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Alzheimers disease typically progresses in stages, which have been defined by the presence of disease-specific biomarkers: amyloid (A), tau (T) and neurodegeneration (N). This progression of biomarkers has been condensed into the ATN framework, in which each of the biomarkers can be either positive (+) or negative (-). Over the past decades, genome-wide association studies have implicated ∼90 different loci involved with the development of late-onset Alzheimers disease. Here, we investigate whether genetic risk for Alzheimers disease contributes equally to the progression in different disease stages or whether it exhibits a stage-dependent effect. Amyloid (A) and tau (T) status was defined using a combination of available PET and CSF biomarkers in the Alzheimers Disease Neuroimaging Initiative cohort. In 312 participants with biomarker-confirmed A-T- status, we used Cox proportional hazards models to estimate the contribution of APOE and polygenic risk scores (beyond APOE) to convert to A+T- status (65 conversions). Furthermore, we repeated the analysis in 290 participants with A+T- status and investigated the genetic contribution to conversion to A+T+ (45 conversions). Both survival analyses were adjusted for age, sex and years of education. For progression from A-T- to A+T-, APOE-e4 burden showed a significant effect [hazard ratio (HR) = 2.88; 95% confidence interval (CI): 1.70-4.89; P < 0.001], whereas polygenic risk did not (HR = 1.09; 95% CI: 0.84-1.42; P = 0.53). Conversely, for the transition from A+T- to A+T+, the contribution of APOE-e4 burden was reduced (HR = 1.62; 95% CI: 1.05-2.51; P = 0.031), whereas the polygenic risk showed an increased contribution (HR = 1.73; 95% CI: 1.27-2.36; P < 0.001). The marginal APOE effect was driven by e4 homozygotes (HR = 2.58; 95% CI: 1.05-6.35; P = 0.039) as opposed to e4 heterozygotes (HR = 1.74; 95% CI: 0.87-3.49; P = 0.12). The genetic risk for late-onset Alzheimers disease unfolds in a disease stage-dependent fashion. A better understanding of the interplay between disease stage and genetic risk can lead to a more mechanistic understanding of the transition between ATN stages and a better understanding of the molecular processes leading to Alzheimers disease, in addition to opening therapeutic windows for targeted interventions.

To better understand the pathological and phenotypic heterogeneity of progressive supranuclear palsy and the links between the two, we applied a novel unsupervised machine learning algorithm (Subtype and Stage Inference) to the largest MRI data set to date of people with clinically diagnosed progressive supranuclear palsy (including progressive supranuclear palsy-Richardson and variant progressive supranuclear palsy syndromes). Our cohort is comprised of 426 progressive supranuclear palsy cases, of which 367 had at least one follow-up scan, and 290 controls. Of the progressive supranuclear palsy cases, 357 were clinically diagnosed with progressive supranuclear palsy-Richardson, 52 with a progressive supranuclear palsy-cortical variant (progressive supranuclear palsy-frontal, progressive supranuclear palsy-speech/language, or progressive supranuclear palsy-corticobasal), and 17 with a progressive supranuclear palsy-subcortical variant (progressive supranuclear palsy-parkinsonism or progressive supranuclear palsy-progressive gait freezing). Subtype and Stage Inference was applied to volumetric MRI features extracted from baseline structural (T1-weighted) MRI scans and then used to subtype and stage follow-up scans. The subtypes and stages at follow-up were used to validate the longitudinal consistency of subtype and stage assignments. We further compared the clinical phenotypes of each subtype to gain insight into the relationship between progressive supranuclear palsy pathology, atrophy patterns, and clinical presentation. The data supported two subtypes, each with a distinct progression of atrophy: a 'subcortical' subtype, in which early atrophy was most prominent in the brainstem, ventral diencephalon, superior cerebellar peduncles, and the dentate nucleus, and a 'cortical' subtype, in which there was early atrophy in the frontal lobes and the insula alongside brainstem atrophy. There was a strong association between clinical diagnosis and the Subtype and Stage Inference subtype with 82% of progressive supranuclear palsy-subcortical cases and 81% of progressive supranuclear palsy-Richardson cases assigned to the subcortical subtype and 82% of progressive supranuclear palsy-cortical cases assigned to the cortical subtype. The increasing stage was associated with worsening clinical scores, whilst the 'subcortical' subtype was associated with worse clinical severity scores compared to the 'cortical subtype' (progressive supranuclear palsy rating scale and Unified Parkinson's Disease Rating Scale). Validation experiments showed that subtype assignment was longitudinally stable (95% of scans were assigned to the same subtype at follow-up) and individual staging was longitudinally consistent with 90% remaining at the same stage or progressing to a later stage at follow-up. In summary, we applied Subtype and Stage Inference to structural MRI data and empirically identified two distinct subtypes of spatiotemporal atrophy in progressive supranuclear palsy. These image-based subtypes were differentially enriched for progressive supranuclear palsy clinical syndromes and showed different clinical characteristics. Being able to accurately subtype and stage progressive supranuclear palsy patients at baseline has important implications for screening patients on entry to clinical trials, as well as tracking disease progression.

