ArticleOrphanet journal of rare diseases2020
LipoDDx: a mobile application for identification of rare lipodystrophy syndromes.
Article in Orphanet journal of rare diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.
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Who cites it
8 citing papers in PubMed, 2 syntheses or guidelines pooled it, 14 citations in OpenAlex.
- Clinical Spectrum ofCells · 2023Pooled it
- Dunnigan lipodystrophy syndrome: French National Diagnosis and Care Protocol (PNDS; Protocole National de Diagnostic et de Soins).Orphanet journal of rare diseases · 2022Guideline
- Proposal of an Algorithm for the Clinical and Molecular Diagnosis of RASopathies Based on HPO Nomenclature.International journal of molecular sciences · 2026Article
- Pathways to improving the awareness, diagnosis and management of lipodystrophy in Brazil: an expert panel discussion.Diabetology & metabolic syndrome · 2025Review
- Clinical Guidance for Lipodystrophy Syndromes: From Diagnosis and Work-Up to Treatment.Current diabetes reports · 2025Review
- The Effectiveness of a Mobile National Remote Emergency System for Malignant Hyperthermia in China: Retrospective Pre-Post Implementation Study.Journal of medical Internet research · 2025Article
- The clinical approach to child and adolescent patients with lipodystrophy: a series of international case discussions.Frontiers in endocrinology · 2025Review
- Identifying congenital generalized lipodystrophy using deep learning-DEEPLIPO.Scientific reports · 2023Article
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Authors and funding
15 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLipodystrophy syndromes are a group of disorders characterized by a loss of adipose tissue once other situations of nutritional deprivation or exacerbated catabolism have been ruled out. With the exception of the HIV-associated lipodystrophy, they have a very low prevalence, which together with their large phenotypic heterogeneity makes their identification difficult, even for endocrinologists and pediatricians. This leads to significant delays in diagnosis or even to misdiagnosis. Our group has developed an algorithm that identifies the more than 40 rare lipodystrophy subtypes described to date. This algorithm has been implemented in a free mobile application, LipoDDx®. Our aim was to establish the effectiveness of LipoDDx®. Forty clinical records of patients with a diagnosis of certainty of most lipodystrophy subtypes were analyzed, including subjects without lipodystrophy. The medical records, blinded for diagnosis, were evaluated by 13 physicians, 1 biochemist and 1 dentist. Each evaluator first gave his/her results based on his/her own criteria. Then, a second diagnosis was given using LipoDDx®. The results were analysed based on a score table according to the complexity of each case and the prevalence of the disease.
resultsLipoDDx® provides a user-friendly environment, based on usually dichotomous questions or choice of clinical signs from drop-down menus. The final result provided by this app for a particular case can be a low/high probability of suffering a particular lipodystrophy subtype. Without using LipoDDx® the success rate was 17 ± 20%, while with LipoDDx® the success rate was 79 ± 20% (p < 0.01).
conclusionsLipoDDx® is a free app that enables the identification of subtypes of rare lipodystrophies, which in this small cohort has around 80% effectiveness, which will be of help to doctors who are not experts in this field. However, it will be necessary to analyze more cases in order to obtain a more accurate efficiency value.
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