Diagnosis Of Disorders Research Articles

Lifelong greenspace exposure and ADHD in Polish children: Role of physical activity and perceived neighbourhood characteristics

Previous research found a protective association between greenspace exposure and attention deficit hyperactivity disorder (ADHD) diagnosis, but previous studies did not investigate mediatory pathways involving child physical activity (PA) and environmental perceptions. Here, we examined the association between lifelong exposure to greenspace and ADHD diagnosis and potential underlying mechanisms (i.e., perceived greenspace, PA, neighbourhood social cohesion, and neighbourhood safety) in children aged 10-13 with and without ADHD. The sample (N = 689) was collected within the NeuroSmog case-control study, where children with (N = 203) and without ADHD (N = 486) were recruited from 18 towns in Southern Poland. ADHD diagnosis was ascertained according to the International Classification of Diseases 11th Revision criteria. Greenspace exposure was defined as the percentage of grass and tree cover in 500 m and 1 km buffers around lifelong residential addresses, respectively. Parents reported information about the availability of domestic garden and data on potential mediators was collected with questionnaires. Structural equation modeling was used to examine hypothesized pathways, and their interplay, linking the three greenspace measures to ADHD. We found that greenspace was indirectly related to ADHD diagnosis: tree cover was positively related to PA, and PA was subsequently negatively related to ADHD diagnosis. Tree cover and garden were both associated with higher levels of perceived greenspace, which in turn related to stronger perceptions of neighbourhood social cohesion. Our findings suggest that exposure to greenspace may lead to lower likelihood of ADHD diagnosis indirectly through PA. These findings highlight how providing children with better access to natural environments for PA may support normal neurodevelopment.

Safety and efficacy of inebilizumab for the treatment of neuromyelitis optica spectrum disorder: end-of-study results from the open-label period of the N-MOmentum trial

Inebilizumab, an anti-CD19 B-cell-depleting antibody, demonstrated safety and efficacy in neuromyelitis optica spectrum disorder in the randomised controlled period of the N-MOmentum trial. Here, end-of-study data, including the randomised controlled period and open-label extension period, are reported. In the double-blind, randomised, placebo-controlled, phase 2/3 N-MOmentum trial, adults aged 18 years and older with an neuromyelitis optica spectrum disorder diagnosis, Expanded Disability Status Scale score of 8·0 or less, and history of either at least one acute inflammatory attack requiring rescue therapy in the past year or two attacks requiring rescue therapy in the past 2 years, were recruited from 81 outpatient specialty clinics or hospitals in 24 countries. Eligible participants were randomly assigned (3:1), using a central interactive voice system or interactive web response system, and a permuted block randomisation scheme (block size of 4), to receive intravenous inebilizumab (300 mg) or identical placebo on days 1 and 15 of the randomised period, which lasted up to 197 days. Participants and all study staff were masked to treatment assignment. The primary endpoint of the randomised period of the trial was time to onset of adjudicated neuromyelitis optica spectrum disorder attack on or before day 197. Participants in the randomised controlled period who had an adjudicated attack, completed 197 days in the study, or were in the randomised controlled period when enrolment stopped, could voluntarily enter the open-label period. In the open-label period, participants either initiated inebilizumab if assigned placebo (receiving 300 mg on days 1 and 15 of the open-label period) or continued treatment if assigned inebilizumab (receiving 300 mg on day 1 and placebo on day 15, to maintain B-cell depletion and masking of the randomised controlled period). All participants subsequently received inebilizumab 300 mg every 6 months for a minimum of 2 years. The end-of-study analysis endpoints were time to adjudicated attack and annualised attack rate (assessed in all participants who received inebilizumab at any point during the randomised controlled period or open-label period [any inebilizumab population] and the aquaporin-4 [AQP4]-IgG seropositive subgroup [any inebilizumab-AQP4-IgG seropositive population]) and safety outcomes (in all participants who were exposed to inebilizumab, analysed as-treated). This study is registered with ClinicalTrials.gov, NCT02200770, and is now complete. Between Jan 6, 2015, and Sept 24, 2018, 467 individuals were screened, 231 were randomly assigned, and 230 received at least one dose of inebilizumab (n=174) or placebo (n=56). Between May 19, 2015, and Nov 8, 2018, 165 (95%) of 174 participants in the inebilizumab group and 51 (91%) of 56 in the placebo group entered the open-label period (mean age 42·9 years [SD 12·4], 197 [91%] of 216 were female, 19 [9%] were male, 115 [53%] were White, 45 [21%] were Asian, 19 [9%] were American Indian or Alaskan Native, and 19 [9%] were Black or African American). As of data cutoff for this end of study analysis (Dec 18, 2020; median exposure 1178 days [IQR 856-1538], total exposure of 730 person-years) 225 participants formed the any inebilizumab population, and 208 (92%) participants were AQP4-IgG seropositive. Overall, 63 adjudicated neuromyelitis optica spectrum disorder attacks occurred in 47 (21%) of 225 treated participants (60 attacks occurred in 44 [21%] of 208 in the AQP4-IgG seropositive subgroup); 40 (63%) of 63 attacks occurred in 34 (15%) of 225 treated participants during the first year of treatment. Of individuals who had an adjudicated attack while receiving inebilizumab, 36 (77%) of 47 were subsequently attack-free at the end of 4 years. Annualised attack rates decreased year-on-year, with end-of-study adjusted annualised attack rates being similar in the any inebilizumab-AQP4-IgG seropositive subgroup (0·097 [95% CI 0·070-0·14]) and any inebilizumab populations (0·092 [0·067-0·13]). Overall, 208 (92%) of 225 participants who received any inebilizumab had at least one treatment-emergent adverse event, the most frequent of which were urinary tract infection (59 [26%]), nasopharyngitis (47 [21%]), and arthralgia (39 [17%]). Infection rates did not increase over 4 years. Three (1%) of 225 participants in the any inebilizumab population died during the open-label period (one each due to a CNS event of unknown cause and pneumonia, respiratory insufficiency resulting from an neuromyelitis optica spectrum disorder attack and viral pneumonia related to COVID-19), all of which were deemed to be unrelated to treatment. Data from the end-of-study analysis of the N-MOmentum trial showed continued and sustained clinical benefits of long-term inebilizumab treatment in individuals with neuromyelitis optica spectrum disorder, which supports the role of inebilizumab as a CD19+ B-cell-depleting therapy in neuromyelitis optica spectrum disorder. MedImmune and Viela Bio/Horizon Therapeutics, now part of Amgen.

