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Masiran R, Ilias MNA, Yubbu P. Methylphenidate-associated chest pain in a child. Drug Ther Bull 2024; 62:108-111. [PMID: 38857950 DOI: 10.1136/dtb.2024.e255187rep] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2024]
Affiliation(s)
- Ruziana Masiran
- Department of Psychiatry, Faculty of Medicine & Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
- Department of Psychiatry, Hospital Sultan Abdul Aziz Shah, Serdang, Selangor, Malaysia
| | | | - Putri Yubbu
- Department of Psychiatry, Faculty of Medicine & Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
- Pediatric Cardiology Unit, Hospital Serdang, Serdang, Selangor, Malaysia
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Stutzman DL, Dopheide JA. Practice Pearls for Stimulant Treatment of Attention-Deficit/Hyperactivity Disorder in Youth. J Pediatr Pharmacol Ther 2024; 29:215-231. [PMID: 38863854 PMCID: PMC11163912 DOI: 10.5863/1551-6776-29.3.215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 09/04/2023] [Indexed: 06/13/2024]
Abstract
Over half of youth with attention-deficit/hyperactivity disorder (ADHD) have co-occurring psychiatric or medical conditions that present treatment challenges. Stimulants are the most effective pharmacologic treatment of ADHD for preschoolers to adults but questions about safety with co-occurring conditions frequently arise. In addition, stigma surrounding diagnosis and treatment can negatively impact care. This manuscript presents evidence-based practice pearls to guide treatment decisions for youth with ADHD and common coexisting psychiatric and medical conditions. Recommendations address specific stimulant adverse effects (i.e., anxiety, cardiac, growth, mania, psychosis) along with management strategies. Pearls were developed for the most common clinical questions, controversial topics, or therapeutic issues that may not be widely known. The goals of this manuscript are to: 1) provide a detailed resource for interprofessional teams regarding stimulant use in youth with ADHD, 2) improve therapeutic outcomes for youth with ADHD and co-occurring psychiatric and/or medical conditions through evidence-based recommendations, and 3) decrease stigma associated with stimulant use through education.
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Affiliation(s)
- Danielle L. Stutzman
- Pediatric Mental Health Institute (DLS), Children’s Hospital Colorado, Aurora, CO
- Department of Clinical Pharmacy (DLS), University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO
- Department of Child and Adolescent Psychiatry (DLS), University of Colorado School of Medicine, Aurora, CO
| | - Julie A. Dopheide
- University of Southern California Mann School of Pharmacy and Pharmaceutical Sciences and Keck School of Medicine (JAD), LAC+USC Medical Center, Los Angeles, CA
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Masiran R, Ilias MNA, Yubbu P. Methylphenidate-associated chest pain in a child. BMJ Case Rep 2023; 16:e255187. [PMID: 38011950 PMCID: PMC10685918 DOI: 10.1136/bcr-2023-255187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2023] Open
Abstract
A young child was diagnosed with autism spectrum disorder with comorbid attention-deficit/hyperactivity disorder. His hyperactivity, impulsivity and absence of awareness towards danger increased his risk of harm and hence methylphenidate was indicated. Unfortunately, he developed chest pain eight months after the treatment initiation. We then stopped the stimulant and changed his treatment to atomoxetine, after which he no longer had chest pain. In the following illustrated case, we will discuss the cardiac side effect of methylphenidate.
