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Background: Oral melanocytic neoplasms pose a diagnostic challenge to pathologists owing to their rarity relative to those in the skin. The utility of PRAME in distinguishing nevi from melanomas has been established in the skin, but limited information exists regarding its usefulness in the oral cavity., Methods: Thirty-five previously diagnosed pigmented oral lesions were retrospectively evaluated with PRAME. The lesions consisted of 16 oral nevi, 10 melanomas, and 10 melanotic macules., Results: Strong and diffuse nuclear PRAME staining was observed in all but one of the oral melanomas, which showed no staining. No nuclear PRAME staining was observed in any of the oral nevi or melanotic macules., Conclusions: PRAME is a useful tool in the evaluation of oral melanocytic neoplasms. Our data indicate that PRAME is a highly specific but incompletely sensitive marker of oral melanoma. Larger studies could further illuminate the diagnostic value of PRAME in oral lesions., (© 2022 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Importance: The rapid proliferation of COVID-19 has left governments scrambling, and several data aggregators are now assisting in the reporting of county cases and deaths. The different variables affecting reporting (e.g., time delays in reporting) necessitates a well-documented reliability study examining the data methods and discussion of possible causes of differences between aggregators., Objective: To statistically evaluate the reliability of COVID-19 data across aggregators using case fatality rate (CFR) estimates and reliability statistics., Design, Setting, and Participants: Cases and deaths were collected daily by volunteers via state and local health departments, as primary sources and newspaper reports, as secondary sources. In an effort to begin comparison for reliability statistical analysis, BroadStreet collected data from other COVID-19 aggregator sources, including USAFacts, Johns Hopkins University, New York Times, The COVID Tracking Project., Main Outcomes and Measures: COVID-19 cases and death counts at the county and state levels., Results: Lower levels of inter-rater agreement were observed across aggregators associated with the number of deaths, which manifested itself in state level Bayesian estimates of COVID-19 fatality rates., Conclusions and Relevance: A national, publicly available data set is needed for current and future disease outbreaks and improved reliability in reporting., Competing Interests: The specific roles of these authors are articulated in the ‘author contributions’ section. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Background: The "trimorbidity" of substance use disorder and mental and physical illness is associated with living in precarious housing or homelessness. The extent to which substance use increases risk of psychosis and both contribute to mortality needs investigation in longitudinal studies., Methods and Findings: A community-based sample of 437 adults (330 men, mean [SD] age 40.6 [11.2] years) living in Vancouver, Canada, completed baseline assessments between November 2008 and October 2015. Follow-up was monthly for a median 6.3 years (interquartile range 3.1-8.6). Use of tobacco, alcohol, cannabis, cocaine, methamphetamine, and opioids was assessed by interview and urine drug screen; severity of psychosis was also assessed. Mortality (up to November 15, 2018) was assessed from coroner's reports and hospital records. Using data from monthly visits (mean 9.8, SD 3.6) over the first year after study entry, mixed-effects logistic regression analysis examined relationships between risk factors and psychotic features. A past history of psychotic disorder was common (60.9%). Nonprescribed substance use included tobacco (89.0%), alcohol (77.5%), cocaine (73.2%), cannabis (72.8%), opioids (51.0%), and methamphetamine (46.5%). During the same year, 79.3% of participants reported psychotic features at