Purpose: Since the term orthorexia nervosa (ON) was coined from the Greek (ὀρθός, right and ὄρεξις, appetite) in 1997 to describe an obsession with “correct” eating, it has been used worldwide without a consistent definition. Although multiple authors have proposed diagnostic criteria, and many theoretical papers have been published, no consensus definition of ON exists, empirical primary evidence is limited, and ON is not a standardized diagnosis. These gaps prevent research to identify risk and protective factors, pathophysiology, functional consequences, and evidence-based therapeutic treatments. The aims of the current study are to categorize the common observations and presentations of ON pathology among experts in the eating disorder field, propose tentative diagnostic criteria, and consider which DSM chapter and category would be most appropriate for ON should it be included. Methods: 47 eating disorder researchers and multidisciplinary treatment specialists from 14 different countries across four continents completed a three-phase modified Delphi process, with 75% agreement determined as the threshold for a statement to be included in the final consensus document. In phase I, participants were asked via online survey to agree or disagree with 67 statements about ON in four categories: A–Definition, Clinical Aspects, Duration; B–Consequences; C–Onset; D–Exclusion Criteria, and comment on their rationale. Responses were used to modify the statements which were then provided to the same participants for phase II, a second round of feedback, again in online survey form. Responses to phase II were used to modify and improve the statements for phase III, in which statements that met the predetermined 75% of agreement threshold were provided for review and commentary by all participants. Results: 27 statements met or exceeded the consensus threshold and were compiled into proposed diagnostic criteria for ON. Conclusions: This is the first time a standardized definition of ON has been developed from a worldwide, multidisciplinary cohort of experts. It represents a summary of observations, clinical expertise, and research findings from a wide base of knowledge. It may be used as a base for diagnosis, treatment protocols, and further research to answer the open questions that remain, particularly the functional consequences of ON and how it might be prevented or identified and intervened upon in its early stages. Although the participants encompass many countries and disciplines, further research will be needed to determine if these diagnostic criteria are applicable to the experience of ON in geographic areas not represented in the current expert panel. Level of evidence: Level V: opinions of expert committees

Background: Diagnosis of schizophrenia (SCZ) is made exclusively clinically, since specific biomarkers that can predict the disease accurately remain unknown. Machine learning (ML) represents a promising approach that could support clinicians in the diagnosis of mental disorders. Objectives: A systematic review, according to the PRISMA statement, was conducted to evaluate its accuracy to distinguish SCZ patients from healthy controls. Methods: We systematically searched PubMed, Embase, MEDLINE, PsychINFO and the Cochrane Library through December 2018 using generic terms for ML techniques and SCZ without language or time restriction. Thirty-five studies were included in this review: eight of them used structural neuroimaging, twenty-six used functional neuroimaging and one both, with a minimum accuracy >60% (most of them 75–90%). Sensitivity, Specificity and accuracy were extracted from each publication or obtained directly from authors. Results: Support vector machine, the most frequent technique, if associated with other ML techniques achieved accuracy close to 100%. The prefrontal and temporal cortices appeared to be the most useful brain regions for the diagnosis of SCZ. ML analysis can efficiently detect significantly altered brain connectivity in patients with SCZ (eg, default mode network, visual network, sensorimotor network, frontoparietal network and salience network). Conclusion: The greater accuracy demonstrated by these predictive models and the new models resulting from the integration of multiple ML techniques will be increasingly decisive for early diagnosis and evaluation of the treatment response and to establish the prognosis of patients with SCZ. To achieve a real benefit for patients, the future challenge is to reach an accurate diagnosis not only through clinical evaluation but also with the aid of ML algorithms.

