Influences of resting-state intrinsic functional brain connectivity on the antidepressant treatment response in late-life depression.

BACKGROUND: Late-life depression (LLD) is characterized by differences in resting state functional connectivity within and between intrinsic functional networks. This study examined whether clinical improvement to antidepressant medications is associated with pre-randomization functional connectivity in intrinsic brain networks. METHODS: Participants were 95 elders aged 60 years or older with major depressive disorder. After clinical assessments and baseline MRI, participants were randomized to escitalopram or placebo with a two-to-one allocation for 8 weeks. Non-remitting participants subsequently entered an 8-week trial of open-label bupropion. The main clinical outcome was depression severity measured by MADRS. Resting state functional connectivity was measured between a priori key seeds in the default mode (DMN), cognitive control, and limbic networks. RESULTS: In primary analyses of blinded data, lower post-treatment MADRS score was associated with higher resting connectivity between: (a) posterior cingulate cortex (PCC) and left medial prefrontal cortex; (b) PCC and subgenual anterior cingulate cortex (ACC); (c) right medial PFC and subgenual ACC; (d) right orbitofrontal cortex and left hippocampus. Lower post-treatment MADRS was further associated with lower connectivity between: (e) the right orbitofrontal cortex and left amygdala; and (f) left dorsolateral PFC and left dorsal ACC. Secondary analyses associated mood improvement on escitalopram with anterior DMN hub connectivity. Exploratory analyses of the bupropion open-label trial associated improvement with subgenual ACC, frontal, and amygdala connectivity. CONCLUSIONS: Response to antidepressants in LLD is related to connectivity in the DMN, cognitive control and limbic networks. Future work should focus on clinical markers of network connectivity informing prognosis. REGISTRATION: ClinicalTrials.gov NCT02332291.

Structural MRI-Based Measures of Accelerated Brain Aging do not Moderate the Acute Antidepressant Response in Late-Life Depression.

OBJECTIVE: Late-life depression (LLD) is characterized by accelerated biological aging. Accelerated brain aging, estimated from structural magnetic resonance imaging (sMRI) data by a machine learning algorithm, is associated with LLD diagnosis, poorer cognitive performance, and disability. We hypothesized that accelerated brain aging moderates the antidepressant response. DESIGN AND INTERVENTIONS: Following MRI, participants entered an 8-week randomized, controlled trial of escitalopram. Nonremitting participants then entered an open-label 8-week trial of bupropion. PARTICIPANTS: Ninety-five individuals with LLD. MEASUREMENTS: A machine learning algorithm estimated each participant's brain age from sMRI data. This was used to calculate the brain-age gap (BAG), or how estimated age differed from chronological age. Secondary sMRI measures of aging pathology included white matter hyperintensity (WMH) volumes and hippocampal volumes. Mixed models examined the relationship between sMRI measures and change in depression severity. Initial analyses tested for a moderating effect of MRI measures on change in depression severity with escitalopram. Subsequent analyses tested for the effect of MRI measures on change in depression severity over time across trials. RESULTS: In the blinded initial phase, BAG was not significantly associated with a differential response to escitalopram over time. BAG was also not associated with a change in depression severity over time across both arms in the blinded phase or in the subsequent open-label bupropion phase. We similarly did not observe effects of WMH volume or hippocampal volume on change in depression severity over time. CONCLUSION: sMRI markers of accelerated brain aging were not associated with treatment response in this sequential antidepressant trial.

Using Novel Implementation Tools for Evidence-based Intervention Delivery (UNITED) across public service systems for three evidence-based autism interventions in under-resourced communities: study protocol.