Clinic-Based Characterization of Adolescents and Young Adults With Migraine: Psychological Functioning, Headache Days, and Disability.

This cross-sectional observational study retrospectively examined clinical data collected from adolescents and young adults (AYAs) seeking care in a specialty headache clinic. We characterized participants' headache characteristics and psychological functioning and examined the association between self-reported anxiety and depressive symptoms and headache frequency, severity, and disability. During their clinic visit, AYAs (M age = 18.36; range = 14-32, 79.5% female) completed an intake questionnaire and reported about their headache characteristics (i.e., frequency, severity, and duration of symptoms in months), mental health history (i.e., previous diagnosis of an anxiety or depressive disorder), and utilization of emergency department (ED) services for migraine. AYAs also completed psychometrically validated screening tools for anxiety and depressive symptoms (i.e., the GAD-7 and PHQ-9). We computed descriptive statistics and examined associations among scores on psychological measures and headache characteristics, including migraine-related disability. We also tested whether individuals with clinically elevated GAD-7 and PHQ-9 scores had higher levels of disability relative to those with fewer/subclinical levels of anxiety and depressive symptoms. Participants (N = 283) reported more than 19 headache days per month on average, with more than 90% describing their average headache intensity as moderate or severe. Nearly half of AYAs reported severe headache-related disability. Approximately one-quarter of AYAs reported a previous diagnosis anxiety or depressive disorder diagnosis, and more than one-third scored above clinical cutoffs on the PHQ-9 and GAD-7. Higher scores on both psychological screening instruments were associated with greater headache frequency. More than 10% of patients endorsed current suicidal ideation; this was not related to headache-related disability. Participants reported a high degree of ED utilization for headache; these rates were unrelated to endorsement of psychological comorbidities. In this sample of AYAs, headache characteristics were generally unrelated to scores on measures on psychological functioning. However, the observed rates of clinically elevated anxiety/depressive symptoms and suicidality in this sample of AYAs underscore the importance of screening for psychological comorbidities in neurology clinics that serve this age group, irrespective of self-reported disability. Results also emphasize the need to expand access to behavioral health services for AYAs with headache disorders and the importance of incorporating a biopsychosocial perspective to the transition of health care from pediatrics to adult neurology practice.

Psychological and social interventions for the promotion of mental health in people living in low- and middle-income countries affected by humanitarian crises.

