Faculty Bibliography

Neurological manifestations have been widely reported in adults with COVID-19, yet the extent of involvement among the pediatric population is currently poorly characterized. The objective of our systematic review is to evaluate the association of SARS-CoV-2 infection with neurological symptoms and neuroimaging manifestations in the pediatric population. A literature search of Cochrane Library; EBSCO CINAHL; Global Index Medicus; OVID AMED, Embase, Medline, PsychINFO; and Scopus was conducted in accordance with the Peer Review of Electronic Search Strategies form (October 1, 2019 to March 15, 2022). Studies were included if they reported (1) COVID-19-associated neurological symptoms and neuroimaging manifestations in individuals aged <18 years with a confirmed, first SARS-CoV-2 infection and were (2) peer-reviewed. Full-text reviews of 222 retrieved articles were performed, along with subsequent reference searches. A total of 843 no-duplicate records were retrieved. Of the 19 identified studies, there were ten retrospective observational studies, seven case series, one case report, and one prospective cohort study. A total of 6985 individuals were included, where 12.8% (n = 892) of hospitalized patients experienced neurocognitive impairments which includes: 1) neurological symptoms (n = 294 of 892, 33.0%), 2) neurological syndromes and neuroimaging abnormalities (n = 223 of 892, 25.0%), and 3) other phenomena (n = 233 of 892, 26.1%). Based on pediatric-specific cohorts, children experienced more drowsiness (7.3% vs. 1.3%) and muscle weakness (7.3% vs. 6.3%) as opposed to adolescents. Agitation or irritability was observed more in children (7.3%) than infants (1.3%). Our findings revealed a high prevalence of immune-mediated patterns of disease among COVID-19 positive pediatric patients with neurocognitive abnormalities.

BACKGROUND:The use of artificial intelligence (AI) for skin cancer assessment has been an emerging topic in dermatology. Leadership of dermatologists is necessary in defining how these technologies fit into clinical practice. OBJECTIVE:To characterize the evolution of AI in skin cancer assessment and characterize the involvement of dermatologists in developing these technologies. METHODS:An electronic literature search was performed using PubMed searching machine learning or artificial intelligence combined with skin cancer or melanoma. Articles were included if they used AI for screening and diagnosis of skin cancer using datasets consisting of dermatoscopic images or photographs of gross lesions. RESULTS:Fifty-one articles were included, of which 41% had dermatologists included as authors. Manuscripts including dermatologists described algorithms built using more images (mean 12111 vs 660). In terms of underlying technology, AI used for skin cancer assessment has followed trends in the field of image recognition. LIMITATIONS/CONCLUSIONS:This review focused on models described in the medical literature and did not account for those described elsewhere. CONCLUSIONS:Greater involvement of dermatologists is needed in thinking through issues in data collection, dataset biases, and applications of technology. Dermatologists can provide access to large, diverse datasets that are increasingly important for building these models.