BACKGROUND: There are a growing number of evidence-based interventions (EBIs) for autistic individuals, but few are successfully implemented with fidelity in under-resourced communities and with families from traditionally disenfranchised groups. Implementation science offers tools to increase EBI use in communities, but most implementation strategies are designed specific to a single EBI. It is not feasible to develop a new implementation strategy each time a new EBI is introduced in the community. Therefore, to test the effectiveness and generalizability of implementation strategies we are developing and testing a multifaceted implementation strategy with three EBIs concurrently. The goal of this protocol paper is to describe the randomized field trial of an implementation strategy for use across autism EBIs, diverse settings and participants, with the goal of increasing rapid uptake of effective practices to reach our most vulnerable children. METHODS: We developed a multifaceted implementation strategy called Using Novel Implementation Tools for Evidence-based intervention Delivery (UNITED) to facilitate the implementation and sustainment of three EBIs in under-resourced settings. We will compare fidelity to, and effectiveness of, each intervention [Mind the Gap (MTG), Remaking Recess (RR), Self-Determined Learning Model of Instruction (SDLMI)] with and without UNITED in a randomized field trial. Randomization will be stratified using a minimization allocation method. We will train community practitioners using remote delivery of modules specific to the intervention, and active coaching via Zoom for at least 6 sessions and up to 12 as dictated by each EBI. Our primary outcome is fidelity to each EBI, and our secondary outcome is at the child or family level (family empowerment for MTG, child peer social engagement for RR, and adolescent self-determination for SDLMI, respectively). We will measure progress through the implementation phases using the Stages of Implementation Completion and cost-effectiveness of UNITED. DISCUSSION: The results of this study will provide rigorous data on the effectiveness and generalizability of one relatively light-touch implementation strategy in increasing use of autism EBIs and associated outcomes in diverse under resourced public service settings for underrepresented autistic youth. TRIAL REGISTRATION: Mind the Gap: Clinicaltrials.gov Identifier:  NCT04972825 (Date registered July 22, 2021); Remaking Recess: Clinicaltrials.gov Identifier:  NCT04972838 (Date registered July 22, 2021); Self-Determined Learning Model of Instruction: Clinicaltrials.gov Identifier:  NCT04972851 (Date registered July 22, 2021).

Integrating the BIDS Neuroimaging Data Format and Workflow Optimization for Large-Scale Medical Image Analysis.

A robust medical image computing infrastructure must host massive multimodal archives, perform extensive analysis pipelines, and execute scalable job management. An emerging data format standard, the Brain Imaging Data Structure (BIDS), introduces complexities for interfacing with XNAT archives. Moreover, workflow integration is combinatorically problematic when matching large amount of processing to large datasets. Historically, workflow engines have been focused on refining workflows themselves instead of actual job generation. However, such an approach is incompatible with data centric architecture that hosts heterogeneous medical image computing. Distributed automation for XNAT toolkit (DAX) provides large-scale image storage and analysis pipelines with an optimized job management tool. Herein, we describe developments for DAX that allows for integration of XNAT and BIDS standards. We also improve DAX's efficiencies of diverse containerized workflows in a high-performance computing (HPC) environment. Briefly, we integrate YAML configuration processor scripts to abstract workflow data inputs, data outputs, commands, and job attributes. Finally, we propose an online database-driven mechanism for DAX to efficiently identify the most recent updated sessions, thereby improving job building efficiency on large projects. We refer the proposed overall DAX development in this work as DAX-1 (DAX version 1). To validate the effectiveness of the new features, we verified (1) the efficiency of converting XNAT data to BIDS format and the correctness of the conversion using a collection of BIDS standard containerized neuroimaging workflows, (2) how YAML-based processor simplified configuration setup via a sequence of application pipelines, and (3) the productivity of DAX-1 on generating actual HPC processing jobs compared with earlier DAX baseline method. The empirical results show that (1) DAX-1 converting XNAT data to BIDS has similar speed as accessing XNAT data only; (2) YAML can integrate to the DAX-1 with shallow learning curve for users, and (3) DAX-1 reduced the job/assessor generation latency by finding recent modified sessions. Herein, we present approaches for efficiently integrating XNAT and modern image formats with a scalable workflow engine for the large-scale dataset access and processing.

Exploring Growth in Expressive Communication of Infants and Toddlers With Autism Spectrum Disorder.

One of the earliest indicators of autism spectrum disorder (ASD) is delay in language and social communication. Despite consensus on the benefits of earlier diagnosis and intervention, our understanding of the language growth of children with ASD during the first years of life remains limited. Therefore, this study compared communication growth patterns of infants and toddlers with ASD to growth benchmarks of a standardized language assessment. We conducted a retrospective analysis of growth on the Early Communication Indicator (ECI) of 23 infants and toddlers who received an ASD diagnosis in the future. At 42 months of age, children with ASD had significantly lower rates of gestures, single words, and multiple words, but significantly higher rates of nonword vocalizations. Children with ASD had significantly slower growth of single and multiple words, but their rate of vocalization growth was significantly greater than benchmark. Although more research is needed with larger samples, because the ECI was designed for practitioners to monitor children's response to intervention over time, these findings show promise for the ECI's use as a progress monitoring measure for young children with ASD. Limitations and the need for future research are discussed.