least once. Greater risk was associated with number of days using methamphetamine (adjusted odds ratio [aOR] 1.14, 95% confidence interval [CI] 1.05-1.24, p = 0.001), alcohol (aOR 1.09, 95% CI 1.01-1.18, p = 0.04), and cannabis (aOR 1.08, 95% CI 1.02-1.14, p = 0.008), adjusted for demographic factors and history of past psychotic disorder. Greater exposure to concurrent month trauma was associated with increased odds of psychosis (adjusted model aOR 1.54, 95% CI 1.19-2.00, p = 0.001). There was no evidence for interactions or reverse associations between psychotic features and time-varying risk factors. During 2,481 total person years of observation, 79 participants died (18.1%). Causes of death were physical illness (40.5%), accidental overdose (35.4%), trauma (5.1%), suicide (1.3%), and unknown (17.7%). A multivariable Cox proportional hazard model indicated baseline alcohol dependence (adjusted hazard ratio [aHR] 1.83, 95% CI 1.09-3.07, p = 0.02), and evidence of hepatic fibrosis (aHR 1.81, 95% CI 1.08-3.03, p = 0.02) were risk factors for mortality. Among those under age 55 years, a history of a psychotic disorder was a risk factor for mortality (aHR 2.38, 95% CI 1.03-5.51, p = 0.04, adjusted for alcohol dependence at baseline, human immunodeficiency virus [HIV], and hepatic fibrosis). The primary study limitation concerns generalizability: conclusions from a community-based, diagnostically heterogeneous sample may not apply to specific diagnostic groups in a clinical setting. Because one-third of participants grew up in foster care or were adopted, useful family history information was not obtainable., Conclusions: In this study, we found methamphetamine, alcohol, and cannabis use were associated with higher risk for psychotic features, as were a past history of psychotic disorder, and experiencing traumatic events. We found that alcohol dependence, hepatic fibrosis, and, only among participants <55 years of age, history of a psychotic disorder were associated with greater risk for mortality. Modifiable risk factors in people living in precarious housing or homelessness can be a focus for interventions., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: WGH has received consulting fees or sat on paid advisory boards for In Silico, Otsuka/Lundbeck, Newron, AlphaSights, the Centre for Drug Research and Development, and the Canadian Agency for Drugs and Technology in Health. He was additionally supported by the Jack Bell Chair in Schizophrenia. FVR received research support from Canadian Institutes of Health Research (CIHR), Brain Canada, Michael Smith Foundation for Health Research, and Vancouver Coastal Health Research Institute; received in-kind equipment support for this investigator-initiated trial from MagVenture; and has been on an advisory board for Janssen. RMP has been a member of the following advisory boards in the past 3 years: Janssen, Lundbeck, and Otsuka; a member of the following speaker’s bureaus in the past 3 years: Janssen, Lundbeck, and Otsuka; and received grants from the Canadian Institutes of Health Research. GWM has received consulting fees or sat on paid advisory boards for: Apotex, AstraZeneca, BMS, Janssen, Lundbeck, Otsuka, Pfizer, and Sunovion. He also received fees for lectures sponsored by AstraZeneca, BMS, Janssen, Otsuka, and Eli Lilly, and has received grants from Janssen Pharmaceuticals. JSGM has received institutional grants from Gilead Sciences, J&J, Merck, ViiV Healthcare, and a Knowledge Translation Award from the Canadian Institutes of Health Research. JSGM has also served as an advisor to Government of Canada and the Government of British Columbia in the last year. AET has received grants from the Canadian Institutes of Health Research (CIHR) and the William and Ada Isabelle Steel Fund. This does not alter our adherence to PLOS Medicine policies on sharing data and materials. AAJ, KMG, SS, TSW, OL, GNS, TAS, ATV, TB, AR, DJL, VDL, WJP, and AMB declared that no competing interests exist.

