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Jaccoud's arthropathy (JA) is a chronic deforming arthropathy, initially linked to rheumatic fever, now more commonly associated with systemic lupus erythematosus (SLE). We report a case of a 27-year-old male presenting with a four-month history of joint pain in the bilateral hands and feet, accompanied by stiffness but no swelling, erythema, or fever. Physical examination revealed flexion deformities, ulnar deviation at the metacarpophalangeal joints, and hyperextension at the proximal interphalangeal joints, without tenderness. Laboratory findings showed elevated anti-double stranded DNA (anti-dsDNA) antibodies and positive antinuclear antibodies (ANA), and imaging confirmed non-erosive arthropathy. Diagnosed with SLE-associated JA, the patient was treated with prednisone, diclofenac, and hydroxychloroquine, leading to significant symptom improvement and decreased anti-dsDNA antibody levels. Even though non-erosive and non-deforming arthropathy is more commonly seen in SLE, timely identification of JA as a non-erosive but deforming arthritis is crucial in differentiating SLE from rheumatoid arthritis. This case underscores the need for comprehensive evaluation and tailored therapy in complex autoimmune conditions to prevent long-term joint damage and improve patient outcomes., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Sanchez et al.)

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is an uncommon genetic disorder that affects small blood vessels in the brain. It leads to neurological symptoms, disability-adjusted life years, and difficult emotional and physical situations for patients and their families. As unusual brain symptoms appear, it becomes important to understand the different clinical manifestations of CADASIL. Our case report and review examine several cases to demonstrate different presentations and management strategies of CADASIL. A 52-year-old male with a family history of strokes at a young age from his father and paternal grandfather presented to a neurology clinic for left facial droop and drooling. Brain magnetic resonance imaging showed extensive periventricular and subcortical white matter disease, including the external capsule and subcortical white matter of the temporal lobe. Findings were suggestive of small vessel vasculopathy. A cerebral angiogram showed that all large extra- and intracranial vessels were patent without evidence of aneurysm formation. There was no obvious evidence of beading of the distal intracranial vessels. Cerebrospinal fluid studies were normal. The NOTCH3 mutation was sent to test for CADASIL, which came back positive. The patient was started on aspirin (81 mg) and atorvastatin (20 mg) daily. The patient was counseled on the possibility of having an ischemic or hemorrhagic stroke. Aspirin and atorvastatin were continued, a neuropsychological evaluation was ordered, and CADASIL genetic counseling and testing were offered to him and his children. Over several years, patients developed several strokes and seizures due to infarcts. He also developed intraparenchymal hemorrhage complicated by dysphagia, requiring a feeding tube. Due to his severe physical debility, he was discharged to a nursing home for rehabilitation, where he did not improve with therapy and remained bedbound. He was discharged and sent home with his family. CADASIL can present as a diagnostic challenge due to its common presentation with migraines, transient ischemic attacks, and strokes, with or without risk factors. This unique presentation of CADASIL with facial palsy highlights the importance of emerging atypical presentations and the need for a detailed history of neuroimaging, family history, and personal history of neurovascular events. By accurately diagnosing the condition, patients and families can be counseled on the disease course and genetics. Management requires a multidisciplinary approach with neurology, genetic counseling, physical therapy, psychology, and psychiatry if depression or anxiety is present, with the aim of improving the patient's quality of life., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2024, Jain et al.)