PreQual: An automated pipeline for integrated preprocessing and quality assurance of diffusion weighted MRI images.

PURPOSE: Diffusion weighted MRI imaging (DWI) is often subject to low signal-to-noise ratios (SNRs) and artifacts. Recent work has produced software tools that can correct individual problems, but these tools have not been combined with each other and with quality assurance (QA). A single integrated pipeline is proposed to perform DWI preprocessing with a spectrum of tools and produce an intuitive QA document. METHODS: The proposed pipeline, built around the FSL, MRTrix3, and ANTs software packages, performs DWI denoising; inter-scan intensity normalization; susceptibility-, eddy current-, and motion-induced artifact correction; and slice-wise signal drop-out imputation. To perform QA on the raw and preprocessed data and each preprocessing operation, the pipeline documents qualitative visualizations, quantitative plots, gradient verifications, and tensor goodness-of-fit and fractional anisotropy analyses. RESULTS: Raw DWI data were preprocessed and quality checked with the proposed pipeline and demonstrated improved SNRs; physiologic intensity ratios; corrected susceptibility-, eddy current-, and motion-induced artifacts; imputed signal-lost slices; and improved tensor fits. The pipeline identified incorrect gradient configurations and file-type conversion errors and was shown to be effective on externally available datasets. CONCLUSIONS: The proposed pipeline is a single integrated pipeline that combines established diffusion preprocessing tools from major MRI-focused software packages with intuitive QA.

Preliminary Evidence That Cortical Amyloid Burden Predicts Poor Response to Antidepressant Medication Treatment in Cognitively Intact Individuals With Late-Life Depression.

OBJECTIVE: Amyloid accumulation, the pathological hallmark of Alzheimer's disease, may predispose some older adults to depression and cognitive decline. Deposition of amyloid also occurs prior to the development of cognitive decline. It is unclear whether amyloid influences antidepressant outcomes in cognitively intact depressed elders. DESIGN: A pharmacoimaging trial utilizing florbetapir (18F) PET scanning followed by 2 sequential 8-week antidepressant medication trials. PARTICIPANTS: Twenty-seven depressed elders who were cognitively intact on screening. MEASUREMENTS AND INTERVENTIONS: After screening, diagnostic testing, assessment of depression severity and neuropsychological assessment, participants completed florbetapir (18F) PET scanning. They were then randomized to receive escitalopram or placebo for 8 weeks in a double-blinded two-to-one allocation rate. Individuals who did not respond to initial treatment transitioned to a second open-label trial of bupropion for another 8 weeks. RESULTS: Compared with 22 amyloid-negative participants, 5 amyloid-positive participants exhibited significantly less change in depression severity and a lower likelihood of remission. In the initial blinded trial, 4 of 5 amyloid-positive participants were nonremitters (80%), while only 18% (4 of 22) of amyloid-negative participants did not remit (p = 0.017; Fisher's Exact test). In separate models adjusting for key covariates, both positive amyloid status (t = 3.07, 21 df, p = 0.003) and higher cortical amyloid binding by standard uptake value ratio (t = 2.62, 21 df, p = 0.010) were associated with less improvement in depression severity. Similar findings were observed when examining change in depression status across both antidepressant trials. CONCLUSIONS: In this preliminary study, amyloid status predicted poor antidepressant response to sequential antidepressant treatment. Alternative treatment approaches may be needed for amyloid-positive depressed elders.

Double-wavelet transform for multi-subject resting state functional magnetic resonance imaging data.

