dc.contributor.author | Oral, Elif A. | |
dc.contributor.author | Meral, Rasimcan | |
dc.contributor.author | Ryan, Benjamin J. | |
dc.contributor.author | Malandrino, Noemi | |
dc.contributor.author | Jalal, Abdelwahab | |
dc.contributor.author | Neidert, Adam H. | |
dc.contributor.author | Muniyappa, Ranganath | |
dc.contributor.author | Akinci, Baris | |
dc.contributor.author | Horowitz, Jeffrey F. | |
dc.contributor.author | Brown, Rebecca J. | |
dc.date.accessioned | 2021-03-05T13:55:29Z | |
dc.date.available | 2021-03-05T13:55:29Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Meral R., Ryan B. J. , Malandrino N., Jalal A., Neidert A. H. , Muniyappa R., Akinci B., Horowitz J. F. , Brown R. J. , Oral E. A. , ""Fat Shadows" From DXA for the Qualitative Assessment of Lipodystrophy: When a Picture Is Worth a Thousand Numbers", DIABETES CARE, cilt.41, ss.2255-2258, 2018 | |
dc.identifier.issn | 0149-5992 | |
dc.identifier.other | av_b492efaf-334f-496d-be07-8713bafd2cc2 | |
dc.identifier.other | vv_1032021 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12627/120248 | |
dc.identifier.uri | https://doi.org/10.2337/dc18-0978 | |
dc.description.abstract | OBJECTIVELipodystrophy syndromes are a heterogeneous group of disorders associated with selective absence of fat. Currently, the diagnosis is established only clinically.RESEARCH DESIGN AND METHODSWe developed a new method from DXA scans called a fat shadow, which is a color-coded representation highlighting only the fat tissue. We conducted a blinded retrospective validation study to assess its usefulness for the diagnosis of lipodystrophy syndromes.RESULTSWe evaluated the fat shadows from 16 patients (11 female and 5 male) with generalized lipodystrophy (GL), 57 (50 female and 7 male) with familial partial lipodystrophy (FPLD), 2 (1 female and 1 male) with acquired partial lipodystrophy, and 126 (90 female and 36 male) control subjects. FPLD was differentiated from control subjects with 85% sensitivity and 96% specificity (95% CIs 72-93 and 91-99, respectively). GL was differentiated from nonobese control subjects with 100% sensitivity and specificity (95% CIs 79-100 and 92-100, respectively).CONCLUSIONSFat shadows provided sufficient qualitative information to infer clinical phenotype and differentiate these patients from appropriate control subjects. We propose that this method could be used to support the diagnosis. | |
dc.language.iso | eng | |
dc.subject | Klinik Tıp | |
dc.subject | Tıp | |
dc.subject | Sağlık Bilimleri | |
dc.subject | Dahili Tıp Bilimleri | |
dc.subject | İç Hastalıkları | |
dc.subject | Endokrinoloji ve Metabolizma Hastalıkları | |
dc.subject | ENDOKRİNOLOJİ VE METABOLİZMA | |
dc.subject | Klinik Tıp (MED) | |
dc.title | "Fat Shadows" From DXA for the Qualitative Assessment of Lipodystrophy: When a Picture Is Worth a Thousand Numbers | |
dc.type | Makale | |
dc.relation.journal | DIABETES CARE | |
dc.contributor.department | University of Michigan System , , | |
dc.identifier.volume | 41 | |
dc.identifier.issue | 10 | |
dc.identifier.startpage | 2255 | |
dc.identifier.endpage | 2258 | |
dc.contributor.firstauthorID | 2357308 | |