Alzheimer's disease (AD) is characterized by the spread of tau pathology throughout the cerebral cortex. This spreading pattern was thought to be fairly consistent across individuals, although recent work has demonstrated substantial variability in the population with AD. Using tau-positron emission tomography scans from 1,612 individuals, we identified 4 distinct spatiotemporal trajectories of tau pathology, ranging in prevalence from 18 to 33%. We replicated previously described limbic-predominant and medial temporal lobe-sparing patterns, while also discovering posterior and lateral temporal patterns resembling atypical clinical variants of AD. These 'subtypes' were stable during longitudinal follow-up and were replicated in a separate sample using a different radiotracer. The subtypes presented with distinct demographic and cognitive profiles and differing longitudinal outcomes. Additionally, network diffusion models implied that pathology originates and spreads through distinct corticolimbic networks in the different subtypes. Together, our results suggest that variation in tau pathology is common and systematic, perhaps warranting a re-examination of the notion of 'typical AD' and a revisiting of tau pathological staging.

Rationale: The decades-long progression of chronic obstructive pulmonary disease (COPD) renders identifying different trajectories of disease progression challenging.Objectives: To identify subtypes of patients with COPD with distinct longitudinal progression patterns using a novel machine-learning tool called "Subtype and Stage Inference" (SuStaIn) and to evaluate the utility of SuStaIn for patient stratification in COPD.Methods: We applied SuStaIn to cross-sectional computed tomography imaging markers in 3,698 Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1-4 patients and 3,479 controls from the COPDGene (COPD Genetic Epidemiology) study to identify subtypes of patients with COPD. We confirmed the identified subtypes and progression patterns using ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) data. We assessed the utility of SuStaIn for patient stratification by comparing SuStaIn subtypes and stages at baseline with longitudinal follow-up data.Measurements and Main Results: We identified two trajectories of disease progression in COPD: a "Tissue→Airway" subtype (n = 2,354, 70.4%), in which small airway dysfunction and emphysema precede large airway wall abnormalities, and an "Airway→Tissue" subtype (n = 988, 29.6%), in which large airway wall abnormalities precede emphysema and small airway dysfunction. Subtypes were reproducible in ECLIPSE. Baseline stage in both subtypes correlated with future FEV1/FVC decline (r = -0.16 [P

