Citations

Abstract Objective For adolescents, DSM‐5 differentiates anorexia nervosa (AN) and atypical AN with the 5th BMI‐centile‐for‐age. We hypothesized that the diagnostic weight cut‐off yields (i) lower weight loss in atypical AN and (ii) discrepant premorbid BMI distributions between the two disorders. Prior studies demonstrate that premorbid BMI predicts admission BMI and weight loss in patients with AN. We explore these relationships in atypical AN. Method Based on admission BMI‐centile < or ≥5th, participants included 411 female adolescent inpatients with AN and 49 with atypical AN from our registry study. Regression analysis and t ‐tests statistically addressed our hypotheses and exploratory correlation analyses compared interrelationships between weight loss, admission BMI, and premorbid BMI in both disorders. Results Weight loss in atypical AN was 5.6 kg lower than in AN upon adjustment for admission age, admission height, premorbid weight and duration of illness. Premorbid BMI‐standard deviation scores differed by almost one between both disorders. Premorbid BMI and weight loss were strongly correlated in both AN and atypical AN. Discussion Whereas the weight cut‐off induces discrepancies in premorbid weight and adjusted weight loss, AN and atypical AN overall share strong weight‐specific interrelationships that merit etiological consideration. Epidemiological and genetic associations between AN and low body weight may reflect a skewed premorbid BMI distribution. In combination with prior findings for similar psychological and medical characteristics in AN and atypical AN, our findings support a homogenous illness conceptualization. We propose that diagnostic subcategorization based on premorbid BMI, rather than admission BMI, may improve clinical validity. Public significance Because body weights of patients with AN must drop below the 5th BMI‐centile per DSM‐5, they will inherently require greater weight loss than their counterparts with atypical AN of the same sex, age, height and premorbid weight. Indeed, patients with atypical AN had a 5.6 kg lower weight loss after controlling for these variables. In comparison to the reference population, we found a lower and higher mean premorbid weight in patients with AN and atypical AN, respectively. Considering previous psychological and medical comparisons showing little differences between AN and atypical AN, we view a single disorder as the most parsimonious explanation. Etiological models need to particularly account for the strong relationship between weight loss and premorbid body weight.

Summary: Incorporation of new technologies to assist the liposuction procedure is becoming increasingly common. These technologies allow for a softer technique, balanced shaping, elimination of excess adipose tissue, and skin tightening. Some of these technologies include ultrasound (US; US-assisted liposculpture, VASER-assisted liposuction), power suction (power-assisted liposuction), radiofrequency (RF; RF-assisted lipolysis), and laser (laser-assisted liposuction). In addition, some of these devices have been shown to reduce the incidence of hematomas/inflammation and shorten recovery time. We report our experience in high-definition liposculpture of the arms in addition to new technologies to improve skin retraction, comparing their results in terms of complications, satisfaction score, and aesthetic outcomes. We included patients with mild-to-moderate arm dermatochalasis (Duncan classification) fat deposits in the upper extremities who were considered candidates for third-generation US-assisted liposculpture, power-assisted liposuction, RF-assisted lipolysis/skin tightening, and laser-assisted liposuction. A total of 683 consecutive patients met the inclusion criteria for the study. Most of them were women (n = 605, 88%). Fat grafting was performed in 80 patients (11.7%). A significant portion of the patients were secondary cases (n = 223, 33%). Age ranged from 18 to 70 years (median = 38 years). BMI ranged from 17.8 to 34.8 kg/m2 (mean = 24.3 kg/m2). RF-assisted and laser-assisted high-definition liposculpture of the arms are both effective and reproducible techniques for patients who seek an athletic and slim arm contour. A low rate of complications and high satisfaction index support our findings.

