Attention-deficit/hyperactivity disorder (ADHD) is a common diagnosis in children and adults. Human albinism is an uncommon genetic condition associated with visual impairment that may affect behavior. To determine if there is a relationship between albinism and ADHD, the prevalence of ADHD was examined among 78 children (age range, 4-18 years) and among 44 adults (age range, 19-79 years) with ocular or oculocutaneous albinism. ADHD was diagnosed in the pediatric population using a combination of Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) criteria, Conners' Parent Rating Scale, and physician observation. Adults were diagnosed using the Utah criteria for ADHD as confirmed by physician history and interview. Seventeen children (22.7% [17 of 75]) (3 children with existing diagnoses of pervasive developmental disorder were identified but were not included in the data analysis) and 3 adults (6.8%) met the criteria for ADHD. The combined hyperactivity and impulsivity subtype of ADHD was most common, accounting for 50% of the diagnoses. Binocular best-corrected visual acuity and genetic type of albinism were not found to correlate with a diagnosis of ADHD. The prevalence of ADHD among children and adults with albinism is more frequent than that reported among the general population and is not related to binocular best-corrected visual acuity.
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http://dx.doi.org/10.1177/0883073807307078 | DOI Listing |
Eur J Obstet Gynecol Reprod Biol
January 2025
Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, University of Southern California, Los Angeles, CA, USA; Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Los Angeles General Medical Center, Los Angeles, CA, USA; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA. Electronic address:
Objective: To assess clinical and obstetric characteristics associated with pregnant patients with a diagnosis of attention-deficit hyperactivity disorder (ADHD).
Methods: This serial cross-sectional study queried the Agency of Healthcare Research and Quality's Healthcare Cost and Utilization Project National Inpatient Sample. The study population was 16,759,786 hospital deliveries from 2016 to 2020.
Eur Child Adolesc Psychiatry
January 2025
Deakin Health Economics, School of Health and Social Development, Faculty of Health, Institute for Health Transformation, Deakin University, Geelong, VIC, Australia.
Various interventions, including caregiver education, psychoeducation, teacher and clinician training and behavioral management embedded with education, are available to enhance awareness and knowledge among caregivers, teachers, and clinicians. This review synthesizes evidence on the effectiveness and cost-effectiveness of interventions to increase ADHD awareness and knowledge for caregivers, clinicians, and teachers. Peer-reviewed literature was identified through the systematic searches of six databases: MEDLINE Complete, APA PsycInfo, CINAHL Complete, ERIC, Global Health and EconLit.
View Article and Find Full Text PDFAnn Vasc Surg
January 2025
Department of Medical and Surgical Sciences, Magna Graecia University of Catanzaro, 88100, Catanzaro, Italy; Interuniversity Center of Phlebolymphology (CIFL), "Magna Graecia" University, 88100 Catanzaro, Italy. Electronic address:
Background: Arterial diseases like coronary artery disease, carotid stenosis, peripheral artery disease, and abdominal aortic aneurysm have high morbidity and mortality, making them key research areas. Their multifactorial nature complicates patient treatment and prevention. Biomarkers offer insights into the biochemical and molecular processes, while social factors also significantly impact patients' health and quality of life.
View Article and Find Full Text PDFJ Am Acad Child Adolesc Psychiatry
January 2025
Penn State College of Medicine, Hershey, Pennsylvania. Electronic address:
J Clin Exp Neuropsychol
January 2025
Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, IL, USA.
Introduction: Diagnostic evaluations for attention-deficit/hyperactivity disorder (ADHD) are becoming increasingly complicated by the number of adults who fabricate or exaggerate symptoms. Novel methods are needed to improve the assessment process required to detect these noncredible symptoms. The present study investigated whether unsupervised machine learning (ML) could serve as one such method, and detect noncredible symptom reporting in adults undergoing ADHD evaluations.
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