Objective: To describe the imaging and clinical features in type II (late-onset) Alexander disease (AxD).
Methods: We retrospectively identified all cases of type II AxD evaluated at Mayo Clinic, Rochester from January 1996 to February 2012. Clinical and neuroimaging data abstracted from the record included age at onset of symptoms, age at diagnosis, first symptom, neurologic symptoms, physical/neurologic findings on examination, genetic testing and/or biopsy (if performed), and MRI findings.
Results: Thirteen patients with type II AxD were identified. Median age at onset was 38 years (range: 12-63). Five patients were female. Eleven of 13 patients had atrophy of the medulla while all 13 had medullary T2 hyperintensity. In 7 patients, these brainstem regions showed patchy enhancement. Five subjects had T2 signal change in the middle cerebellar peduncle, with associated contrast enhancement in 4 subjects. Eleven of 12 patients with T2 fluid-attenuated inversion recovery (FLAIR) imaging had pial FLAIR signal change in the medulla. Nine of 12 patients with spinal cord imaging had cord atrophy, and 3 of 9 of these evaluated with contrast had cervical cord enhancement.
Conclusions: Our study confirms prior reports of atrophy and signal change of the medulla and spinal cord in late-onset AxD. We expand on previous imaging studies by identifying middle cerebellar peduncle and pial FLAIR signal changes as important diagnostic clues. Variable patchy enhancement may occur in regions of T2 hyperintensity, leading to diagnostic uncertainty. In addition, we demonstrate that previously emphasized clinical features such as palatal tremor may not be common. We affirm that age at onset predicts clinical phenotype and imaging findings.
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http://dx.doi.org/10.1212/01.wnl.0000438230.33223.bc | DOI Listing |
J Infect Dev Ctries
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Chest Dpt., Ahmed Maher Teaching Hospital, GOTHI, Cairo, Egypt.
Introduction: The present study aimed to explore the epidemiologic threats and factors associated with the coronavirus disease 2019 (COVID-19)-associated mucormycosis (CAM) epidemic that emerged in Egypt during the second COVID-19 wave. The study also aimed to explore the diagnostic features and the role of surgical interventions of CAM on the outcome of the disease in a central referral hospital.
Methodology: The study included 64 CAM patients from a referral hospital for CAM and a similar number of matched controls from COVID-19 patients who did not develop CAM.
J Infect Dev Ctries
December 2024
Nephrology Department, UHC Mother Tereza, Tirane, Albania.
Introduction: Acute kidney injury involves inflammation and intrinsic renal damage, and is a common complication of severe coronavirus disease 2019 (COVID-19). Baseline chronic kidney disease (CKD) confers an increased mortality risk. We determined the renal long-term outcomes of COVID-19 in patients with baseline CKD, and the risk factors prompting renal replacement therapy (RRT) initiation and mortality.
View Article and Find Full Text PDFJ Med Case Rep
January 2025
Department of Dermatology and Venereology, Faculty of Medicine, University of Aleppo, Aleppo, Syria.
Background: Basal cell nevus syndrome, also known as Gorlin or Gorlin-Goltz syndrome, is a hereditary condition caused by mutation in the PATCHED gene. The syndrome presents with a wide range of clinical manifestations, including basal cell carcinomas, jaw cysts, and skeletal anomalies. Diagnosis is based on specific criteria, and treatment typically includes surgical removal of basal cell carcinomas.
View Article and Find Full Text PDFClin Epigenetics
January 2025
Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Alcohol consumption is an important risk factor for multiple diseases. It is typically assessed via self-report, which is open to measurement error through recall bias. Instead, molecular data such as blood-based DNA methylation (DNAm) could be used to derive a more objective measure of alcohol consumption by incorporating information from cytosine-phosphate-guanine (CpG) sites known to be linked to the trait.
View Article and Find Full Text PDFNPJ Digit Med
January 2025
Graduate School of Data Science, Seoul National University, Seoul, Republic of Korea.
Polysomnography (PSG) is crucial for diagnosing sleep disorders, but manual scoring of PSG is time-consuming and subjective, leading to high variability. While machine-learning models have improved PSG scoring, their clinical use is hindered by the 'black-box' nature. In this study, we present SleepXViT, an automatic sleep staging system using Vision Transformer (ViT) that provides intuitive, consistent explanations by mimicking human 'visual scoring'.
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