Introduction Difficult or impossible femoral access remains a significant burden for mechanical thrombectomy (MT) in stroke, affecting between 4.4% (impossible) to ∼10% of cases (time to first angiography [T1A] > 30 min) [1]. Visualization of CT angiography (CTA) or MR angiography are the only available diagnostic tools for neurointerventionalists (NIs) to qualitatively assess catheterization difficulty ahead of intervention. Visualization of 3D segmentation of the head‐and‐neck arteries from CTA may provide enhanced spatial information for catheter access difficulty assessment to the occlusion site, as well as large vessel occlusion (LVO) localization or carotid stenosis detection. Methods Three observers (2 expert NIs and 1 medical image engineer) assessed a sample of patients with anterior circulation stroke rating LVO location, femoral access difficulty according to a Likert scale (0 to 5) and assessment of radial access compared to femoral (easier or not). Raters were asked to answer the same form for each case twice, once after visualizing only the CTA and again after visualizing a deep‐learning, automated 3D segmentation of the head‐and‐neck arteries from CTA [2]. Cases were randomly sampled and blind to raters for both assessments. Likert scale values were normalized and averaged across observers, and correlation to T1A was studied. LVO localization accuracy and time needed for the analysis was also assessed. Results The final sample included N = 117 cases, where 22.98% presented difficult or impossible access. LVO location prevalence was 13/15/45/27% for extracranial ICA (eICA)/TICA/M1/M2, and 49/51% for right/left. Averaged Likert values presented significant linear correlation for both segmentation and CTA visualization, but this was much stronger in the former (R: 0.58 vs 0.30, p<0.001). Three‐dimensional visualization of segmented vessels allowed for an enhanced detection of difficult or impossible femoral access (ROC‐AUC: 0.85 vs 0.66). LVO detection was also superior after segmentation visualization (mean accuracy across observers: 0.81 vs 0.72) and time needed for assessment was on average 2.3 times shorter (44 s vs 100 s). In difficult or impossible patients, radial access was considered easier in 74% (63‐89%) of cases when visualizing the segmentation compared to 42% (35‐48%) when inspecting the CTA. Conclusion Visualization of deep‐learning 3D arterial segmentation resulted in enhanced difficult or impossible femoral access for MT, LVO detection and faster analysis over traditional pre‐procedural CTA inspection. Adding this visualization to the current workflow could enhance difficult access detection ahead of intervention.

Abstract Objectives The objective of this study was to explore the prevalence, characteristics and risk factors of COVID-19 breakthrough infections (BIs) in idiopathic inflammatory myopathies (IIMs) using data from the COVID-19 Vaccination in Autoimmune Diseases (COVAD) study. Methods A validated patient self-reporting e-survey was circulated by the COVAD study group to collect data on COVID-19 infection and vaccination in 2022. BIs were defined as COVID-19 occurring ≥14 days after two vaccine doses. We compared BI characteristics and severity among patients with IIMs, patients with other autoimmune rheumatic and non-rheumatic diseases (AIRD, nrAID), and healthy controls (HCs). Multivariable Cox regression models were used to assess the risk factors for BI, severe BI ,and hospitalizations among patients with IIMs. Results Among the 9449 included responses, BIs occurred in 1447 respondents (15.3%). The median age was 44 years [interquartile range (IQR) 21], 77.4% were female, and 182 BIs (12.9%) occurred among the 1406 patients with IIMs. Multivariable Cox regression among the data for patients with IIMs showed increasing age to be a protective factor for BIs [hazard ratio (HR) = 0.98, 95% CI = 0.97–0.99], and HCQ and SSZ use were risk factors (HR = 1.81, 95% CI = 1.24–2.64, and HR = 3.79, 95% CI = 1.69–8.42, respectively). Glucocorticoid use was a risk factor for a severe BI (HR = 3.61, 95% CI = 1.09–11.8). Non-white ethnicity (HR = 2.61, 95% CI = 1.03–6.59) was a risk factor for hospitalization. Compared with other groups, patients with IIMs required more supplemental oxygen therapy (IIMs = 6.0% vs AIRDs = 1.8%, nrAIDs = 2.2% and HCs = 0.9%), intensive care unit admission (IIMs = 2.2% vs AIRDs = 0.6%, nrAIDs and HCs = 0%), advanced treatment with antiviral or monoclonal antibodies (IIMs = 34.1% vs AIRDs = 25.8%, nrAIDs = 14.6% and HCs = 12.8%) and had more hospitalization (IIMs = 7.7% vs AIRDs = 4.6%, nrAIDs = 1.1% and HCs = 1.5%). Conclusion Patients with IIMs are susceptible to severe COVID-19 BIs. Age and immunosuppressive treatments were related to the risk of BIs.