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Affiliation(s)
- Ruziana Masiran
- Department of Psychiatry, Faculty of Medicine & Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
- Department of Psychiatry, Hospital Sultan Abdul Aziz Shah, Serdang, Selangor, Malaysia
| | | | - Putri Yubbu
- Department of Psychiatry, Faculty of Medicine & Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
- Pediatric Cardiology Unit, Hospital Serdang, Serdang, Selangor, Malaysia
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Loh HW, Ooi CP, Oh SL, Barua PD, Tan YR, Molinari F, March S, Acharya UR, Fung DSS. Deep neural network technique for automated detection of ADHD and CD using ECG signal. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 241:107775. [PMID: 37651817 DOI: 10.1016/j.cmpb.2023.107775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 08/09/2023] [Accepted: 08/22/2023] [Indexed: 09/02/2023]
Abstract
BACKGROUND AND OBJECTIVE Attention Deficit Hyperactivity problem (ADHD) is a common neurodevelopment problem in children and adolescents that can lead to long-term challenges in life outcomes if left untreated. Also, ADHD is frequently associated with Conduct Disorder (CD), and multiple research have found similarities in clinical signs and behavioral symptoms between both diseases, making differentiation between ADHD, ADHD comorbid with CD (ADHD+CD), and CD a subjective diagnosis. Therefore, the goal of this pilot study is to create the first explainable deep learning (DL) model for objective ECG-based ADHD/CD diagnosis as having an objective biomarker may improve diagnostic accuracy. METHODS The dataset used in this study consist of ECG data collected from 45 ADHD, 62 ADHD+CD, and 16 CD patients at the Child Guidance Clinic in Singapore. The ECG data were segmented into 2 s epochs and directly used to train our 1-dimensional (1D) convolutional neural network (CNN) model. RESULTS The proposed model yielded 96.04% classification accuracy, 96.26% precision, 95.99% sensitivity, and 96.11% F1-score. The Gradient-weighted class activation mapping (Grad-CAM) function was also used to highlight the important ECG characteristics at specific time points that most impact the classification score. CONCLUSION In addition to achieving model performance results with our suggested DL method, Grad-CAM's implementation also offers vital temporal data that clinicians and other mental healthcare professionals can use to make wise medical judgments. We hope that by conducting this pilot study, we will be able to encourage larger-scale research with a larger biosignal dataset. Hence allowing biosignal-based computer-aided diagnostic (CAD) tools to be implemented in healthcare and ambulatory settings, as ECG can be easily obtained via wearable devices such as smartwatches.
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Affiliation(s)
- Hui Wen Loh
- School of Science and Technology, Singapore University of Social Sciences, Singapore
| | - Chui Ping Ooi
- School of Science and Technology, Singapore University of Social Sciences, Singapore
| | - Shu Lih Oh
- Cogninet Australia, Sydney, NSW 2010, Australia
| | - Prabal Datta Barua
- Cogninet Australia, Sydney, NSW 2010, Australia; Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia; School of Business (Information System), University of Southern Queensland, Australia; Australian International Institute of Higher Education, Sydney, NSW 2000, Australia; School of Science & Technology, University of New England, Australia; School of Biosciences, Taylor's University, Malaysia; School of Computing, SRM Institute of Science and Technology, India; School of Science and Technology, Kumamoto University, Japan; Sydney School of Education and Social work, University of Sydney, Australia
| | - Yi Ren Tan
- Developmental Psychiatry, Institute of Mental Health, Singapore
| | - Filippo Molinari
- Biolab, Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy
| | - Sonja March
- Centre for Health Research and School of Psychology and Wellbeing, University of Southern Queensland, Springfield, Australia
| | - U Rajendra Acharya
- School of Mathematics, Physics, and Computing, University of Southern Queensland, Springfield, Australia.
| | - Daniel Shuen Sheng Fung
- Developmental Psychiatry, Institute of Mental Health, Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, DUKE NUS Medical School, Yong Loo Lin School of Medicine, National University of Singapore
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Trairatvorakul P, Meinzen-Derr J, Heydarian H, Mason K, Anixt JS. Stimulant Medication Treatment in Children with Congenital Heart Disease and Attention-Deficit/Hyperactivity Disorder: Cardiovascular Outcomes. J Dev Behav Pediatr 2023; 44:e247-e254. [PMID: 37081695 DOI: 10.1097/dbp.0000000000001187] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 03/07/2023] [Indexed: 04/22/2023]
Abstract
OBJECTIVE Children with congenital heart disease (CHD) are at increased risk for attention-deficit/hyperactivity disorder (ADHD). The aim of this study was to determine whether children with CHD and ADHD clinically treated with stimulant medication were at increased risk for changes in cardiovascular parameters or death compared with CHD-matched controls. METHODS In this retrospective cohort study, patients with CHD + ADHD treated with stimulant medication (exposed group [EG]) were matched by CHD diagnosis and visit age to patients not on stimulants (nonexposed group [NEG]). Cardiovascular parameters (heart rate [HR] and systolic and diastolic blood pressure [SBP and DBP]) and electrocardiograms (ECGs) from medical records over 12 months were compared using mixed effects models. RESULTS Cardiovascular parameters for 151 children with CHD (mean age 8 ± 4 years) were evaluated (N = 46 EG and N = 105 NEG). Stimulant medication use was not associated with sudden cardiac death. HR and SBP did not significantly change over time in the EG and remained similar between groups. EG children had higher DBP compared with NEG children over time ( p = 0.001). Group × time interactions for HR, SBP, and DBP were not different between the EG and NEG. QTc was not significantly different between the EG and NEG (447 ms vs 439 ms, p = 0.23). EG children demonstrated improvement in ADHD symptoms. CONCLUSION Stimulant medication use in children with CHD was not associated with clinically significant changes in cardiovascular parameters compared with controls. Stimulants should be considered for ADHD treatment in children with CHD when prescribed with appropriate monitoring and coordination with the cardiologist.