Dopamine impairments occur in anorexia nervosa. The aim of this study was to see whether treatment with the atypical dopamine antagonist antipsychotic olanzapine improves the disorder. Thirty anorexics, 18 restricted and 12 bingeing-purging, underwent a 3-month course of cognitive behavioral therapy, plus at random and double-blinded oral olanzapine (2.5 mg for 1 month, 5 mg for 2 months) in half and oral placebo in the other half of them. BMI, psychopathological aspects (eating disorder inventory, Hamilton Rating Scale, Buss-Durkee Rating Scale, Yale Brown Cornell for Eating Disorders Rating Scale, temperament-character inventory), and homovanillic acid blood concentrations for dopamine secretion, were monitored at baseline and then monthly during the trial. At the end of the trial BMI, total eating disorder inventory, total Yale Brown Cornell for Eating Disorders Rating Scale, Buss-Durkee Rating Scale, Hamilton Rating Scale scores and in olanzapine-treated patients the subitems of eating disorder inventory ineffectiveness and maturity fear, of Buss-Durkee Rating Scale direct aggressiveness, of temperament-characteristic inventory persistence had improved significantly. When stratified for anorexia nervosa subtype, BMI changes were significant among anorexia nervosa bingeing-purging patient, 'depression' (Hamilton Rating Scale) and 'direct aggressiveness' (Buss-Durkee Rating Scale) among anorexia nervosa bingeing-purging patients, 'persistence' (temprerament-characteristic inventory), among anorexics restricted patients, with a trend toward significance for obsessivity-compulsivity (Yale Brown Cornell for Eating Disorders Rating Scale). homovanilic acid blood levels increased significantly in the cognitive behavioral therapy+olanzapine group. No correlations were observed between homovanilic acid concentrations and psychopathological parameters. The pharmacological treatment can significantly improve specific aspects of anorexia nervosa.

To evaluate whether obese patients with a binge eating disorder (BED) have an altered metabolic and inflammatory profile related to their eating behaviors compared with non-BED obese.A total of 115 White obese patients consecutively recruited underwent biochemical, anthropometrical evaluation, and a 75-g oral glucose tolerance test. Patients answered the Binge Eating Scale and were interviewed by a psychiatrist. The patients were subsequently divided into 2 groups according to diagnosis: non-BED obese (n = 85) and BED obese (n = 30). Structural equation modeling analysis was performed to elucidate the relation between eating behaviors and metabolic and inflammatory profile.BED obese exhibited significantly higher percentages of altered eating behaviors, body mass index (P < 0.001), waist circumference (P < 0.01), fat mass (P < 0.001), and a lower lean mass (P < 0.001) when compared with non-BED obese. Binge eating disorder obese also had a worse metabolic and inflammatory profile, exhibiting significantly lower high-density lipoprotein cholesterol levels (P < 0.05), and higher levels of glycated hemoglobin (P < 0.01), uric acid (P < 0.05), erythrocyte sedimentation rate (P < 0.001), high-sensitive C-reactive protein (P < 0.01), and white blood cell counts (P < 0.01). Higher fasting insulin (P < 0.01) and higher insulin resistance (P < 0.01), assessed by homeostasis model assessment index and visceral adiposity index (P < 0.001), were observed among BED obese. All differences remained significant after adjusting for body mass index. No significant differences in fasting plasma glucose or 2-hour postchallenge plasma glucose were found. Structural equation modeling analysis confirmed the relation between the altered eating behaviors of BED and the metabolic and inflammatory profile.Binge eating disorder obese exhibited an unfavorable metabolic and inflammatory profile, which is related to their characteristic eating habits.

Several studies have investigated the cognitive profile in patients with Anorexia Nervosa (AN) and Bulimia Nervosa (BN); on the contrary few studies have evaluated it in patients with Binge Eating Disorder (BED). The purpose of this study was to compare decision making, central coherence and set-shifting between BED and AN patients. A battery of neuropsychological tests including the Iowa Gambling Task (IGT), the Rey-Osterrieth Complex Figure Test (RCFT), the Wisconsin Card Sorting Test (WCST), the Trial Making Task (TMT) and the Hayling Sentence Completion Task (HSCT) were administered in a sample of 135 women (45 AN, 45 BED, 45 Healthy Controls [HC]). Furthermore, Beck Depression Inventory (BDI) was administered to evaluate depressive symptoms. Years of education, age, Body Mass Index (BMI) and depression severity were considered as covariates in statistical analyses. BED and AN patients showed high rates of cognitive impairment compared to HC on the domains investigated; furthermore, the cognitive profile of BED patients was characterised by poorer decision making and cognitive flexibility compared to patients with AN. Cognitive performance was strongly associated with depressive symptoms. In the present sample, two different neurocognitive profiles emerged: a strong cognitive rigidity and a central coherence based on the details was predominant in patients with AN, while a lack of attention and difficulty in adapting to changes in a new situation seemed to better describe patients with BED. The knowledge of the different cognitive profiles of EDs patients may be important for the planning their psychotherapeutic intervention.