Posterior cortical atrophy is a clinico-radiological syndrome characterized by progressive decline in visual processing and atrophy of posterior brain regions. With the majority of cases attributable to Alzheimer's disease and recent evidence for genetic risk factors specifically related to posterior cortical atrophy, the syndrome can provide important insights into selective vulnerability and phenotypic diversity. The present study describes the first major longitudinal investigation of posterior cortical atrophy disease progression. Three hundred and sixty-one individuals (117 posterior cortical atrophy, 106 typical Alzheimer's disease, 138 controls) fulfilling consensus criteria for posterior cortical atrophy-pure and typical Alzheimer's disease were recruited from three centres in the UK, Spain and USA. Participants underwent up to six annual assessments involving MRI scans and neuropsychological testing. We constructed longitudinal trajectories of regional brain volumes within posterior cortical atrophy and typical Alzheimer's disease using differential equation models. We compared and contrasted the order in which regional brain volumes become abnormal within posterior cortical atrophy and typical Alzheimer's disease using event-based models. We also examined trajectories of cognitive decline and the order in which different cognitive tests show abnormality using the same models. Temporally aligned trajectories for eight regions of interest revealed distinct (P < 0.002) patterns of progression in posterior cortical atrophy and typical Alzheimer's disease. Patients with posterior cortical atrophy showed early occipital and parietal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion leading to tissue loss of comparable extent later. Hippocampal, entorhinal and frontal regions underwent a lower rate of change and never approached the extent of posterior cortical involvement. Patients with typical Alzheimer's disease showed early hippocampal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion. Cognitive models showed tests sensitive to visuospatial dysfunction declined earlier in posterior cortical atrophy than typical Alzheimer's disease whilst tests sensitive to working memory impairment declined earlier in typical Alzheimer's disease than posterior cortical atrophy. These findings indicate that posterior cortical atrophy and typical Alzheimer's disease have distinct sites of onset and different profiles of spatial and temporal progression. The ordering of disease events both motivates investigation of biological factors underpinning phenotypic heterogeneity, and informs the selection of measures for clinical trials in posterior cortical atrophy.

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique-Subtype and Stage Inference (SuStaIn)-able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer's disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 × 10-4) or temporal stage (p = 3.96 × 10-5). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine.

The uptake of human papilloma virus (HPV) and other adolescent vaccinations in special schools for young people with disability is significantly lower than in mainstream settings. This study explored the factors believed to influence parental decision making regarding vaccine uptake for students with intellectual disability and/or on the autism spectrum attending special schools in New South Wales, Australia, from the perspective of all stakeholders involved in the program. Focus groups and interviews were conducted with 40 participants, including parents, school staff, and immunisation providers. The thematic analysis identified two themes: (1) appreciating diverse parental attitudes towards vaccination and (2) educating parents and managing vaccination questions and concerns. While most parents were described as pro-vaccination, others were anti-vaccination or vaccination-hesitant, articulating a marked protectiveness regarding their child's health. Reasons for vaccine hesitancy included beliefs that vaccines cause autism, concerns that the vaccination may be traumatic for the child, vaccination fatigue following COVID-19, and assumptions that children with disability will not be sexually active. Special school staff regarded the vaccination information pack as inadequate for families, and nurses described limited educational impact resulting from minimal direct communication with parents. More effective communication strategies are needed to address vaccine hesitancy among parents with children with disability. [ABSTRACT FROM AUTHOR]

Background and Hypothesis Given the heterogeneity and possible disease progression in schizophrenia, identifying the neurobiological subtypes and progression patterns in each patient may lead to novel biomarkers. Here, we adopted data-driven machine-learning techniques to identify the progression patterns of brain morphological changes in schizophrenia and investigate the association with treatment resistance. Study Design In this cross-sectional multicenter study, we included 177 patients with schizophrenia, characterized by treatment response or resistance, with 3D T1-weighted magnetic resonance imaging. Cortical thickness and subcortical volumes calculated by FreeSurfer were converted into z scores using 73 healthy controls data. The Subtype and Stage Inference (SuStaIn) algorithm was used for unsupervised machine-learning analysis. Study Results SuStaIn identified 3 different subtypes: (1) subcortical volume reduction (SC) type (73 patients), in which volume reduction of subcortical structures occurs first and moderate cortical thinning follows, (2) globus pallidus hypertrophy and cortical thinning (GP-CX) type (42 patients), in which globus pallidus hypertrophy initially occurs followed by progressive cortical thinning, and (3) cortical thinning (pure CX) type (39 patients), in which thinning of the insular and lateral temporal lobe cortices primarily happens. The remaining 23 patients were assigned to baseline stage of progression (no change). SuStaIn also found 84 stages of progression, and treatment-resistant schizophrenia showed significantly more progressed stages than treatment-responsive cases (P  = .001). The GP-CX type presented earlier stages than the pure CX type (P  = .009). Conclusions The brain morphological progressions in schizophrenia can be classified into 3 subtypes, and treatment resistance was associated with more progressed stages, which may suggest a novel biomarker. [ABSTRACT FROM AUTHOR]