Despite the broad literature base on factor analysis best practices, research seeking to evaluate a measure's psychometric properties frequently fails to consider or follow these recommendations. This leads to incorrect factor structures, numerous and often overly complex competing factor models and, perhaps most harmful, biased model results. Our goal is to demonstrate a practical and actionable process for factor analysis through (a) an overview of six statistical and psychometric issues and approaches to be aware of, investigate, and report when engaging in factor structure validation, along with a flowchart for recommended procedures to understand latent factor structures; (b) demonstrating these issues to provide a summary of the updated Posttraumatic Stress Disorder Checklist (PCL-5) factor models and a rationale for validation; and (c) conducting a comprehensive statistical and psychometric validation of the PCL-5 factor structure to demonstrate all the issues we described earlier. Considering previous research, the PCL-5 was evaluated using a sample of 1,403 U.S. Air Force remotely piloted aircraft operators with high levels of battlefield exposure. Previously proposed PCL-5 factor structures were not supported by the data, but instead a bifactor model is arguably more statistically appropriate.

Objective: PediaTrac™, a 363-item web-based tool to track infant development, administered in modules of ∼40-items per sampling period, newborn (NB), 2--, 4--, 6--, 9-- and 12--months was validated. Caregivers answered demographic, medical, and environmental questions, and questions covering the sensorimotor, feeding/eating, sleep, speech/language, cognition, social-emotional, and attachment domains., Methods: Expert Panel Reviews and Cognitive Interviews (CI) were conducted to validate the item bank. Classical Test Theory (CTT) and Item Response Theory (IRT) methods were employed to examine the dimensionality and psychometric properties of PediaTrac with pooled longitudinal and cross-sectional cohorts (N = 132)., Results: Intraclass correlation coefficients (ICC) for the Expert Panel Review revealed moderate agreement at 6 -months and good reliability at other sampling periods. ICC estimates for CI revealed moderate reliability regarding clarity of the items at NB and 4 months, good reliability at 2--, 9-- and 12--months and excellent reliability at 6 -months. CTT revealed good coefficient alpha estimates (α ≥ 0.77 for five of the six ages) for the Social-Emotional/Communication, Attachment (α ≥ 0.89 for all ages), and Sensorimotor (α ≥ 0.75 at 6-months) domains, revealing the need for better targeting of sensorimotor items. IRT modeling revealed good reliability (r = 0.85-0.95) for three distinct domains (Feeding/Eating, Social-Emotional/Communication and Attachment) and four subdomains (Feeding Breast/Formula, Feeding Solid Food, Social-Emotional Information Processing, Communication/Cognition). Convergent and discriminant construct validity were demonstrated between our IRT-modeled domains and constructs derived from existing developmental, behavioral and caregiver measures. Our Attachment domain was significantly correlated with existing measures at the NB and 2-month periods, while the Social-Emotional/Communication domain was highly correlated with similar constructs at the 6-, 9- and 12-month periods., Conclusion: PediaTrac has potential for producing novel and effective estimates of infant development via the Sensorimotor, Feeding/Eating, Social-Emotional/Communication and Attachment domains., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: Cutaneous drug reactions are frequently found. Assessing the clinical and epidemiological profile of severe forms is extremely relevant for their better recognition and management. Few studies have assessed the severe forms of cutaneous drug reactions in patients hospitalized in our setting., Objectives: To assess the clinical and epidemiological aspects of severe cutaneous adverse reactions to drugs in a tertiary hospital in Porto Alegre, Brazil., Methods: All cases of severe cutaneous adverse reactions to drugs in patients hospitalized from January/2005 to December/2010 were retrospectively analyzed for clinical and epidemiological variables. Cases of Stevens-Johnson Syndrome, Toxic Epidermal Necrolysis, drug hypersensitivity syndrome or Drug Reaction with Eosinophilia and Systemic Symptoms and acute generalized exanthematous pustulosis were included., Results: An occurrence rate of 1 serious reaction for every 3,048 inpatients was found (total of 173,767 inpatients admitted in the period). Drug Reaction with Eosinophilia and Systemic Symptoms was the most frequent presentation. The drugs most frequently involved were anticonvulsants (40.4%), antibiotics (26.3%), and analgesics/anti-inflammatory drugs (10.5%). Thirty seven patients (64.9%) were admitted to hospital because of the cutaneous drug reaction. Ten patients (17.5%) died and in most of those (60%), the drug causing the reaction could not be determined., Conclusions: The frequency of severe cutaneous adverse reactions to drugs in our setting is significant. Drug Reaction with Eosinophilia and Systemic Symptoms seems to be the most frequent presentation of severe cutaneous drug reactions. Most patients developed cutaneous drug reactions outside the hospital. Mortality rates were higher for Toxic Epidermal Necrolysis and this presentation significantly affected older people. Not knowing the drug causing the reaction was related to mortality.

Visual and auditory verbal learning using a selective reminding format was studied in a mixed clinical sample of children with autism spectrum disorder (ASD) (n = 42), attention-deficit hyperactivity disorder (n = 83), velocardiofacial syndrome (n = 17) and neurotypicals (n = 38) using the Test of Memory and Learning to (1) more thoroughly characterize and examine the integrity of learning and memory processes, (2) to better understand the mechanisms of learning impairment, and (3) to inform instructional practices in ASD. Contrary to expectations, children with ASD demonstrated a relative weakness in the rate of acquisition of visual in contrast to verbal learning compared to neurotypicals. They also showed a complex pattern of consolidation. Overall, between-group differences were more likely to emerge during the visual learning task, suggesting that it may be more sensitive for detecting neurodevelopmental differences. The heuristic value of assessing memory and learning across multiple trials and comparing performance during immediate and delayed recall is discussed.