Conventional regions of interest (ROIs)-level resting state fMRI (functional magnetic resonance imaging) response analyses do not rigorously model the underlying spatial correlation within each ROI. This can result in misleading inference. Moreover, they tend to estimate the temporal covariance matrix with the assumption of stationary time series, which may not always be valid. To overcome these limitations, we propose a double-wavelet approach that simplifies temporal and spatial covariance structure because wavelet coefficients are approximately uncorrelated under mild regularity conditions. This property allows us to analyze much larger dimensions of spatial and temporal resting-state fMRI data with reasonable computational burden. Another advantage of our double-wavelet approach is that it does not require the stationarity assumption. Simulation studies show that our method reduced false positive and false negative rates by properly taking into account spatial and temporal correlations in data. We also demonstrate advantages of our method by using resting-state fMRI data to study the difference in resting-state functional connectivity between healthy subjects and patients with major depressive disorder.

Description of a Mass Poisoning in a Rural District in Mozambique: The First Documented Bongkrekic Acid Poisoning in Africa.

Background: On 9 January 2015, in a rural town in Mozambique, >230 persons became sick and 75 died of an illness linked to drinking pombe, a traditional alcoholic beverage. Methods: An investigation was conducted to identify case patients and determine the cause of the outbreak. A case patient was defined as any resident of Chitima who developed any new or unexplained neurologic, gastrointestinal, or cardiovascular symptom from 9 January at 6:00 am through 12 January at 11:59 pm. We conducted medical record reviews, healthcare worker and community surveys, anthropologic and toxicologic investigations of local medicinal plants and commercial pesticides, and laboratory testing of the suspect and control pombe. Results: We identified 234 case patients; 75 (32%) died and 159 recovered. Overall, 61% of case patients were female (n = 142), and ages ranged from 1 to 87 years (median, 30 years). Signs and symptoms included abdominal pain, diarrhea, vomiting, and generalized malaise. Death was preceded by psychomotor agitation and abnormal posturing. The median interval from pombe consumption to symptom onset was 16 hours. Toxic levels of bongkrekic acid (BA) were detected in the suspect pombe but not the control pombe. Burkholderia gladioli pathovar cocovenenans, the bacteria that produces BA, was detected in the flour used to make the pombe. Conclusions: We report for the first time an outbreak of a highly lethal illness linked to BA, a deadly food-borne toxin in Africa. Given that no previous outbreaks have been recognized outside Asia, our investigation suggests that BA might be an unrecognized cause of toxic outbreaks globally.

Naturalistic Language Recordings Reveal "Hypervocal" Infants at High Familial Risk for Autism.

Children's early language environments are related to later development. Little is known about this association in siblings of children with autism spectrum disorder (ASD), who often experience language delays or have ASD. Fifty-nine 9-month-old infants at high or low familial risk for ASD contributed full-day in-home language recordings. High-risk infants produced more vocalizations than low-risk peers; conversational turns and adult words did not differ by group. Vocalization differences were driven by a subgroup of "hypervocal" infants. Despite more vocalizations overall, these infants engaged in less social babbling during a standardized clinic assessment, and they experienced fewer conversational turns relative to their rate of vocalizations. Two ways in which these individual and environmental differences may relate to subsequent development are discussed.

Early intensive behavioral intervention (EIBI) for young children with autism spectrum disorders (ASD).