There is growing evidence that children are vulnerable to poor psychological outcomes following exposure to a range of potentially traumatic events. Teachers are in a unique and well-placed position to provide vital support to children following potentially traumatic events and to also provide a vital role in helping to identify children who may be experiencing ongoing psychosocial difficulties. We present a review of mental health trauma resources available for use in educational settings within Australia and New Zealand, with a primary focus on post-disaster resources. We describe the design, development, and dissemination of our resources and training package, Childhood Trauma Reactions: A Guide for Educators from Preschool to Year 12, and present data on how these resources were received. Trauma-informed practices within the school and classroom will enable better outcomes in the immediate post-trauma environment and beyond for all children. Our model focuses on: (1) increasing awareness and understanding of children's post-trauma reactions, (2) exploring effective strategies for teachers within the classroom, and (3) developing policy and procedures for the identification and referral of children who may be at risk. More funding is required to help distribute training and resources and to make mental health following trauma a higher priority.

Background Antimicrobial resistance (AMR) in uropathogens has been increasing in Australia. Many nations observed heightened AMR during the coronavirus disease 2019 (COVID-19) pandemic, but it is not known how this may vary across clinical settings and in nations with lower infection rates. Methods We investigated the uropathogen composition and corresponding antibiotic resistance of 775 559 Australian isolates from the community, hospitals, and aged care facilities before (2016–2019) and during (2020–2022) the COVID-19 pandemic. A mathematical model was developed to predict the likelihood of resistance to currently recommended antibiotics for treating urinary tract infections (UTIs). Results Among uropathogens originating from the community, hospitals, and aged care facilities, Escherichia coli accounted for 71.4%, 57.6%, and 65.2%, respectively. During the COVID-19 pandemic period, there was an increase in UTIs caused by E coli across all settings. Uropathogens from aged care and hospitals frequently showed higher resistance to antibiotics compared to those isolated from the community. Interestingly, AMR among uropathogens showed a declining trend during the COVID-19 pandemic. Based on the resistance patterns of the past 3 years, our modeling predicted that 30%, 42.6%, and 38.8% of UTIs in the community, hospitals, and aged care facilities, respectively, would exhibit resistance to trimethoprim treatment as empirical therapy. In contrast, resistance to nitrofurantoin was predicted to be 14.6%, 26%, and 24.1% from these 3 respective settings. Conclusions Empirical therapy of UTIs in Australia with trimethoprim requires evaluation due to high rates of resistance observed across clinical settings. [ABSTRACT FROM AUTHOR]

Amyloid-β is thought to facilitate the spread of tau throughout the neocortex in Alzheimer's disease, though how this occurs is not well understood. This is because of the spatial discordance between amyloid-β, which accumulates in the neocortex, and tau, which accumulates in the medial temporal lobe during ageing. There is evidence that in some cases amyloid-β-independent tau spreads beyond the medial temporal lobe where it may interact with neocortical amyloid-β. This suggests that there may be multiple distinct spatiotemporal subtypes of Alzheimer's-related protein aggregation, with potentially different demographic and genetic risk profiles. We investigated this hypothesis, applying data-driven disease progression subtyping models to post-mortem neuropathology and in vivo PET-based measures from two large observational studies: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Religious Orders Study and Rush Memory and Aging Project (ROSMAP). We consistently identified 'amyloid-first' and 'tau-first' subtypes using cross-sectional information from both studies. In the amyloid-first subtype, extensive neocortical amyloid-β precedes the spread of tau beyond the medial temporal lobe, while in the tau-first subtype, mild tau accumulates in medial temporal and neocortical areas prior to interacting with amyloid-β. As expected, we found a higher prevalence of the amyloid-first subtype among apolipoprotein E (APOE) ε4 allele carriers while the tau-first subtype was more common among APOE ε4 non-carriers. Within tau-first APOE ε4 carriers, we found an increased rate of amyloid-β accumulation (via longitudinal amyloid PET), suggesting that this rare group may belong within the Alzheimer's disease continuum. We also found that tau-first APOE ε4 carriers had several fewer years of education than other groups, suggesting a role for modifiable risk factors in facilitating amyloid-β-independent tau. Tau-first APOE ε4 non-carriers, in contrast, recapitulated many of the features of primary age-related tauopathy. The rate of longitudinal amyloid-β and tau accumulation (both measured via PET) within this group did not differ from normal ageing, supporting the distinction of primary age-related tauopathy from Alzheimer's disease. We also found reduced longitudinal subtype consistency within tau-first APOE ε4 non-carriers, suggesting additional heterogeneity within this group. Our findings support the idea that amyloid-β and tau may begin as independent processes in spatially disconnected regions, with widespread neocortical tau resulting from the local interaction of amyloid-β and tau. The site of this interaction may be subtype-dependent: medial temporal lobe in amyloid-first, neocortex in tau-first. These insights into the dynamics of amyloid-β and tau may inform research and clinical trials that target these pathologies. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI)-based tools are widely employed, but their use for diagnosis and prognosis of neurological disorders is still evolving. Here we analyse a cross-sectional multicentre structural MRI dataset of 696 people with epilepsy and 118 control subjects. We use an innovative machine-learning algorithm, Subtype and Stage Inference, to develop a novel data-driven disease taxonomy, whereby epilepsy subtypes correspond to distinct patterns of spatiotemporal progression of brain atrophy.In a discovery cohort of 814 individuals, we identify two subtypes common to focal and idiopathic generalized epilepsies, characterized by progression of grey matter atrophy driven by the cortex or the basal ganglia. A third subtype, only detected in focal epilepsies, was characterized by hippocampal atrophy. We corroborate external validity via an independent cohort of 254 people and confirm that the basal ganglia subtype is associated with the most severe epilepsy.Our findings suggest fundamental processes underlying the progression of epilepsy-related brain atrophy. We deliver a novel MRI- and AI-guided epilepsy taxonomy, which could be used for individualized prognostics and targeted therapeutics. [ABSTRACT FROM AUTHOR]