Abstract Objectives To investigate health-related quality of life in patients with idiopathic inflammatory myopathies (IIMs) compared with those with non-IIM autoimmune rheumatic diseases (AIRDs), non-rheumatic autoimmune diseases (nrAIDs) and without autoimmune diseases (controls) using Patient-Reported Outcome Measurement Information System (PROMIS) instrument data obtained from the second COVID-19 vaccination in autoimmune disease (COVAD-2) e-survey database. Methods Demographics, diagnosis, comorbidities, disease activity, treatments and PROMIS instrument data were analysed. Primary outcomes were PROMIS Global Physical Health (GPH) and Global Mental Health (GMH) scores. Factors affecting GPH and GMH scores in IIMs were identified using multivariable regression analysis. Results We analysed responses from 1582 IIM, 4700 non-IIM AIRD and 545 nrAID patients and 3675 controls gathered through 23 May 2022. The median GPH scores were the lowest in IIM and non-IIM AIRD patients {13 [interquartile range (IQR) 10–15] IIMs vs 13 [11–15] non-IIM AIRDs vs 15 [13–17] nrAIDs vs 17 [15–18] controls, P &lt; 0.001}. The median GMH scores in IIM patients were also significantly lower compared with those without autoimmune diseases [13 (IQR 10–15) IIMs vs 15 (13–17) controls, P &lt; 0.001]. Inclusion body myositis, comorbidities, active disease and glucocorticoid use were the determinants of lower GPH scores, whereas overlap myositis, interstitial lung disease, depression, active disease, lower PROMIS Physical Function 10a and higher PROMIS Fatigue 4a scores were associated with lower GMH scores in IIM patients. Conclusion Both physical and mental health are significantly impaired in IIM patients, particularly in those with comorbidities and increased fatigue, emphasizing the importance of patient-reported experiences and optimized multidisciplinary care to enhance well-being in people with IIMs.

AbstractDiffuse cystic lung diseases (DCLDs) are a diverse group of lung disorders characterized by the presence of multiple air filled cysts within the lung tissue. These cysts are thin walled and surrounded by normal lung tissue. In adults, DCLD can be associated with various conditions such as lymphangioleiomyomatosis (LAM), Langerhans cell histiocytosis, cancers, and more. In children, DCLD is often linked to lung developmental abnormalities, with bronchopulmonary dysplasia being a common cause. Patients with pulmonary cysts are typically asymptomatic, but some may experience mild symptoms or pneumothorax. While DCLD in children is rarely due to malignancy, metastatic lung disease can be a cause. It is important for clinicians to be aware of the possibility of metastatic lung disease when encountering DCLD.

Abstract The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Abstract Introduction The aim of this case–control study was to determine if exposure to tumor necrosis factor alpha inhibitors (TNFIs) or immunomodulators (thiopurines or methotrexate) was associated with development of primary gastrointestinal lymphoma (PGIL) in patients with chronic inflammatory conditions. Methods Patients with PGIL and controls evaluated at a tertiary care center over 20 years were matched 1:3 using a medical record informatics search engine based on their chronic inflammatory condition (Crohn’s disease [CD], ulcerative colitis [UC], rheumatoid arthritis, ankylosing spondylitis, and psoriatic arthritis) and duration of follow-up. Patients who started on TNFI within 3 months of PGIL diagnosis were excluded. We extracted demographics, medical history, and medications used. Univariate models using conditional logistic regression were used due to the small number of matched pairs. Results Twenty PGIL cases matched with 60 controls were followed for a mean 9.9 ± 6.9 and 9.7 ± 8.6 years, respectively. Mean age at time of PGIL diagnosis was 47.5 ± 22.0 (standard deviation) years and the majority (75%) were males. The most common inflammatory diagnosis was inflammatory bowel disease (80% of cases; 45% with UC and 35% with CD). Development of PGIL was not associated with TNFI (odds ratio [OR] = 2.6; 95% confidence interval [CI] 0.69–11.01; P = .18), but with use of TNFI in combination with thiopurines (OR = 8.93; 95% CI 1.43–80.25; P = .014). Risk of PGIL increased with every additional TNFI (2.277 (1.002–5.713); P = .0494). All cases exposed to multiple TNFI were also exposed to thiopurines. Use of thiopurines (alone or in combination) was the greatest risk factor (OR = 6.32; 95% CI 1.55–37.05; P = 0.006) to develop PGIL. Conclusions TNFI therapy was not associated with increased risk for PGIL unless used in combination with thiopurines and with every switch to a different TNFI.