Objectives: We aimed to identify clinical and EEG monitoring characteristics associated with generalized, lateralized, and bilateral-independent periodic discharges (GPDs, LPDs, and BIPDs) and to determine which patterns were associated with outcomes in critically ill children., Methods: We performed a prospective observational study of consecutive critically ill children undergoing continuous EEG monitoring, including standardized scoring of GPDs, LPDs, and BIPDs. We identified variables associated with GPDs, LPDs, and BIPDs and assessed whether each pattern was associated with hospital discharge outcomes including the Glasgow Outcome Scale-Extended Pediatric version (GOS-E-Peds), Pediatric Cerebral Performance Category (PCPC), and mortality., Results: PDs occurred in 7% (91/1,399) of subjects. Multivariable logistic regression indicated that patients with coma (odds ratio [OR], 3.45; 95% confidence interval [CI]: 1.55, 7.68) and abnormal EEG background category (OR, 6.85; 95% CI: 3.37, 13.94) were at increased risk for GPDs. GPDs were associated with mortality (OR, 3.34; 95% CI: 1.24, 9.02) but not unfavorable GOS-E-Peds (OR, 1.93; 95% CI: 0.88, 4.23) or PCPC (OR, 1.64; 95% CI: 0.75, 3.58). Patients with acute nonstructural encephalopathy did not experience LPDs, and LPDs were not associated with mortality or unfavorable outcomes. BIPDs were associated with mortality (OR, 3.68; 95% CI: 1.14, 11.92), unfavorable GOS-E-Peds (OR, 5.00; 95% CI: 1.39, 18.00), and unfavorable PCPC (OR, 5.96; 95% CI: 1.65, 21.46)., Significance: Patients with coma or more abnormal EEG background category had an increased risk for GPDs and BIPDs, and no patients with an acute nonstructural encephalopathy experienced LPDs. GPDs were associated with mortality and BIPDs were associated with mortality and unfavorable outcomes, but LPDs were not associated with unfavorable outcomes., (Copyright © 2022 by the American Clinical Neurophysiology Society.)

Purpose: Continuous EEG monitoring (CEEG) to identify electrographic seizures (ES) in critically ill children is resource intense. Targeted strategies could enhance implementation feasibility. We aimed to validate previously published findings regarding the optimal CEEG duration to identify ES in critically ill children., Methods: This was a prospective observational study of 1,399 consecutive critically ill children with encephalopathy. We validated the findings of a multistate survival model generated in a published cohort ( N = 719) in a new validation cohort ( N = 680). The model aimed to determine the CEEG duration at which there was <15%, <10%, <5%, or <2% risk of experiencing ES if CEEG were continued longer. The model included baseline clinical risk factors and emergent EEG risk factors., Results: A model aiming to determine the CEEG duration at which a patient had <10% risk of ES if CEEG were continued longer showed similar performance in the generation and validation cohorts. Patients without emergent EEG risk factors would undergo 7 hours of CEEG in both cohorts, whereas patients with emergent EEG risk factors would undergo 44 and 36 hours of CEEG in the generation and validation cohorts, respectively. The <10% risk of ES model would yield a 28% or 64% reduction in CEEG hours compared with guidelines recommending CEEG for 24 or 48 hours, respectively., Conclusions: This model enables implementation of a data-driven strategy that targets CEEG duration based on readily available clinical and EEG variables. This approach could identify most critically ill children experiencing ES while optimizing CEEG use., Competing Interests: N. S. Abend: Funding from NIH (NINDS) K02NS096058 and Wolfson Foundation for this study. Other funding from PCORI (to institution), UCB Pharma (to institution), Epilepsy Foundation (consulting), and Demos Publishing (royalties). The remaining authors have no funding or conflicts of interest to disclose., (Copyright © 2022 by the American Clinical Neurophysiology Society.)