BACKGROUND: The rising prevalence of autism spectrum disorders (ASD) increases the need for evidence-based behavioral treatments to lessen the impact of symptoms on children's functioning. At present, there are no curative or psychopharmacological therapies to effectively treat all symptoms of the disorders. Early intensive behavioral intervention (EIBI) is a treatment based on the principles of applied behavior analysis. Delivered for multiple years at an intensity of 20 to 40 hours per week, it is one of the more well-established treatments for ASD. This is an update of a Cochrane review last published in 2012. OBJECTIVES: To systematically review the evidence for the effectiveness of EIBI in increasing functional behaviors and skills, decreasing autism severity, and improving intelligence and communication skills for young children with ASD. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, 12 additional electronic databases and two trials registers in August 2017. We also checked references and contacted study authors to identify additional studies. SELECTION CRITERIA: Randomized control trials (RCTs), quasi-RCTs, and controlled clinical trials (CCTs) in which EIBI was compared to a no-treatment or treatment-as-usual control condition. Participants must have been less than six years of age at treatment onset and assigned to their study condition prior to commencing treatment. DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by Cochrane.We synthesized the results of the five studies using a random-effects model of meta-analysis, with a mean difference (MD) effect size for outcomes assessed on identical scales, and a standardized mean difference (SMD) effect size (Hedges' g) with small sample correction for outcomes measured on different scales. We rated the quality of the evidence using the GRADE approach. MAIN RESULTS: We included five studies (one RCT and four CCTs) with a total of 219 children: 116 children in the EIBI groups and 103 children in the generic, special education services groups. The age of the children ranged between 30.2 months and 42.5 months. Three of the five studies were conducted in the USA and two in the UK, with a treatment duration of 24 months to 36 months. All studies used a treatment-as-usual comparison group.Primary outcomesThere is low quality-evidence at post-treatment that EIBI improves adaptive behaviour (MD 9.58 (assessed using Vineland Adaptive Behavior Scale (VABS) Composite; normative mean = 100, normative SD = 15), 95% confidence interval (CI) 5.57 to 13.60, P < 0.0001; 5 studies, 202 participants), and reduces autism symptom severity (SMD -0.34, 95% CI -0.79 to 0.11, P = 0.14; 2 studies, 81 participants; lower values indicate positive effects) compared to treatment as usual.No adverse effects were reported across studies.Secondary outcomesThere is low-quality evidence at post-treatment that EIBI improves IQ (MD 15.44 (assessed using standardized IQ tests; scale 0 to 100, normative SD = 15), 95% CI 9.29 to 21.59, P < 0.001; 5 studies, 202 participants); expressive (SMD 0.51, 95% CI 0.12 to 0.90, P = 0.01; 4 studies, 165 participants) and receptive (SMD 0.55, 95% CI 0.23 to 0.87, P = 0.001; 4 studies, 164 participants) language skills; and problem behaviour (SMD -0.58, 95% CI -1.24 to 0.07, P = 0.08; 2 studies, 67 participants) compared to treatment as usual. AUTHORS' CONCLUSIONS: There is weak evidence that EIBI may be an effective behavioral treatment for some children with ASD; the strength of the evidence in this review is limited because it mostly comes from small studies that are not of the optimum design. Due to the inclusion of non-randomized studies, there is a high risk of bias and we rated the overall quality of evidence as 'low' or 'very low' using the GRADE system, meaning further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate.It is important that providers of EIBI are aware of the current evidence and use clinical decision-making guidelines, such as seeking the family's input and drawing upon prior clinical experience, when making recommendations to clients on the use EIBI. Additional studies using rigorous research designs are needed to make stronger conclusions about the effects of EIBI for children with ASD.

Towards Portable Large-Scale Image Processing with High-Performance Computing.

High-throughput, large-scale medical image computing demands tight integration of high-performance computing (HPC) infrastructure for data storage, job distribution, and image processing. The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has constructed a large-scale image storage and processing infrastructure that is composed of (1) a large-scale image database using the eXtensible Neuroimaging Archive Toolkit (XNAT), (2) a content-aware job scheduling platform using the Distributed Automation for XNAT pipeline automation tool (DAX), and (3) a wide variety of encapsulated image processing pipelines called "spiders." The VUIIS CCI medical image data storage and processing infrastructure have housed and processed nearly half-million medical image volumes with Vanderbilt Advanced Computing Center for Research and Education (ACCRE), which is the HPC facility at the Vanderbilt University. The initial deployment was natively deployed (i.e., direct installations on a bare-metal server) within the ACCRE hardware and software environments, which lead to issues of portability and sustainability. First, it could be laborious to deploy the entire VUIIS CCI medical image data storage and processing infrastructure to another HPC center with varying hardware infrastructure, library availability, and software permission policies. Second, the spiders were not developed in an isolated manner, which has led to software dependency issues during system upgrades or remote software installation. To address such issues, herein, we describe recent innovations using containerization techniques with XNAT/DAX which are used to isolate the VUIIS CCI medical image data storage and processing infrastructure from the underlying hardware and software environments. The newly presented XNAT/DAX solution has the following new features: (1) multi-level portability from system level to the application level, (2) flexible and dynamic software development and expansion, and (3) scalable spider deployment compatible with HPC clusters and local workstations.

CADASIL as a Useful Medical Model and Genetic Form of Vascular Depression.