Because of wars, conflicts, persecutions, human rights violations, and humanitarian crises, about 84 million people are forcibly displaced around the world; the great majority of them live in low- and middle-income countries (LMICs). People living in humanitarian settings are affected by a constellation of stressors that threaten their mental health. Psychosocial interventions for people affected by humanitarian crises may be helpful to promote positive aspects of mental health, such as mental well-being, psychosocial functioning, coping, and quality of life. Previous reviews have focused on treatment and mixed promotion and prevention interventions. In this review, we focused on promotion of positive aspects of mental health. To assess the effects of psychosocial interventions aimed at promoting mental health versus control conditions (no intervention, intervention as usual, or waiting list) in people living in LMICs affected by humanitarian crises. We searched CENTRAL, MEDLINE, Embase, and seven other databases to January 2023. We also searched the World Health Organization's (WHO) International Clinical Trials Registry Platform and ClinicalTrials.gov to identify unpublished or ongoing studies, and checked the reference lists of relevant studies and reviews. Randomised controlled trials (RCTs) comparing psychosocial interventions versus control conditions (no intervention, intervention as usual, or waiting list) to promote positive aspects of mental health in adults and children living in LMICs affected by humanitarian crises. We excluded studies that enrolled participants based on a positive diagnosis of mental disorder (or based on a proxy of scoring above a cut-off score on a screening measure). We used standard Cochrane methods. Our primary outcomes were mental well-being, functioning, quality of life, resilience, coping, hope, and prosocial behaviour. The secondary outcome was acceptability, defined as the number of participants who dropped out of the trial for any reason. We used GRADE to assess the certainty of evidence for the outcomes of mental well-being, functioning, and prosocial behaviour. We included 13 RCTs with 7917 participants. Nine RCTs were conducted on children/adolescents, and four on adults. All included interventions were delivered to groups of participants, mainly by paraprofessionals. Paraprofessional is defined as an individual who is not a mental or behavioural health service professional, but works at the first stage of contact with people who are seeking mental health care. Four RCTs were carried out in Lebanon; two in India; and single RCTs in the Democratic Republic of the Congo, Jordan, Haiti, Bosnia and Herzegovina, the occupied Palestinian Territories (oPT), Nepal, and Tanzania. The mean study duration was 18 weeks (minimum 10, maximum 32 weeks). Trials were generally funded by grants from academic institutions or non-governmental organisations. For children and adolescents, there was no clear difference between psychosocial interventions and control conditions in improving mental well-being and prosocial behaviour at study endpoint (mental well-being: standardised mean difference (SMD) 0.06, 95% confidence interval (CI) -0.17 to 0.29; 3 RCTs, 3378 participants; very low-certainty evidence; prosocial behaviour: SMD -0.25, 95% CI -0.60 to 0.10; 5 RCTs, 1633 participants; low-certainty evidence), or at medium-term follow-up (mental well-being: mean difference (MD) -0.70, 95% CI -2.39 to 0.99; 1 RCT, 258 participants; prosocial behaviour: SMD -0.48, 95% CI -1.80 to 0.83; 2 RCT, 483 participants; both very low-certainty evidence). Interventions may improve functioning (MD -2.18, 95% CI -3.86 to -0.50; 1 RCT, 183 participants), with sustained effects at follow-up (MD -3.33, 95% CI -5.03 to -1.63; 1 RCT, 183 participants), but evidence is very uncertain as the data came from one RCT (both very low-certainty evidence). Psychosocial interventions may improve mental well-being slightly in adults at study endpoint (SMD -0.29, 95% CI -0.44 to -0.14; 3 RCTs, 674 participants; low-certainty evidence), but they may have little to no effect at follow-up, as the evidence is uncertain and future RCTs might either confirm or disprove this finding. No RCTs measured the outcomes of functioning and prosocial behaviour in adults. To date, there is scant and inconclusive randomised evidence on the potential benefits of psychological and social interventions to promote mental health in people living in LMICs affected by humanitarian crises. Confidence in the findings is hampered by the scarcity of studies included in the review, the small number of participants analysed, the risk of bias in the studies, and the substantial level of heterogeneity. Evidence on the efficacy of interventions on positive mental health outcomes is too scant to determine firm practice and policy implications. This review has identified a large gap between what is known and what still needs to be addressed in the research area of mental health promotion in humanitarian settings.

Systematic review and meta-analysis:relative age in attention-deficit/ hyperactivity disorder and autism spectrum disorder.