Background: Transgender healthcare is a rapidly evolving interdisciplinary field. In the last decade, there has been an unprecedented increase in the number and visibility of transgender and gender diverse (TGD) people seeking support and gender-affirming medical treatment in parallel with a significant rise in the scientific literature in this area. The World Professional Association for Transgender Health (WPATH) is an international, multidisciplinary, professional association whose mission is to promote evidence-based care, education, research, public policy, and respect in transgender health. One of the main functions of WPATH is to promote the highest standards of health care for TGD people through the Standards of Care (SOC). The SOC was initially developed in 1979 and the last version (SOC-7) was published in 2012. In view of the increasing scientific evidence, WPATH commissioned a new version of the Standards of Care, the SOC-8. Aim: The overall goal of SOC-8 is to provide health care professionals (HCPs) with clinical guidance to assist TGD people in accessing safe and effective pathways to achieving lasting personal comfort with their gendered selves with the aim of optimizing their overall physical health, psychological well-being, and self-fulfillment. Methods: The SOC-8 is based on the best available science and expert professional consensus in transgender health. International professionals and stakeholders were selected to serve on the SOC-8 committee. Recommendation statements were developed based on data derived from independent systematic literature reviews, where available, background reviews and expert opinions. Grading of recommendations was based on the available evidence supporting interventions, a discussion of risks and harms, as well as the feasibility and acceptability within different contexts and country settings. Results: A total of 18 chapters were developed as part of the SOC-8. They contain recommendations for health care professionals who provide care and treatment for TGD people. Each of the recommendations is followed by explanatory text with relevant references. General areas related to transgender health are covered in the chapters Terminology, Global Applicability, Population Estimates, and Education. The chapters developed for the diverse population of TGD people include Assessment of Adults, Adolescents, Children, Nonbinary, Eunuchs, and Intersex Individuals, and people living in Institutional Environments. Finally, the chapters related to gender-affirming treatment are Hormone Therapy, Surgery and Postoperative Care, Voice and Communication, Primary Care, Reproductive Health, Sexual Health, and Mental Health. Conclusions: The SOC-8 guidelines are intended to be flexible to meet the diverse health care needs of TGD people globally. While adaptable, they offer standards for promoting optimal health care and guidance for the treatment of people experiencing gender incongruence. As in all previous versions of the SOC, the criteria set forth in this document for gender-affirming medical interventions are clinical guidelines; individual health care professionals and programs may modify these in consultation with the TGD person., Competing Interests: Conflict of interests were reviewed as part of the selection process for committee members and at the end of the process before publication. No conflicts of interest were deemed significant or consequential., (© 2022 The Author(s). Published with license by Taylor & Francis Group, LLC.)

Purpose: We implemented a video ambulatory EEG (VA-EEG) Program as an alternative to inpatient video EEG monitoring for some patients given potential benefits related to quicker access, greater convenience, and lower cost. To evaluate the newly initiated program, we performed a quality improvement study to assess whether VA-EEG yielded studies with interpretable EEG and video quality that generated clinically beneficial data., Methods: This was a single-center prospective quality improvement study. We surveyed ordering clinicians, electroencephalographers, and caregivers regarding consecutive children who underwent clinically indicated VA-EEG. The primary outcome was the percentage of VA-EEG studies in which the ordering clinician reported that the study had answered the question of interest., Results: We evaluated 74 consecutive children selected to undergo clinically indicated VA-EEG by their clinicians and caregivers. Ordering clinicians reported that 77% of studies answered the question of interest. Electroencephalographers reported that the quality of the EEG and video was excellent or adequate in 100% and 92% of patients, respectively. Additionally, 84% of caregivers reported preferring VA-EEG if EEG data were needed in the future., Conclusions: Video ambulatory EEG may be an effective diagnostic modality among children selected by clinicians and caregivers to undergo long-term EEG monitoring. Given it is effective as well as convenient, accessible, and lower cost than inpatient EEG monitoring, all of which align with our institution's quality goals, we intend to expand our VA-EEG Program., Competing Interests: The authors have no funding or conflicts of interest to disclose., (Copyright © 2020 by the American Clinical Neurophysiology Society.)

Objectives: We aimed to determine the incidence of periodic and rhythmic patterns (PRP), assess the interrater agreement between electroencephalographers scoring PRP using standardized terminology, and analyze associations between PRP and electrographic seizures (ES) in critically ill children., Methods: This was a prospective observational study of consecutive critically ill children undergoing continuous electroencephalographic monitoring (CEEG). PRP were identified by one electroencephalographer, and then two pediatric electroencephalographers independently scored the first 1-h epoch that contained PRP using standardized terminology. We determined the incidence of PRPs, evaluated interrater agreement between electroencephalographers scoring PRP, and evaluated associations between PRP and ES., Results: One thousand three hundred ninety-nine patients underwent CEEG. ES occurred in 345 (25%) subjects. PRP, ES + PRP, and ictal-interictal continuum (IIC) patterns occurred in 142 (10%), 81 (6%), and 93 (7%) subjects, respectively. The most common PRP were generalized periodic discharges (GPD; 43, 30%), lateralized periodic discharges (LPD; 34, 24%), generalized rhythmic delta activity (GRDA; 34, 24%), bilateral independent periodic discharges (BIPD; 14, 10%), and lateralized rhythmic delta activity (LRDA; 11, 8%). ES risk varied by PRP type (p < .01). ES occurrence was associated with GPD (odds ratio [OR] = 6.35, p < .01), LPD (OR = 10.45, p < .01), BIPD (OR = 6.77, p < .01), and LRDA (OR = 6.58, p < .01). Some modifying features increased the risk of ES for each of those PRP. GRDA was not significantly associated with ES (OR = 1.34, p = .44). Each of the IIC patterns was associated with ES (OR = 6.83-8.81, p < .01). ES and PRP occurred within 6 h (before or after) in 45 (56%) subjects., Significance: PRP occurred in 10% of critically ill children who underwent CEEG. The most common patterns were GPD, LPD, GRDA, BIPD, and LRDA. The GPD, LPD, BIPD, LRDA, and IIC patterns were associated with ES. GRDA was not associated with ES., (© 2021 International League Against Epilepsy.)

