Objectives: To document changes in Axis I psychiatric disorders after bariatric surgery and examine their relationship with postsurgery weight loss.
Methods: As part of a three-site substudy of the Longitudinal Assessment of Bariatric Surgery Research Consortium, 199 patients completed the Structured Clinical Interview for DSM-IV before Roux-en-Y gastric bypass or laparoscopic adjustable gastric band. At 2 or 3 years after surgery, 165 (83%) patients completed a follow-up assessment (presurgery median body mass index = 44.8 kg/m, median age = 46 years, 92.7% white, 81.1% female). Linear-mixed modeling was used to test change in prevalence of psychiatric disorders over time, report remission and incidence, and examine associations between psychiatric disorders and weight loss.
Results: Compared with status presurgery, the prevalence of any Axis I psychiatric disorder was significantly lower at 2 and 3 years after surgery (30.2% versus 16.8% [p = .003] and 18.4% [p = .012], respectively). Adjusting for site, age, sex, race, presurgery body mass index, and surgical procedure, presurgery mood, anxiety, eating or substance use disorders (lifetime or current) were not related to weight change, nor were postsurgery mood or anxiety disorders (p for all > .05). However, having a postsurgery eating disorder was independently associated with less weight loss at 2 or 3 years (β = 6.7%, p = .035).
Conclusions: Bariatric surgery was associated with decreases in psychiatric disorders through 3 years after surgery. Postsurgical eating disorders were associated with less weight loss after surgery, adding to the literature suggesting that disordered eating after surgery is related to suboptimal weight loss.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5041300 | PMC |
http://dx.doi.org/10.1097/PSY.0000000000000277 | DOI Listing |
Int J Bipolar Disord
December 2024
Department for Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt-Goethe University, Frankfurt am Main, Germany.
Background: Attention-deficit/hyperactivity disorder (ADHD) is a common neuro-developmental disorder that often persists into adulthood. Moreover, it is frequently accompanied by bipolar disorder (BD) as well as borderline personality disorder (BPD). It is unclear whether these disorders share underlying pathomechanisms, given that all three are characterized by alterations in affective states, either long or short-term.
View Article and Find Full Text PDFSci Rep
December 2024
The Department of Mechanical Engineering and Mechatronics, Ariel University, Ariel, Israel.
Autism spectrum disorder (ASD) involves challenges in communication and social interaction, including challenges in recognizing emotions. Existing technological solutions aim to improve social behaviors in individuals with ASD by providing learning aids. This paper presents a real-time environmental translator designed to enhance social behaviors in individuals with ASD using sensory substitution.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Neurology, Union Hospital of Jilin University, Changchun, 130000, China.
Alzheimer's disease (AD) is a severe neurodegenerative disease, and the most common type of dementia, with symptoms of progressive cognitive dysfunction and behavioral impairment. Studying the pathogenesis of AD and exploring new targets for the prevention and treatment of AD is a very worthwhile challenge. Accumulating evidence has highlighted the effects of fatty acid metabolism on AD.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Pharmacology, University of the Basque Country, UPV/EHU, Sarriena S/N, 48940, Leioa, Bizkaia, Spain.
Cannabis use disorder affects up to 42% of individuals with schizophrenia, correlating with earlier onset, increased positive symptoms, and more frequent hospitalizations. This study employed an untargeted lipidomics approach to identify biomarkers in plasma samples from subjects with schizophrenia, cannabis use disorder, or both (dual diagnosis), aiming to elucidate the metabolic underpinnings of cannabis abuse and schizophrenia development. The use of liquid chromatography-high resolution mass spectrometry enabled the annotation of 119 metabolites, with the highest identification confidence level achieved for 16 compounds.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Information and Computer Science, College of Computer Science and Engineering, University of Ha'il, Ha'il, 81481, Saudi Arabia.
Alzheimer's disease (AD) is a brain disorder that causes memory loss and behavioral and thinking problems. The symptoms of Alzheimer's are similar throughout its development stages, which makes it difficult to diagnose manually. Therefore, artificial intelligence (AI) techniques address the limitations of manual diagnosis.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!