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Affiliation(s)
- Pon Trairatvorakul
- Division of Growth and Development, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, and King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand
- Center of Excellence for Maximizing Children's Developmental Potential, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Jareen Meinzen-Derr
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH
| | - Haleh Heydarian
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH
- Division of Cardiology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH; and
| | - Karen Mason
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH
- Division of Developmental and Behavioral Pediatrics, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH
| | - Julia S Anixt
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH
- Division of Developmental and Behavioral Pediatrics, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH
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Xu X, Zhuo L, Zhang L, Peng H, Lyu Y, Sun H, Zhai Y, Luo D, Wang X, Li X, Li L, Zhang Y, Ma X, Wang Q, Li Y. Dexmedetomidine alleviates host ADHD-like behaviors by reshaping the gut microbiota and reducing gut-brain inflammation. Psychiatry Res 2023; 323:115172. [PMID: 36958092 DOI: 10.1016/j.psychres.2023.115172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 02/28/2023] [Accepted: 03/14/2023] [Indexed: 03/25/2023]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent psychiatric disorders that affects children and even continues into adulthood. Dexmedetomidine (DEX), a short-term sedative, can selectively activate the α2-adrenoceptor. Treatment with α2-adrenergic agonists in patients with ADHD is becoming increasingly common. However, the therapeutic potential of DEX for the treatment of ADHD is unknown. Here, we evaluated the effect of DEX on ADHD-like behavior in spontaneously hypertensive rats (SHRs), a widely used animal model of ADHD. DEX treatment ameliorated hyperactivity and spatial working memory deficits and normalized θ electroencephalogram (EEG) rhythms in SHRs. We also found that DEX treatment altered the gut microbiota composition and promoted the enrichment of beneficial gut bacterial genera associated with anti-inflammatory effects in SHRs. The gut pathological scores and permeability and the level of inflammation observed in the gut and brain were remarkably improved after DEX administration. Moreover, transplantation of fecal microbiota from DEX-treated SHRs produced effects that mimicked the therapeutic effects of DEX administration. Therefore, DEX is a promising treatment for ADHD that functions by reshaping the composition of the gut microbiota and reducing inflammation in the gut and brain.
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Affiliation(s)
- Xiangzhao Xu
- Department of Anesthesiology and Perioperative Medicine and Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China; Department of Anesthesiology, The People's Hospital of Nanchuan, Chongqing 408400, China
| | - Lixia Zhuo
- Department of Anesthesiology and Perioperative Medicine and Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Linjuan Zhang
- Department of Anesthesiology and Perioperative Medicine and Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Huan Peng
- Department of Anesthesiology and Perioperative Medicine and Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Yixuan Lyu
- Department of Anesthesiology and Perioperative Medicine and Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Huan Sun
- Department of Anesthesiology and Perioperative Medicine and Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Yifang Zhai
- Department of Anesthesiology and Perioperative Medicine and Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Danlei Luo
- Department of Anesthesiology and Perioperative Medicine and Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Xiaodan Wang
- Department of Anesthesiology and Perioperative Medicine and Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Xinyang Li
- Department of Anesthesiology and Perioperative Medicine and Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Liya Li
- Department of Anesthesiology and Perioperative Medicine and Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Ying Zhang
- Department of Anesthesiology and Perioperative Medicine and Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Xiancang Ma
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Qiang Wang
- Department of Anesthesiology and Perioperative Medicine and Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Yan Li
- Department of Anesthesiology and Perioperative Medicine and Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.
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