Background: a‐synuclein aggregation is a pathologic hallmark of several Lewy body disorders with differing symptoms. This symptom heterogeneity may be due to varying underlying disease trajectories. Here, we use a data‐driven approach to identify and characterize distinct spatial‐temporal progression patterns of α‐synuclein deposition. Method: The Subtype and Stage Inference (SuStaIn) model evaluates the optimal grouping of individuals into subtypes with distinct orderings of events/stages. We applied Ordinal SuStaIn to post‐mortem Lewy‐type α‐synuclein (LTS) density scores measured in 10 regions (including olfactory bulb and tract [OBT], limbic, brainstem, and cortical regions) of 814 subjects from the Sun Health Research Institute Brain Donation Program (Table‐1). The optimal SuStaIn model was selected according to the Cross‐Validation Information Criteria. We selected 781 subjects with stage>0 (nexcluded = 13) and subtype probability>50% (nexcluded = 20) to assess differences in subtypes. Hierarchical multinomial logistic regressions were performed to compare subtypes on (1) age at death, sex, APOE‐e4 copies, and post‐mortem interval; (2) total amyloid plaque load; and (3) total tau tangle load. In a subset of individuals (n = 355), we additionally compared subtypes on MMSE scores and the motor section of the Unified Parkinson Disease Rating Scale (UPDRS). All models were adjusted for SuStaIn stage and significant predictors of preceding models. Result: SuStaIn identified three subtypes with distinct LTS trajectories, which we termed "OBT/Limbic‐first", "OBT/Brainstem‐first", and "OBT‐sparing/Brainstem‐first" based on the first regions to show deposition (Figure‐1). The majority of individuals were assigned to OBT/Limbic‐first (N = 475,60.8%), followed by OBT/Brainstem‐first (N = 165,21.1%), and OBT‐sparing/Brainstem‐first (N = 141,18.1%) subtypes (Table‐1). We observed a higher frequency of homozygous APOE‐e4 carriers and amyloid and tau burden in the OBT/Limbic‐first subtype compared to the OBT/Brainstem‐first (ßAPOE‐e4 = 0.82±0.40, pAPOE‐e4 =.042; ßamyloid= 0.08±0.42, pamyloid<.001; ßtau= 0.17±0.03, ptau<.001) and OBT‐sparing/Brainstem‐first (ßAPOE‐e4 = 0.98±0.48, pAPOE‐e4 =.042; ßamyloid= 0.14±0.27, pamyloid<.001; ßtau= 0.18±0.03, ptau<.001) subtypes. In addition, the OBT/Brainstem‐first subtype showed a higher amyloid burden (ß = 0.06±0.02, p =.012) and higher MMSE (ß = 0.08±0.04, p = 0.030) compared to the OBT‐sparing/Brainstem‐first (Table‐1, Figure‐2). Conclusion: In this large post‐mortem SuStaIn study, we identified three subtypes of α‐synuclein deposition, possibly reflecting different epicenters and spreading trajectories of misfolded α‐synuclein, where OBT/Limbic‐first was associated with Alzheimer's co‐pathology. Follow‐up work will study how these subtypes differ in clinical diagnosis and symptomatology. [ABSTRACT FROM AUTHOR]