Objective: To determine the association between electroencephalographic seizure (ES) and electroencephalographic status epilepticus (ESE) exposure and unfavorable neurobehavioral outcomes in critically ill children with acute encephalopathy., Methods: This was a prospective cohort study of acutely encephalopathic critically ill children undergoing continuous EEG monitoring (CEEG). ES exposure was assessed as (1) no ES/ESE, (2) ES, or (3) ESE. Outcomes assessed at discharge included the Glasgow Outcome Scale-Extended Pediatric Version (GOS-E-Peds), Pediatric Cerebral Performance Category (PCPC), and mortality. Unfavorable outcome was defined as a reduction in GOS-E-Peds or PCPC score from preadmission to discharge. Stepwise selection was used to generate multivariate logistic regression models that assessed associations between ES exposure and outcomes while adjusting for multiple other variables., Results: Among 719 consecutive critically ill patients, there was no evidence of ES in 535 patients (74.4%), ES occurred in 140 patients (19.5%), and ESE in 44 patients (6.1%). The final multivariable logistic regression analyses included ES exposure, age dichotomized at 1 year, acute encephalopathy category, initial EEG background category, comatose at CEEG initiation, and Pediatric Index of Mortality 2 score. There was an association between ESE and unfavorable GOS-E-Peds (odds ratio 2.21, 95% confidence interval 1.07-4.54) and PCPC (odds ratio 2.17, 95% confidence interval 1.05-4.51) but not mortality. There was no association between ES and unfavorable outcome or mortality., Conclusions: Among acutely encephalopathic critically ill children, there was an association between ESE and unfavorable neurobehavioral outcomes, but no association between ESE and mortality. ES exposure was not associated with unfavorable neurobehavioral outcomes or mortality., (© 2021 American Academy of Neurology.)

Herein, we describe the discovery and optimization of a novel series that inhibits bacterial DNA gyrase and topoisomerase IV via binding to, and stabilization of, DNA cleavage complexes. Optimization of this series led to the identification of compound 25 , which has potent activity against Gram-positive bacteria, a favorable in vitro safety profile, and excellent in vivo pharmacokinetic properties. Compound 25 was found to be efficacious against fluoroquinolone-sensitive Staphylococcus aureus infection in a mouse thigh model at lower doses than moxifloxacin. An X-ray crystal structure of the ternary complex formed by topoisomerase IV from Klebsiella pneumoniae , compound 25 , and cleaved DNA indicates that this compound does not engage in a water-metal ion bridge interaction and forms no direct contacts with residues in the quinolone resistance determining region (QRDR). This suggests a structural basis for the reduced impact of QRDR mutations on antibacterial activity of 25 compared to fluoroquinolones.