Current approaches to the assessment and classification of personality disorders (PDs) rely almost exclusively on self-report methodology. In this paper, we document the many difficulties with self-reports, including limitations in their accuracy, the confounding effect of mood state, and problems with the selection and retention of factors in factor analytic approaches to self-report questionnaires. We also discuss the role of implicit processes in self-reports, with special attention directed to the phenomenon of priming and its effect on outcome. To rectify these issues, we suggest a transtheoretical, multimethod, multimodal approach to personality pathology assessment and diagnosis, which utilizes the richness of prototypes and empirical findings on PD categories and pathologies.

Exploratory factor analysis (EFA) is a commonly used statistical technique for examining the relationships between variables (e.g., items) and the factors (e.g., latent traits) they depict. There are several decisions that must be made when using EFA, with one of the more important being choice of the rotation criterion. This selection can be arduous given the numerous rotation criteria available and the lack of research/literature that compares their function and utility. Historically, researchers have chosen rotation criteria based on whether or not factors are correlated and have failed to consider other important aspects of their data. This study reviews several rotation criteria, demonstrates how they may perform with different factor pattern structures, and highlights for researchers subtle but important differences between each rotation criterion. The choice of rotation criterion is critical to ensure researchers make informed decisions as to when different rotation criteria may or may not be appropriate. The results suggest that depending on the rotation criterion selected and the complexity of the factor pattern matrix, the interpretation of the interfactor correlations and factor pattern loadings can vary substantially. Implications and future directions are discussed.

There is little agreement about the latent factor structure of the Diagnostic and Statistical Manual of Mental Disorders (DSM) personality disorders (PDs). Factor analytic studies over the past 2 decades have yielded different results, in part reflecting differences in factor analytic technique, the measure used to assess the PDs, and the changing DSM criteria. In this study, we explore the latent factor structure of the DSM (4th ed.; IV) PDs in a sample of 1200 psychiatric outpatients evaluated with the Structured Interview for DSM-IV PDs (B. Pfohl, N. Blum, & M. Zimmerman, 1997). We first evaluated 2 a priori models of the PDs with confirmatory factor analysis (CFA), reflecting their inherent organization in the DSM-IV: a 3-factor model and a 10-factor model. Fit statistics did not suggest that these models yielded an adequate fit. We then evaluated the latent structure with exploratory factor analysis (EFA). Multiple solutions produced more statistically and theoretically reasonable results, as well as providing clinically useful findings. On the basis of fit statistics and theory, 3 models were evaluated further--the 4-, 5-, and 10-factor models. The 10-factor model, which did not resemble the 10-factor model of the CFA, was determined to be the strongest of all 3 models. Future research should use contemporary methods of evaluating factor analytic results in order to more thoroughly compare various factor solutions., (PsycINFO Database Record (c) 2011 APA, all rights reserved)

The Differentiation of Self Inventory (DSI) is a multidimensional measure of differentiation consisting of four subscales focusing on adults (ages 25+), and their significant relationships, including current relationships with family of origin. Although the DSI full scale and three of its subscales are theoretically and psychometrically sound, the Fusion with Others (FO) subscale is lacking. Therefore, responses of 225 adults were used to revise the FO subscale. Results yielded a 12-item, revised FO subscale with improved internal consistency reliability and construct validity. Greater fusion with others was associated with greater spousal fusion and dimensions of adult attachment insecurity. Implications for Bowen theory and suggestions for future research with the DSI-R are discussed.

Among 2966 acute leukemia, 26 familial cases were reported. Leukemia occured mainly in the first relative individuals and particularly in the sibship. The relative risk for a sib of leukemic patient is four time more than for random people. Leukemia was often similar among patients of the same family and the onsets of the disease occured approximatly at the same age whatever the time between the dates of diagnosis. Twins with leukemia were often monozygotous. Relative risk of leukemia among twins, decreases according to the age: the probability of leukemia for a twin is: (a) 100 p. cent if the other twin is leukemic before 1 year old; (b) 15 p. cent between 1 to 4 years old and (c) similar to other sib after 4 years old. Among chronic leukemias, only chronic lymphocytic leukemia seems to have a genetic background for susceptibility. Some familial diseases (congenital aplastic anemia, Bloom's disease, Ataxia telangiectasia) or congenital diseases (Down's syndrome) increase the risk of leukemia.