Youngest students in their class, with birthdates just before the school entry cut-off date, are overrepresented among children receiving an Attention-Deficit/Hyperactivity Disorder (ADHD) diagnosis or medication for this. This is known as the relative age effect. This systematic review and meta-analysis summarises the evidence on the influence of relative age on ADHD symptoms, diagnosis and medication prescribing. As no review to date has investigated the association with autism spectrum disorder (ASD) diagnosis, this is also examined. Following prospective registration with PROSPERO, we conducted a systematic review according to the PRISMA guidelines. We searched seven databases: Medline, Embase, PsycInfo, Web of Science Core Collection, ERIC, Psychology and Behavioural Sciences Collection, and Cochrane Library. Additional references were identified from manual search of retrieved reviews. We performed a meta-analysis of quantitative data. Thirty-two studies were included, thirty-one investigated ADHD and two ASD. Younger relative age was associated with ADHD diagnosis and medication, with relative risks of 1.38 (1.36-1.52 95% CI) and 1.28 (1.21-1.36 95% CI) respectively. However, risk estimates exhibited high heterogeneity. A relative age effect was observed for teacher ratings of ADHD symptoms but not for parent ratings. With regard to ASD, the youngest children in their school year were more likely to be diagnosed with ASD. This review confirms a relative age effect for ADHD diagnosis and prescribed ADHD medication and suggests that differences in teacher and parent ratings might contribute to this. Further research is needed on the possible association with ASD.

Early Play Behaviors of Infants at Elevated Likelihood for Autism Spectrum Disorder.

Although research has examined early identification of autism spectrum disorder (ASD), few studies have found behavioral markers during midinfancy associated with later ASD diagnosis. To examine infants' play behaviors and atypical positions at age 6 mo and later outcome classification among infants at elevated likelihood (EL) and typical likelihood (TL) for ASD. Atypical positions refer to movement patterns indicative of motor delays or deviations, including atypical extension and flexion, poor weight shift and rotation, hypertonicity or hypotonicity, and the presence of primitive reflex patterns. Observational cohort longitudinal design using blinded video analysis. Fifty-eight infants (41 EL infants and 17 TL infants) 6 mo of age. Infants later diagnosed with ASD needed more support to engage in play at age 6 mo compared with infants who did not receive an ASD diagnosis (U = 130, z = -2.29, p < .05, r = .31). Atypical positions at 6 mo of age were not associated with a later diagnosis of ASD. Play behaviors may be early indicators of developmental differences for infants later diagnosed with ASD. The results of this pilot study suggest the need to observe the quality of interaction with a caregiver and objects during early play, which may serve as potential early indicators of ASD. Plain-Language Summary: Few studies have found behavioral markers during midinfancy that are associated with a later diagnosis of autism spectrum disorder (ASD). The results of this study showed that infants who were later diagnosed with ASD were found to have differences in play behaviors compared to infants who were not later diagnosed with ASD. Thus, early play behaviors may be an early indicator of developmental differences for infants who are later diagnosed with ASD.

High-Order line graphs of fMRI data in major depressive disorder.

Resting-state functional magnetic resonance imaging (rs-fMRI) technology and the complex network theory can be used to elucidate the underlying mechanisms of brain diseases. The successful application of functional brain hypernetworks provides new perspectives for the diagnosis and evaluation of clinical brain diseases; however, many studies have not assessed the attribute information of hyperedges and could not retain the high-order topology of hypergraphs. In addition, the study of multi-scale and multi-layered organizational properties of the human brain can provide richer and more accurate data features for classification models of depression. This work aims to establish a more accurate classification framework for the diagnosis of major depressive disorder (MDD) using the high-order line graph algorithm. And accuracy, sensitivity, specificity, precision, F1 score are used to validate its classification performance. Based on rs-fMRI data from 38 MDD subjects and 28 controls, we constructed a human brain hypernetwork and introduced a line graph model, followed by the construction of a high-order line graph model. The topological properties under each order line graph were calculated to measure the classification performance of the model. Finally, intergroup features that showed significant differences under each order line graph model were fused, and a support vector machine classifier was constructed using multi-kernel learning. The Kolmogorov-Smirnov nonparametric permutation test was used as the feature selection method and the classification performance was measured with the leave-one-out cross-validation method. The high-order line graph achieved a better classification performance compared with other traditional hypernetworks (accuracy=92.42%, sensitivity=92.86%, specificity=92.11%, precision=89.66%, F1=91.23%). Furthermore, the brain regions found in the present study have been previously shown to be associated with the pathology of depression. This work validated the classification model based on the high-order line graph, which can better express the topological features of the hypernetwork by comprehensively considering the hyperedge information under different connection strengths, thereby significantly improving the classification accuracy of MDD. Therefore, this method has potential for use in the clinical diagnosis of MDD.

