The new International Classification of Diseases—11th revision (ICD-11) succeeds ICD-10. In the three decades since ICD-10 was released, demands for detailed information on the clinical history of a morbid patient have increased. ICD-11 has now implemen
(2) The polygenic dissection of the trait body mass index (BMI) has led to the detection of more than 700 loci, which account for 5% of the BMI variance. Whereas the elucidation of loci for eating disorders is just beginning, genetic correlations between mental disorders and somatic and ...
There are a number of very important departures from the ICD-10, which are consistent with recent literature and follow, in spirit, the changes from the DSM-IV to the DSM-5 [5]. First, the ICD-10 does not have a specific grouping for neurodevelopmental disorders and uses slightly different...
This supports the improved clinical utility of both schemes over the former DSM-IV [22] and ICD-10 [2] where a larger proportion of people did not meet full criteria [6,37]. In the present study, a greater number of participants received a main diagnosis of BN or BED with the ...
For example, ICD-11 provides novel concepts that allow multiple purposes for disease classification. Moreover, the code scheme that contains stem and extension codes in the ICD-11 is also new to users of ICD-10. Many challenges in the transition from ICD-10 to ICD-11 exist, such as ...
Introduction: Although research suggests that exercise benefits mental health, psychiatric disorders have been acknowledged in the ultra-endurance-athlete population. At present, the mental-health consequences of high-volume training associated with ultr
nutrients Article An Investigation of the Clinical Utility of the Proposed ICD-11 and DSM-5 Diagnostic Schemes for Eating Disorders Characterized by Recurrent Binge Eating in People with a High BMI Marly Amorim Palavras 1,2 , Phillipa Hay 2 and Angélica Claudino 1,* 1 Eating Disorders Program...
models for important clinical predictors as well as for covariates that were significant in univariable analysis. For the Cox regression analysis, our basic model (model 1) started with several clinical predictors based on prior research and univariable Cox regression results: age, sex, BMI, ...