Background: The psoriasis symptom inventory (PSI) is a validated tool measuring patient-reported psoriasis signs and symptoms, with higher scores indicating increased severity. This post hoc analysis examines PSI response rates and scores stratified by sex and skin clearance levels in clinical trials of brodalumab, an interleukin-17 receptor A antagonist efficacious for treatment of moderate-to-severe psoriasis.
Method(s): Data were analyzed from two double-blind, placebo- and active-comparator-controlled, phase 3 studies (AMAGINE-2/-3). This analysis includes patients who received continuous brodalumab 210 mg every 2 weeks (Q2W) or ustekinumab through 12 weeks. Rates of PSI response (total score of <=8) were stratified by sex. Mean PSI scores were stratified by sex and psoriasis area and severity index improvement scores from baseline of 75% to <90% (PASI 75 to <90), PASI >=90 to <100, and PASI 100.
Result(s): Regardless of sex, brodalumab was associated with significantly higher PSI response rates than ustekinumab from week 2 (P <.0001) through week 12 (P =.002). At week 12, PSI response rates in brodalumab and ustekinumab cohorts, respectively, were 72.3% vs 59.7% (males) and 67.3% vs 57.5% (females). Among patients with PASI 75 to <90 at week 12, brodalumab was associated with numerically lower mean (standard error) PSI scores vs ustekinumab for males (4.89 [0.72] vs 5.85 [0.51]) and females (6.40 [1.24] vs 7.37 [0.93]).
Conclusion(s): In male and female patients, brodalumab was associated with achievement of PSI response by week 2 and a trend toward greater symptom relief for those with incomplete PASI responses at week 12 vs ustekinumab.
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The majority of antidepressant medication trials have focused on adult populations (ages 18-65), with much less research in older and younger populations. Moreover, key differences in the efficacy and safety of antidepressants have been identified between these age groups. Ketamine has emerged as a promising new treatment for treatment resistant depression (TRD). The objective of this review is to summarize and synthesize the extant literature on the effectiveness, safety and tolerability of ketamine for depression in special age populations (age ≤18 and ≥ 60). Following PRISMA guidelines, a systematic review was performed, searching EMBASE, PsycInfo, and PubMed from inception through July 2020. Studies reporting the use of any ketamine formulation with variable routes of administration to treat clinically diagnosed depression in adolescents or older adults were included. Thirteen studies were included in the analysis and ten observed rapid (≤2 week latency) antidepressant effects following ketamine treatments, with better outcomes following larger, repeated doses, and in open-label rather than blinded settings. Two case reports in adolescents assessed measures of suicidal ideation and both found ketamine to effectuate rapid anti-suicidal effects. Ketamine appears to be safe and well-tolerated in adolescents and older adults. The small quantity, high heterogeneity, and generally low quality of available studies precludes statistical syntheses and significantly limits the strength of our conclusions. Preliminary proof-of-concept studies are promising, however, rigorously designed randomized controlled trials (RCTs) are still required to ascertain effectiveness, safety and tolerability in these groups.

There is significant interest in understanding the pathophysiology of Obsessive-Compulsive Disorder (OCD) using resting-state fMRI (rsfMRI). Previous studies acknowledge abnormalities within and beyond the fronto-striato-limbic circuit in OCD that require further clarifications. However, limited information could be inferred from the conventional way of investigating the functional connectivity differences between OCD and healthy controls. Here, we identified altered brain organization in patients with OCD by applying individual-based approaches to maximize the identification of underlying network-based features specific to the OCD group. rsfMRI of 20 patients with OCD and 22 controls were preprocessed, and individual-fMRI-subspace was derived for each subject within each group. We evaluated group differences in functional connectivity using individual-fMRI-subspace and established its advantage over conventional-fMRI methodology. We applied prediction-based approaches to highlight the group differences by evaluating the differences in functional connections that predicted the clinical scores (namely, the Obsessive-Compulsive Inventory-Revised (OCI-R) and Hamilton Anxiety Rating Scale). Then, we explored the brain network organization of both groups by estimating the subject-specific communities within each group. Lastly, we evaluated associations between the inter-individual variation of nodes in the communities to clinical measures using linear regression. Functional connectivity analysis using individual-fMRI-subspace detected 83 connections that were different between OCD and control groups, compared to none found using conventional-fMRI methodology. Connectome-based prediction analysis did not show significant overlap between the two groups in the functional connections that predicted the clinical scores. This suggests that the functional architecture in patients with OCD may be different compared to controls. Seven communities were found in both groups. Interestingly, within the OCD group but not controls, we observed functional connectivity between cerebellar and visual regions, and lack of connectivity between striato-limbic and frontal areas. Inter-individual variations in the community-size of these two communities were also associated with the OCI-R score (p < .005). Due to our small sample size, we further validated our results by (i) accounting for head motion, (ii) applying global signal regression (GSR) in data processing, and (iii) using an alternate atlas for parcellation. While the main results were consistently observed with accounting for head motion and using another atlas, the key findings were not reproduced with GSR application. The study demonstrated the existence of disconnectedness in fronto-striato-limbic community and connectedness between cerebellar and visual areas in OCD patients, which was also related to the clinical symptomatology of OCD.