Early detection of glaucoma: feature visualization with a deep convolutional network

ABSTRACT Computer-aided diagnosis of ocular disorders like glaucoma can be effectively performed with retinal fundus images. Since the advent of machine learning and later deep learning techniques in medical image analysis, research focusing on automated and early detection of glaucoma has gained prominence. In this paper, we show how a deep Convolutional Neural Network model can be used in visualising the features related to Glaucoma that are consistent with (a subset of) those used by ophthalmologists for diagnosis. However, since the doctors do not necessarily depend entirely on these features but back them up with other important measurements such as visual field testing (HVF), any deep neural network such as CNN may not necessarily be expected to yield 100% accuracy. Further, other important parameters such as Intraocular Pressure (IOP), which may be built into a deep learning model, may not necessarily correlate well with the presence of Glaucoma. In this work, a deep CNN model has been trained and tested on a large number of high-quality fundus images, both normal and glaucomatous. We compare the results with transfer learning models such as VGG16, ResNet50, and MobileNetV2. On an average, we obtained an accuracy of 93.75% in identifying glaucoma, focusing only on the features of the fundus image.

Jon’s Heroes in Training: A Cross-Sector Collaboration Serving University and Community Stakeholders

Jon’s Heroes in Training (JHT) represents a strong cross-sector collaboration that was created and has evolved over the past five years. JHT is an after-school program where children (ages 3–22) with an autism spectrum disorder (ASD) diagnosis come to the local university to engage in high-quality physical education lessons designed and implemented by physical education teacher education (PETE) students currently taking a required Adapted Physical Education class. This article discusses (a) the process required to establish the shared mission and vision of JHT and the role of the Office of Civic Engagement (OCE); (b) the negotiated roles and responsibilities of stakeholders, including university faculty from PETE, PETE students, children with ASD and their families, and local non-profit organizations; (c) the impact of JHT on its stakeholders; and (d) lessons learned and future directions.

Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality

Sleep is essential to life. Accurate measurement and classification of sleep/wake and sleep stages is important in clinical studies for sleep disorder diagnoses and in the interpretation of data from consumer devices for monitoring physical and mental well-being. Existing non-polysomnography sleep classification techniques mainly rely on heuristic methods developed in relatively small cohorts. Thus, we aimed to establish the accuracy of wrist-worn accelerometers for sleep stage classification and subsequently describe the association between sleep duration and efficiency (proportion of total time asleep when in bed) with mortality outcomes. We developed a self-supervised deep neural network for sleep stage classification using concurrent laboratory-based polysomnography and accelerometry. After exclusion, 1448 participant nights of data were used for training. The difference between polysomnography and the model classifications on the external validation was 34.7 min (95% limits of agreement (LoA): −37.8–107.2 min) for total sleep duration, 2.6 min for REM duration (95% LoA: −68.4–73.4 min) and 32.1 min (95% LoA: −54.4–118.5 min) for NREM duration. The sleep classifier was deployed in the UK Biobank with 100,000 participants to study the association of sleep duration and sleep efficiency with all-cause mortality. Among 66,214 UK Biobank participants, 1642 mortality events were observed. Short sleepers (<6 h) had a higher risk of mortality compared to participants with normal sleep duration of 6–7.9 h, regardless of whether they had low sleep efficiency (Hazard ratios (HRs): 1.58; 95% confidence intervals (CIs): 1.19–2.11) or high sleep efficiency (HRs: 1.45; 95% CIs: 1.16–1.81). Deep-learning-based sleep classification using accelerometers has a fair to moderate agreement with polysomnography. Our findings suggest that having short overnight sleep confers mortality risk irrespective of sleep continuity.

Deep learning for temporomandibular joint arthropathies: Asystematic review and meta-analysis.