Accidental injuries represent the most common type of traumatic event to which a youth is likely to be exposed. While the majority of youth who experience an accidental injury will recover spontaneously, a significant proportion will go on to develop Post-Traumatic Stress Disorder (PTSD). And yet, there is little published treatment outcome research in this area. This review focuses on two key issues within the child PTSD literature--namely the role of parents in treatment and the timing of intervention. The issue of parental involvement in the treatment of child PTSD is a question that is increasingly being recognized as important. In addition, the need to find a balance between providing early intervention to at risk youth while avoiding providing treatment to those youth who will recover spontaneously has yet to be addressed. This paper outlines the rationale for and the development of a trauma-focused CBT protocol with separate parent and child programs, for use with children and adolescents experiencing PTSD following an accidental injury. The protocol is embedded within an indicated intervention framework, allowing for the early identification of youth at risk within a medical setting. Two case studies are presented in order to illustrate key issues raised in the review, implementation of the interventions, and the challenges involved.

TAR DNA-binding protein-43 (TDP-43) accumulation is the primary pathology underlying several neurodegenerative diseases. Charting the progression and heterogeneity of TDP-43 accumulation is necessary to better characterize TDP-43 proteinopathies, but current TDP-43 staging systems are heuristic and assume each syndrome is homogeneous. Here, we use data-driven disease progression modelling to derive a fine-grained empirical staging system for the classification and differentiation of frontotemporal lobar degeneration due to TDP-43 (FTLD-TDP, n = 126), amyotrophic lateral sclerosis (ALS, n = 141) and limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) with and without Alzheimer's disease (n = 304). The data-driven staging of ALS and FTLD-TDP complement and extend previously described human-defined staging schema for ALS and behavioural variant frontotemporal dementia. In LATE-NC individuals, progression along data-driven stages was positively associated with age, but negatively associated with age in individuals with FTLD-TDP. Using only regional TDP-43 severity, our data driven model distinguished individuals diagnosed with ALS, FTLD-TDP or LATE-NC with a cross-validated accuracy of 85.9%, with misclassifications associated with mixed pathological diagnosis, age and genetic mutations. Adding age and SuStaIn stage to this model increased accuracy to 92.3%. Our model differentiates LATE-NC from FTLD-TDP, though some overlap was observed between late-stage LATE-NC and early-stage FTLD-TDP. We further tested for the presence of subtypes with distinct regional TDP-43 progression patterns within each diagnostic group, identifying two distinct cortical-predominant and brainstem-predominant subtypes within FTLD-TDP and a further two subcortical-predominant and corticolimbic-predominant subtypes within ALS. The FTLD-TDP subtypes exhibited differing proportions of TDP-43 type, while there was a trend for age differing between ALS subtypes. Interestingly, a negative relationship between age and SuStaIn stage was seen in the brainstem/subcortical-predominant subtype of each proteinopathy. No subtypes were observed for the LATE-NC group, despite aggregating individuals with and without Alzheimer's disease and a larger sample size for this group. Overall, we provide an empirical pathological TDP-43 staging system for ALS, FTLD-TDP and LATE-NC, which yielded accurate classification. We further demonstrate that there is substantial heterogeneity amongst ALS and FTLD-TDP progression patterns that warrants further investigation in larger cross-cohort studies. [ABSTRACT FROM AUTHOR]

