Evidence map›Paper›PMID 37313426›Full record

ArticleJCEM case reports2023

A Visual Diagnosis: Lipodystrophy.

Salman Zahoor Bhat, Rebecca J Brown, Ronadip R Banerjee

Abstract readCase Reports
In one paragraph

Article in JCEM case reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Evaluating the therapeutic impact of tirzepatide in people with partial lipodystrophy.The Journal of clinical endocrinology and metabolism · 2026
    Observational
  2. Severe Insulin Resistance Syndromes: Clinical Spectrum and Management.International journal of molecular sciences · 2025
    Review
  3. Article
  4. Review
  5. 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

3 authors.

Salman Zahoor BhatDivision of Endocrinology, Diabetes, and Metabolism, John Hopkins School of Medicine, Baltimore, MD 21287, USA.ORCID https://orcid.org/0000-0003-0304-4044
Rebecca J BrownNational Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA.ORCID https://orcid.org/0000-0002-2589-7382
Ronadip R BanerjeeDivision of Endocrinology, Diabetes, and Metabolism, John Hopkins School of Medicine, Asthma & Allergy Building, Baltimore, MD 21224, USA.ORCID https://orcid.org/0000-0001-8310-251X

Funding

Molecular and Clinical Studies of Insulin ResistanceZIADK047050 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI BROWN, REBECCA · 2009 to 2025
$6.1M
6 · The paper itself

Abstract

Lipodystrophy syndromes are rare metabolic disorders characterized by local or generalized loss of adipose tissue, resulting in insulin resistance, dyslipidemia, and cosmetic disfiguration. The lipodystrophic phenotype is highly variable, with partial lipodystrophy often missed or misdiagnosed as other diseases from a lack of a proper physical examination and low physician awareness. Correct diagnosis is important for optimal treatment and follow-up strategies in these patients. The use of GLP-1 analogs has not been systematically evaluated in lipodystrophy and could be a potential precision medicine therapy. We aim to make the reader, particularly generalists or endocrinologists outside of tertiary referral centers, aware of the presentation and clinical features of partial lipodystrophy, emphasize the role of a full physical examination in diagnosis, and discuss therapeutic options, including GLP-1-based glycemic management illustrated by our clinical case.

Indexed as

adipose tissuediabetesGLP-1 analogsinsulin resistancelipodystrophyphysical exam

Identifiers

PMID37313426
PMCPMC10259177

What Socratic 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 Socratic graph.