Evidence map›Paper›PMID 34774658›Full record

ReviewJournal of the American Academy of Dermatology2022

DESCRIBE-AD: A novel classification framework for atopic dermatitis.

Raj Chovatiya, Jonathan I Silverberg

Abstract readReview
In one paragraph

Review in Journal of the American Academy of Dermatology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
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.

Raj ChovatiyaDepartment of Dermatology, Feinberg School of Medicine at Northwestern University, Chicago, Illinois.
Jonathan I SilverbergDepartment of Dermatology, The George Washington University School of Medicine and Health Sciences, Washington, DC. Electronic address: JonathanISilverberg@gmail.com.

Funding

PA-20-072: Supplement to A Chicago Center of Excellence in Learning Health Systems Research Training (ACCELERAT)K12HS026385 · AHRQ · NORTHWESTERN UNIVERSITY AT CHICAGO · PI FRANKLIN, PATRICIA D, KHO, ABEL N. · 2018 to 2022
$3.4M
AHRQ HHS K12 HS026385
6 · The paper itself

Abstract

backgroundAtopic dermatitis (AD) is a chronic, inflammatory skin disease associated with heterogeneous morphology, distribution, symptoms, severity, extent, longitudinal courses, quality of life burden, comorbidities, and treatment responses. This heterogeneity contributes to challenges in diagnosis, the characterization of disease activity, and therapeutic stratification.

objectiveTo develop a framework to standardize AD assessment.

methodsWe propose a novel framework to assess AD based on a literature review and clinical experience.

resultsDESCRIBE-AD is a framework that can effectively capture the clinical domains contributing to AD heterogeneity and includes both patient- and clinician-reported perspectives. DESCRIBE-AD includes assessments of Dermatitis morphology and phenotype, Evolution of disease, Symptom severity, Comorbid health disorders, Response to therapy, Intensity of lesions, Burden of disease, and Extent of lesions. Rather than placing the focus on any single, specific aspect of AD, DESCRIBE-AD allows for a comprehensive approach to the assessment and clinical management of AD.

conclusionsDESCRIBE-AD is a novel framework that can be used to better describe the heterogeneity of AD and guide treatment decisions.

Indexed as

Dermatitis, AtopicChronic DiseaseComorbidityHumansQuality of LifeSeverity of Illness IndexSkinatopic dermatitisburdeneczemaheterogeneityoutcomeseverity

Identifiers

PMID34774658
PMCPMC10119387

What OpenQuestion holds

Textmetadata
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.