type 1 (LAD-1) and Pregnancy in the Shade of COVID-19 Epidemic: A Patient and Physician Experience.

Aleksandra Opalińska, Adrian Burdacki, Konrad Kwaśniak, Katarzyna Pogoda, Jacek Tabarkiewicz, Adam Reich

Open access · goldAbstract readLetter
In one paragraph

Article in Dermatology and therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 27% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
  6. Review
  7. 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

6 authors at 1 institution in 1 country.

Aleksandra OpalińskaDepartment of Dermatology, Institute of Medical Sciences, Medical College of Rzeszow University, Rzeszów, Poland.
Adrian BurdackiDepartment of Hematology, Institute of Medical Sciences, Medical College of Rzeszow University, Rzeszów, Poland.
Konrad KwaśniakDepartment of Immunology, Institute of Medical Sciences, Medical College of Rzeszow University, Rzeszow, Poland.
Katarzyna PogodaDepartment of Immunology, Institute of Medical Sciences, Medical College of Rzeszow University, Rzeszow, Poland.
Jacek TabarkiewiczDepartment of Immunology, Institute of Medical Sciences, Medical College of Rzeszow University, Rzeszow, Poland.
Adam ReichDepartment of Dermatology, Institute of Medical Sciences, Medical College of Rzeszow University, Rzeszów, Poland. adi_medicalis@go2.pl.ORCID http://orcid.org/0000-0002-5573-1754
University of Rzeszów · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the first part of this article, the anonymous patient diagnosed with leukocyte adhesion deficiency type 1 (LAD-1) and pyoderma gangrenosum (PG) discusses her experience of her medical history and treatment in a foreign country during her pregnancy and the coronavirus disease-19 (COVID-19) pandemic. The patient's dermatologists, immunologist, and diagnostician refer to the epidemiology, genetics, diagnosis, morphologic manifestations, including skin lesions, treatment, and prognosis in LAD-1. The patient's diagnostic and therapeutic process was discussed in the last part of this paper.

Indexed as

COVID-19CyclosporineLeukocyte adhesion deficiency type 1PrednisolonePregnancyPyoderma gangrenosum

Identifiers

PMID33686591
PMCPMC7939102
OpenAlexW3133600060

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.