The accurate diagnosis of temporomandibular disorders continues to be a challenge, despite the existence of internationally agreed-upon diagnostic criteria. The purpose of this study is to review applications of deep learning models in the diagnosis of temporomandibular joint arthropathies. An electronic search was conducted on PubMed, Scopus, Embase, Google Scholar, IEEE, arXiv, and medRxiv up to June 2023. Studies that reported the efficacy (outcome) of prediction, object detection or classification of TMJ arthropathies by deep learning models (intervention) of human joint-based or arthrogenous TMDs (population) in comparison to reference standard (comparison) were included. To evaluate the risk of bias, included studies were critically analysed using the quality assessment of diagnostic accuracy studies (QUADAS-2). Diagnostic odds ratios (DOR) were calculated. Forrest plot and funnel plot were created using STATA 17 and MetaDiSc. Full text review was performed on 46 out of the 1056 identified studies and 21 studies met the eligibility criteria and were included in the systematic review. Four studies were graded as having a low risk of bias for all domains of QUADAS-2. The accuracy of all included studies ranged from 74% to 100%. Sensitivity ranged from 54% to 100%, specificity: 85%-100%, Dice coefficient: 85%-98%, and AUC: 77%-99%. The datasets were then pooled based on the sensitivity, specificity, and dataset size of seven studies that qualified for meta-analysis. The pooled sensitivity was 95% (85%-99%), specificity: 92% (86%-96%), and AUC: 97% (96%-98%). DORs were 232 (74-729). According to Deek's funnel plot and statistical evaluation (p =.49), publication bias was not present. Deep learning models can detect TMJ arthropathies high sensitivity and specificity. Clinicians, and especially those not specialized in orofacial pain, may benefit from this methodology for assessing TMD as it facilitates a rigorous and evidence-based framework, objective measurements, and advanced analysis techniques, ultimately enhancing diagnostic accuracy.

Incidence of hand and wrist disorders in primary care.

The incidence of different types of hand and wrist disorders in primary care is unknown since there are no specific encodings for it. To determine the overall incidence and the incidence of specific types of hand and wrist disorders in primary care. A healthcare registration database from Dutch general practice, which contains medical records of over 200 000 patients and included approximately 25% of the population of the area of Rotterdam. Patients aged ≥18 years with a new diagnosis of hand or wrist disorder from 1 January 2015 to 31 December 2019 were extracted using a search algorithm based on ICPC coding and search terms in free text. The mean incidence over the study period of a hand disorder was 5.9 per 1,000 persons-years and of a wrist disorder 0.3 per 1,000 persons-years. The incidence of trigger finger/thumb, fracture hand/finger, tendon/ligament tendinopathy, mallet finger and ligament injury hand/finger were 3 (2.69-3.15), 1 (1.03-1.33), 1 (0.98-1.28), 0.6 (0.48-0.69) and 0.1 (0.06-0.14) per 1,000 persons-years, respectively. The incidence of a wrist fracture and ligament injury were 0.2 (0.13-0.25) and 0.1 (0.04-0.12) per 1,000 persons-years, respectively. There is a large difference between the number of patients presenting to the GP with hand and wrist complaints and the number of hand and wrist diagnosis reported in the medical files. Introducing specific ICPC codes for different types of hand and wrist disorders could (potentially) lead to a more accurate registration of a diagnosis and determination of the incidence figures.

Connections between specific mental health diagnoses of schizophrenia, bipolar disorder and schizoaffective disorder and primary substance use

Purpose This study aims to use the database of consumers referred to the dual diagnosis shared care service to examine those connections. The Eastern Dual Diagnosis Service, based in Melbourne, Australia, has established a database of consumers with co-occurring mental health disorders and problematic substance use. An examination of mental health and substance-use information obtained over a two-year period in the delivery of dual diagnosis shared care to consumers of mental health services is supporting an improved understanding of substance use and the connections to specific mental health diagnoses of schizophrenia, bipolar disorder and schizoaffective disorder. Design/methodology/approach This research uses a quantitative approach to review the prevalence of primary substance use and mental health diagnoses for consumers referred to as dual diagnosis shared care. Reviewed are referrals from adult mental health community and rehabilitation teams operating within a mental health and well-being program between January 2019 and December 2020 inclusive. Findings Of the 387 clients referred to the specialist dual diagnosis shared care, methamphetamine, alcohol and cannabis are associated with 89.4% of the primary mental health diagnosis (PMHD). The most common PMHDs are schizophrenia, schizoaffective disorder and bipolar disorder. The most common PMHD and substance-use connection was schizophrenia and methamphetamine. Nicotine was reported to be used by 84% of consumers and often occurred in addition to another problematic primary substance. Originality/value Improved dual diagnosis data collection from a community-based clinical mental health service is increasing understanding of the mental health and substance-use relationship. This is now providing clarity on routes of investigation into co-occurring mental health and problematic substance-use trends and guiding improved integrated treatments within a contemporary mental health setting.

