| 1. |
- Walton, Esther, et al.
(författare)
-
Brain Structure in Acutely Underweight and Partially Weight-Restored Individuals With Anorexia Nervosa : A Coordinated Analysis by the ENIGMA Eating Disorders Working Group
- 2022
-
Ingår i: Biological Psychiatry. - : Elsevier. - 0006-3223 .- 1873-2402. ; 92:9, s. 730-738
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The pattern of structural brain abnormalities in anorexia nervosa (AN) is still not well understood. While several studies report substantial deficits in gray matter volume and cortical thickness in acutely underweight patients, others find no differences, or even increases in patients compared with healthy control subjects. Recent weight regain before scanning may explain some of this heterogeneity. To clarify the extent, magnitude, and de-pendencies of gray matter changes in AN, we conducted a prospective, coordinated meta-analysis of multicenter neuroimaging data.METHODS: We analyzed T1-weighted structural magnetic resonance imaging scans assessed with standardized methods from 685 female patients with AN and 963 female healthy control subjects across 22 sites worldwide. In addition to a case-control comparison, we conducted a 3-group analysis comparing healthy control subjects with acutely underweight AN patients (n = 466) and partially weight-restored patients in treatment (n = 251).RESULTS: In AN, reductions in cortical thickness, subcortical volumes, and, to a lesser extent, cortical surface area were sizable (Cohen's d up to 0.95), widespread, and colocalized with hub regions. Highlighting the effects of un-dernutrition, these deficits were associated with lower body mass index in the AN sample and were less pronounced in partially weight-restored patients.CONCLUSIONS: The effect sizes observed for cortical thickness deficits in acute AN are the largest of any psychiatric disorder investigated in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Consortium to date. These results confirm the importance of considering weight loss and renutrition in biomedical research on AN and underscore the importance of treatment engagement to prevent potentially long-lasting structural brain changes in this population.
|
|
| 2. |
- Haugen, Ida K., et al.
(författare)
-
Development of radiographic classification criteria for hand osteoarthritis : a methodological report (Phase 2)
- 2022
-
Ingår i: RMD Open. - : BMJ. - 2056-5933. ; 8:1
-
Tidskriftsartikel (refereegranskat)abstract
- ObjectivesIn Phase 1 of developing new hand osteoarthritis (OA) classification criteria, features associated with hand OA were identified in a population with hand complaints. Radiographic findings could better discriminate patients with hand OA and controls than clinical examination findings. The objective of Phase 2 was to achieve consensus on the features and their weights to be included in three radiographic criteria sets of overall hand OA, interphalangeal OA and thumb base OA.MethodsMultidisciplinary, international expert panels were convened. Patient vignettes were used to identify important features consistent with hand OA. A consensus-based decision analysis approach implemented using 1000minds software was applied to identify the most important features and their relative importance influencing the likelihood of symptoms being due to hand OA. Analyses were repeated for interphalangeal and thumb base OA. The reliability and validity of the proposed criteria sets were tested.ResultsThe experts agreed that the criteria sets should be applied in a population with pain, aching or stiffness in hand joint(s) not explained by another disease or acute injury. In this setting, five additional criteria were considered important: age, morning stiffness, radiographic osteophytes, radiographic joint space narrowing and concordance between symptoms and radiographic findings. The reliability and validity were very good.ConclusionRadiographic features were considered critical when determining whether a patient had symptoms due to hand OA. The consensus-based decision analysis approach in Phase 2 complemented the data-driven results from Phase 1, which will form the basis of the final classification criteria sets.
|
|