OBJECTIVE: The main magnetic resonance imaging (MRI) findings of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) are white matter hyperintensities (WMHs), lacunar infarctions, and cerebral microbleeds (CMBs). The purpose of this study was to investigate the effects of these three neuroimaging markers of CADASIL on depression to determine whether CADASIL is a useful medical model supporting the vascular depression hypothesis. METHODS: Eighty-four subjects with CADASIL, aged 34-86 years, participated in this study. They underwent comprehensive clinical evaluation, including 3T MRI and genotyping of NOTCH3. The effects of WMH, lacunar infarctions, and CMBs were analyzed by path analyses and multivariate logistic regression analyses. RESULTS: Patients with CADASIL exhibited frequencies of 17.9% for major depressive disorder (MDD) and 10.7% for minor depressive disorder. The frequency of MDD increased from 5.0% to 46.2% as WMH volume increased from first quartile to fourth quartile. WMH volume (OR: 1.03, 95% CI: 1.003-1.06) in patients with CADASIL was associated with the current depressive disorder. Path analyses demonstrated that only WMH volume was associated with the Korean version of the short form Geriatric Depression Scale score, Center for Epidemiologic Studies Depression Scale score, and 17-item Hamilton depression scale score. The effects of lacunar infarctions and CMBs on depression were not significant in path analyses and multivariate logistic regression analyses. CONCLUSIONS: This study demonstrates that WMHs are closely associated with depression in patients with CADASIL. This supports that CADASIL might be a useful medical model and genetic form of vascular depression.

Vanderbilt University Institute of Imaging Science Center for Computational Imaging XNAT: A multimodal data archive and processing environment.

The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has developed a database built on XNAT housing over a quarter of a million scans. The database provides framework for (1) rapid prototyping, (2) large scale batch processing of images and (3) scalable project management. The system uses the web-based interfaces of XNAT and REDCap to allow for graphical interaction. A python middleware layer, the Distributed Automation for XNAT (DAX) package, distributes computation across the Vanderbilt Advanced Computing Center for Research and Education high performance computing center. All software are made available in open source for use in combining portable batch scripting (PBS) grids and XNAT servers.

Posterior structural brain volumes differ in maltreated youth with and without chronic posttraumatic stress disorder.

Magnetic resonance imaging studies of maltreated children with posttraumatic stress disorder (PTSD) suggest that maltreatment-related PTSD is associated with adverse brain development. Maltreated youth resilient to chronic PTSD were not previously investigated and may elucidate neuromechanisms of the stress diathesis that leads to resilience to chronic PTSD. In this cross-sectional study, anatomical volumetric and corpus callosum diffusion tensor imaging measures were examined using magnetic resonance imaging in maltreated youth with chronic PTSD (N = 38), without PTSD (N = 35), and nonmaltreated participants (n = 59). Groups were sociodemographically similar. Participants underwent assessments for strict inclusion/exclusion criteria and psychopathology. Maltreated youth with PTSD were psychobiologically different from maltreated youth without PTSD and nonmaltreated controls. Maltreated youth with PTSD had smaller posterior cerebral and cerebellar gray matter volumes than did maltreated youth without PTSD and nonmaltreated participants. Cerebral and cerebellar gray matter volumes inversely correlated with PTSD symptoms. Posterior corpus callosum microstructure in pediatric maltreatment-related PTSD differed compared to maltreated youth without PTSD and controls. The group differences remained significant when controlling for psychopathology, numbers of Axis I disorders, and trauma load. Alterations of these posterior brain structures may result from a shared trauma-related mechanism or an inherent vulnerability that mediates the pathway from chronic PTSD to comorbidity.

Sarcopenia as a predictor of complications and survival following radical cystectomy.