Movement Disorder: Initial Manifestation of Hereditary Hemochromatosis – A Case Report

Hereditary hemochromatosis is a condition resulting in tissue damage by pathological iron deposition due to genetic alterations. The clinical manifestations are diverse, and depend on the involvement of the affected organ. Complications such as cirrhosis, heart failure, diabetes, and arthritis are described. Iron deposition in brain tissues with neurological damage and presence of symptoms is not a usual finding. Some case series describe movement disorders as the clinical manifestation. The authors report a patient with movement disorder due to hepato-cerebral hemochromatosis, who showed clinical improvement after diagnosis and treatment. Hereditary hemochromatosis should be considered in the differential diagnosis of movement disorders in patients with signs of iron overload.

Clinical and Biomedical Applications of Lensless Holographic Microscopy

AbstractMany clinical procedures and biomedical research workflows rely on microscopy, including diagnosis of cancer, genetic disorders, autoimmune diseases, infections, and quantification of cell culture. Despite its widespread use, traditional image acquisition and review by trained microscopists is often lengthy and expensive, limited to large hospitals or laboratories, precluding use in point‐of‐care settings. In contrast, lensless or lensfree holographic microscopy (LHM) is inexpensive and widely deployable because it can achieve performance comparable to expensive and bulky objective‐based benchtop microscopes while relying on components that cost only a few hundred dollars or less. Lab‐on‐a‐chip integration is practical and enables LHM to be combined with single‐cell isolation, sample mixing, and in‐incubator imaging. Additionally, many manual tasks in conventional microscopy are instead computational in LHM, including image focusing, stitching, and classification. Furthermore, LHM offers a field of view hundreds of times greater than that of conventional microscopy without sacrificing resolution. Here, the basic LHM principles are summarized, as well as recent advances in artificial intelligence integration and enhanced resolution. How LHM is applied to the above clinical and biomedical applications is discussed in detail. Finally, emerging clinical applications, high‐impact areas for future research, and some current challenges facing widespread adoption are identified.

Sex Differences in Diagnosis and Treatment Timing of Comorbid Depression/Anxiety and Disease Subtypes in Patients With ADHD: A Database Study.

Our study examined the impact of sex, ADHD subtype, and comorbid illnesses (depression/anxiety) on the timing of diagnosis and treatment for ADHD. To analyze ADHD patients, four health databases were used to assess subtype, comorbid mood, and antidepressant or anxiolytic drug exposure. Analyses were stratified by sex and age. Standardized mean differences measured intergroup differences. Females with ADHD were identified at older ages and had higher rates of depression and anxiety diagnoses and treatments before and after their initial ADHD diagnosis. Predominantly inattentive ADHD patients were diagnosed later and more likely to receive mood disorder diagnosis and treatment than hyperactive impulsive ADHD patients. Results suggest a more complex ADHD presentation in females, potentially causing late diagnosis and delayed treatment.

Total knee arthroplasty survival rates are lower in younger men,as well as rheumatoid patients and after previous high-tibial osteotomy: A registry study.

The purpose of this study was to investigate if patient's gender significantly affected the long-term outcome of patients undergoing total knee arthroplasty (TKA) and to provide a cross-gender comparison of a large patient sample from a single regional register. The Registry of Prosthetic Orthopedic Implant of Emilia Romagna (RIPO) investigated all primary TKAs performed from July 2000 to December 2020 by collecting data of menand womenseparately. Primary bicompartmental and tricompartmental TKAs were included. The survival rates and the reasons for revision were assessed to check if any other factor could have influenced implantfailure. In total,66,032 TKAs were included and analysed, comprising 46,774 women and 19,258 men. The 15-year Kaplan-Meier survival percentage was 93.6% for womenand 92.5% formen (p = 0.001). Men exhibited a higher revision risk following primary TKA(p = 0.012), particularly when the primary diagnosis was arthritis resulting from rheumatic disorders (p = 0.018) and arthritis following high-tibial osteotomy (p = 0.024). Failure risk was also higher for men below the age of 60 years(p = 0.038). The long-term outcome in TKA showed significant differences between men and women, with a significantly lower survival rate in men at 15 years, especially when they areunder 60 years old or with a diagnosis of rheumatic disorders or arthritis following high-tibial osteotomy. It is necessary to design specific studies to have relevant data concerning gender differences in prosthetic surgery and to customise treatments to improve outcome and patient satisfaction. Level III.

Acoustically Enhanced Triboelectric Stethoscope for Ultrasensitive Cardiac Sounds Sensing and Disease Diagnosis.