Objective: To determine whether machine learning techniques would enhance our ability to incorporate key variables into a parsimonious model with optimized prediction performance for electroencephalographic seizure (ES) prediction in critically ill children., Methods: We analyzed data from a prospective observational cohort study of 719 consecutive critically ill children with encephalopathy who underwent clinically-indicated continuous EEG monitoring (CEEG). We implemented and compared three state-of-the-art machine learning methods for ES prediction: (1) random forest; (2) Least Absolute Shrinkage and Selection Operator (LASSO); and (3) Deep Learning Important FeaTures (DeepLIFT). We developed a ranking algorithm based on the relative importance of each variable derived from the machine learning methods., Results: Based on our ranking algorithm, the top five variables for ES prediction were: (1) epileptiform discharges in the initial 30 minutes, (2) clinical seizures prior to CEEG initiation, (3) sex, (4) age dichotomized at 1 year, and (5) epileptic encephalopathy. Compared to the stepwise selection-based approach in logistic regression, the top variables selected by our ranking algorithm were more informative as models utilizing the top variables achieved better prediction performance evaluated by prediction accuracy, AUROC and F1 score. Adding additional variables did not improve and sometimes worsened model performance., Conclusion: The ranking algorithm was helpful in deriving a parsimonious model for ES prediction with optimal performance. However, application of state-of-the-art machine learning models did not substantially improve model performance compared to prior logistic regression models. Thus, to further improve the ES prediction, we may need to collect more samples and variables that provide additional information., (Copyright © 2021. Published by Elsevier Ltd.)

Objective: Electroencephalographic seizures (ESs) are common in encephalopathic critically ill children, but identification requires extensive resources for continuous electroencephalographic monitoring (CEEG). In a previous study, we developed a clinical prediction rule using three clinical variables (age, acute encephalopathy category, clinically evident seizure[s] prior to CEEG initiation) and two electroencephalographic (EEG) variables (EEG background category and interictal discharges within the first 30 minutes of EEG) to identify patients at high risk for ESs for whom CEEG might be essential. In the current study, we aimed to validate the ES prediction model using an independent cohort., Methods: The prospectively acquired validation cohort consisted of 314 consecutive critically ill children treated in the Pediatric Intensive Care Unit of a quaternary care referral hospital with acute encephalopathy undergoing clinically indicated CEEG. We calculated test characteristics using the previously developed prediction model in the validation cohort. As in the generation cohort study, we selected a 0.10 cutpoint to emphasize sensitivity., Results: The incidence of ESs in the validation cohort was 22%. The generation and validation cohorts were alike in most clinical and EEG characteristics. The ES prediction model was well calibrated and well discriminating in the validation cohort. The model had a sensitivity of 90%, specificity of 37%, positive predictive value of 28%, and negative predictive value of 93%. If applied, the model would limit 31% of patients from undergoing CEEG while failing to identify 10% of patients with ESs. The model had similar performance characteristics in the generation and validation cohorts., Significance: A model employing five readily available clinical and EEG variables performed well when validated in a new consecutive cohort. Implementation would substantially reduce CEEG utilization, although some patients with ESs would not be identified. This model may serve a critical role in targeting limited CEEG resources to critically ill children at highest risk for ESs., (© 2020 International League Against Epilepsy.)

Objectives: To determine the optimal duration of continuous EEG monitoring (CEEG) for electrographic seizure (ES) identification in critically ill children., Methods: We performed a prospective observational cohort study of 719 consecutive critically ill children with encephalopathy. We evaluated baseline clinical risk factors (age and prior clinically evident seizures) and emergent CEEG risk factors (epileptiform discharges and ictal-interictal continuum patterns) using a multistate survival model. For each subgroup, we determined the CEEG duration for which the risk of ES was <5% and <2%., Results: ES occurred in 184 children (26%). Patients achieved <5% risk of ES after (1) 6 hours if ≥1 year without prior seizures or EEG risk factors; (2) 1 day if <1 year without prior seizures or EEG risks; (3) 1 day if ≥1 year with either prior seizures or EEG risks; (4) 2 days if ≥1 year with prior seizures and EEG risks; (5) 2 days if <1 year without prior seizures but with EEG risks; and (6) 2.5 days if <1 year with prior seizures regardless of the presence of EEG risks. Patients achieved <2% risk of ES at the same durations except patients without prior seizures or EEG risk factors would require longer CEEG (1.5 days if <1 year of age, 1 day if ≥1 year of age)., Conclusions: A model derived from 2 baseline clinical risk factors and emergent EEG risk factors would allow clinicians to implement personalized strategies that optimally target limited CEEG resources. This would enable more widespread use of CEEG-guided management as a potential neuroprotective strategy., Clinicaltrialsgov Identifier: NCT03419260., (© 2020 American Academy of Neurology.)