PURPOSE: Patients undergoing radical cystectomy face substantial but highly variable risks of major complications. Risk stratification may be enhanced by objective measures such as sarcopenia. Sarcopenia (loss of skeletal muscle mass) has emerged as a novel biomarker associated with adverse outcomes in many clinical contexts relevant to cystectomy. Based on these data we hypothesized that sarcopenia would be associated with increased 30-day major complications and mortality after radical cystectomy for bladder cancer. MATERIALS AND METHODS: We performed a retrospective study of patients treated with radical cystectomy at our institution from 2008 to 2011. Sarcopenia was assessed by measuring cross-sectional area of the psoas muscle (total psoas area) on preoperative computerized tomography. Cutoff points were developed and evaluated using ROC curves to determine predictive ability in men and women for outcomes of major complications and survival. RESULTS: Of 224 patients with bladder cancer 200 underwent preoperative computerized tomography within 1 month of surgery. Total psoas area was calculated with a mean score of 712 and 571 cm2/m2 in men and women, respectively. A clear association was noted between major complications and lower total psoas area in women using a cutoff of 523 cm2/m2 to define sarcopenia (AUC 0.70). Sarcopenia was not significantly associated with complications in men. There was a nonsignificant trend of sarcopenia with worse 2-year survival. CONCLUSIONS: Sarcopenia in women was a predictor of major complications after radical cystectomy. Further research confirming sarcopenia as a useful predictor of complications would support the development of targeted interventions to mitigate the untoward effects of sarcopenia before cancer surgery.

Sensory subtypes in children with autism spectrum disorder: latent profile transition analysis using a national survey of sensory features.

BACKGROUND: Sensory features are highly prevalent and heterogeneous among children with ASD. There is a need to identify homogenous groups of children with ASD based on sensory features (i.e., sensory subtypes) to inform research and treatment. METHODS: Sensory subtypes and their stability over 1 year were identified through latent profile transition analysis (LPTA) among a national sample of children with ASD. Data were collected from caregivers of children with ASD ages 2-12 years at two time points (Time 1 N = 1294; Time 2 N = 884). RESULTS: Four sensory subtypes (Mild; Sensitive-Distressed; Attenuated-Preoccupied; Extreme-Mixed) were identified, which were supported by fit indices from the LPTA as well as current theoretical models that inform clinical practice. The Mild and Extreme-Mixed subtypes reflected quantitatively different sensory profiles, while the Sensitive-Distressed and Attenuated-Preoccupied subtypes reflected qualitatively different profiles. Further, subtypes reflected differential child (i.e., gender, developmental age, chronological age, autism severity) and family (i.e., income, mother's education) characteristics. Ninety-one percent of participants remained stable in their subtypes over 1 year. CONCLUSIONS: Characterizing the nature of homogenous sensory subtypes may facilitate assessment and intervention, as well as potentially inform biological mechanisms.

Empirical lessons about occupational categorization from case studies of unemployment.

BACKGROUND: Scrutiny regarding the typological categorization of occupation (e.g., occupation as work, rest, or leisure) has prompted interest in experiential categories as a less exclusionary alternative. Empirical research can extend the dialogue about categorization by demonstrating how people in particular situations apply and generate occupational categories. PURPOSE: This article explores how adults without work utilized typological and experiential categorizations when discussing their occupations. METHOD: Data were generated via a secondary analysis of interview transcripts from three ethnographic case studies. FINDINGS: Study consultants gravitated toward experiential rather than typological categorizations, emphasizing the social, chosen, purposeful, and temporal qualities of their occupational engagement. IMPLICATIONS: Occupational therapy practitioners and researchers must explicitly state how and why they categorize occupations with clients and research participants. Whereas typological categories can be used to initiate discussions about occupation, open questions paired with consultant-generated experiential categories may better capture occupational engagement and reveal potential injustices in situations like unemployment

Adapting the Early Communication Indicator as a Social Communication Outcome Measure for Young Autistic Children: A Pilot Study.

PURPOSE: We sought to conduct a pilot investigation of the reliability and administration fidelity of a new play-based measure of social communication for infants and toddlers with an autism diagnosis. METHOD: Our team adapted an existing measure, the Early Communication Indicator (ECI), for use with young autistic children in clinical and research contexts. In this brief report, we detail our adaptation process including administration and scoring of the final adapted measure based on data from a two-phase pilot study with young autistic children (N = 17). RESULTS: This adapted measure, the Early Communication Indicator-Autism (ECI-A), captured a range of scores for the ECI, Initiation of Joint Attention, and Directed Communication in pilot testing. Interrater reliability was moderate to strong across the scored behaviors. Finally, parents were able to administer the ECI-A with high fidelity with support from the research staff. CONCLUSIONS: This two-phase pilot study demonstrated promise for the ECI-A as a brief measure of social communication that can be administered by parents and reliably scored by trained staff with limited background in autism assessments. Validation of the ECI-A is presently underway. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.26042077.