Electronic stethoscope used to detect cardiac sounds that contains essential clinical information is a primary tool for diagnosis of various cardiac disorders. However, the linear electro-mechanical constitutive relation makes conventional piezoelectric sensors rather ineffective to detect low-intensity, low-frequency heart acoustic signal without the assistance of complex filtering and amplification circuits. Herein, we find that triboelectric sensor features superior advantages over piezoelectric one for micro-quantity sensing originated from the fast saturated constitutive characteristic. As a result, the triboelectric sensor shows ultrahigh sensitivity (1215mV/Pa) than the piezoelectric counterpart (21mV/Pa) in the sound pressure range of 50 - 80dB under the same testing condition. By designing a trumpet-shaped auscultatory cavity with a power function cross-section to achieve acoustic energy converging and impedance matching, triboelectric stethoscope delivers 36dB signal-to-noise ratio for human test (2.3 times of that for piezoelectric one). Further combining with machine learning, five cardiac states can be diagnosed at 97% accuracy. In general, the triboelectric sensor is distinctly unique in basic mechanism, provides a novel design concept for sensing micromechanical quantities, and presents significant potential for application in cardiac sounds sensing and disease diagnosis. This article is protected by copyright. All rights reserved.

Application of whole exome sequencing in the diagnosis of muscular disorders: a study of Taiwanese pediatric patients

BackgroundMuscular dystrophies and congenital myopathies encompass various inherited muscular disorders that present diagnostic challenges due to clinical complexity and genetic heterogeneity.MethodsThis study aimed to investigate the use of whole exome sequencing (WES) in diagnosing muscular disorders in pediatric patients in Taiwan. Out of 161 pediatric patients suspected to have genetic/inherited myopathies, 115 received a molecular diagnosis through conventional tests, single gene testing, and gene panels. The remaining 46 patients were divided into three groups: Group 1 (multiplex ligation-dependent probe amplification–negative Duchenne muscular dystrophy) with three patients (6.5%), Group 2 (various forms of muscular dystrophies) with 21 patients (45.7%), and Group 3 (congenital myopathies) with 22 patients (47.8%).ResultsWES analysis of these groups found pathogenic variants in 100.0% (3/3), 57.1% (12/21), and 68.2% (15/22) of patients in Groups 1 to 3, respectively. WES had a diagnostic yield of 65.2% (30 patients out of 46), detecting 30 pathogenic or potentially pathogenic variants across 28 genes.ConclusionWES enables the diagnosis of rare diseases with symptoms and characteristics similar to congenital myopathies and muscular dystrophies, such as muscle weakness. Consequently, this approach facilitates targeted therapy implementation and appropriate genetic counseling.

The Intergenerational Transfer of Mental Disorders: A Population-Based Multigenerational Linkage Study: Le transfert intergénérationnel des troubles mentaux : une étude sur les liens multigénérationnels basée sur la population.

The aetiology of mental disorders involves genetic and environmental factors, both reflected in family health history. We examined the intergenerational transmission of multiple mental disorders from parents and grandparents using population-based, objectively measured family histories. This population-based retrospective cohort study used administrative healthcare databases in Manitoba, Canada and included adults living in Manitoba from 1977 to 2020 with linkages to at least one parent and one grandparent. Index date was when individuals turned 18 or 1 April 1977, whichever occurred later. Mental disorder diagnoses (mood and anxiety, substance use and psychotic disorders) were identified in individuals, parents and grandparents from hospitalization and outpatient records. Cox proportional hazards regression models included sociodemographic characteristics, individual's comorbidity and mental disorder history in a grandparent, mother and father. Of 109,359 individuals with no mental disorder prior to index date, 47.1% were female, 36.3% had a mental disorder during follow-up, and 90.9% had a parent or grandparent with a history of a mental disorder prior to the index date. Both paternal and maternal history of a mental disorder increased the risk of the disorder in individuals. Psychotic disorders had the strongest association with parental history and were mostly influenced by paternal (hazards ratio [HR] 3.73, 95% confidence interval [CI] 2.99 to 4.64) compared to maternal history (HR 2.23, 95% CI, 1.89 to 2.64). Grandparent history was independently associated with the risk of all mental disorders but had the strongest influence on substance use disorders (HR 1.42, 95% CI, 1.34 to 1.50). Parental history of mental disorders was associated with an increased risk of all mental disorders. Grandparent history of mental disorders was associated with a small risk increase of the disorders above and beyond parental history influence. This three-generation study further highlights the need for family-based interventional programs in families affected by mental disorders. The Intergenerational Transfer of Mental Illnesses.