Background: Young children and their caregivers have faced an increased risk of developing mental health difficulties during the coronavirus disease 2019 pandemic. However, very little is still known about the mental health of children younger than 6 years. Existing research suggests that families with caregiver/s who are healthcare workers may be at increased risk. The primary purpose of the paper is to report on the mental health difficulties experienced by young children and their caregivers in Turkey and to investigate if mental health outcomes are worse for young children and caregivers who are healthcare workers in comparison to non-healthcare workers during the first year of the coronavirus disease 2019 pandemic. Methods: An online survey was completed by 158 caregivers of children aged 1-5 years during December 2020 in Turkey. Caregivers reported on pandemic related experiences, child and parent mental health. Results: Up to 30% of caregivers reported their child was experiencing moderate to severe anxiety, depressive symptoms, and sleep disturbances. Between 36.2% and 39.2% of caregivers reported moderate to extremely severe levels of depression, anxiety, and/or stress symptoms. Multivariate analysis of covariance analyses found no significant differences between the healthcare worker and non-healthcare worker groups for child (F(4,131) = 1.037, P > .05) or parent mental health outcomes (F(3,141) = 0.712, P > .05). Conclusion: Our study showed that one-third of children and their caregivers experienced mental health problems during the coronavirus disease 2019 pandemic unrelated to the caregiver's occupation in the health sector. It is important that all families with young children have access to mental health support during disruptive events. [ABSTRACT FROM AUTHOR]

Background: Infants, toddlers and preschoolers are the highest risk group for burn injury. However, to date this population has been largely neglected. This study examined the prevalence, onset, comorbidity and recovery patterns of posttrauma reactions in young children with burns. Methods: Parents of 130 unintentionally burned children (1-6 years) participated in the study. The Diagnostic Infant Preschool Assessment was conducted with parents at 1 and 6 months postinjury. Results: The majority of children were resilient. However, 35% were diagnosed with at least one psychological disorder, there was a high rate of comorbidity with posttraumatic stress disorder, and 8% of children did not experience recovery in distress levels over the course of 6 months. Conclusions: These outcomes are likely to have serious repercussions for a young child's medical and psychosocial recovery as well as their normal developmental trajectories. It is recommended that screening, prevention and early intervention resources are incorporated into paediatric health care settings to optimise children's psychological adjustment following burn injury.

Infants, toddlers and preschoolers are a high risk group for exposure to trauma. Young children are also vulnerable to experiencing adverse outcomes as they are undergoing a rapid developmental period, have limited coping skills and are strongly dependent on their primary caregiver to protect them physically and emotionally. However, although millions of young children experience trauma each year, this population has been largely neglected. Fortunately, over the last 2 decades there has been a growing appreciation of the magnitude of the problem with a small but expanding number of dedicated researchers and clinicians working with this population. This review examines the empirical literature on trauma in young children with regards to the following factors: (1) how trauma reactions typically manifest in young children; (2) history and diagnostic validity of posttraumatic stress disorder (PTSD) in preschoolers; (3) prevalence, comorbidity and course of trauma reactions; (4) developmental considerations; (5) risk and protective factors; and (6) treatment. The review highlights that there are unique developmental differences in the rate and manifestation of trauma symptomatology, the current "Diagnostic and Statistical Manual of Mental Disorders" (4th ed., DSM-IV-TR) PTSD criteria is not developmentally sensitive and the impact of trauma must be considered within the context of the parent-child relationship. Recommendations for future research with this population are also discussed.

This study investigated the existing diagnostic algorithms for posttraumatic stress disorder (PTSD) to determine the most developmentally sensitive and valid approach for diagnosing this disorder in preschoolers. Participants were 130 parents of unintentionally burned children (1-6 years). Diagnostic interviews were conducted with parents to assess for PTSD in their child at 1 and 6 months postinjury and the Child Behavior Checklist for 1.5-5 was also completed. The proposed algorithm for PTSD in preschool children for the "Diagnostic and Statistical Manual of Mental Disorders" (5th ed.) provided the most developmentally sensitive and valid measure of PTSD. The rate of PTSD diagnosis was 25% at 1 month and 10% at 6 months. The predictive utility of Criterion A was not demonstrated. These findings provide support for the inclusion of the proposed algorithm for PTSD in preschool children. (Contains 4 tables.)