We describe a COVID-19 patient with acute hyperhidrosis and symptomatic orthostatic tachycardia. We encountered 3 other patients with ophthalmic dysautonomia. We posit COVID-19 as a cause of acute, limited, possibly dysimmune, autonomic dysfunction.A 39-year-old man, a construction worker with no medical history, was diagnosed with COVID-19 from nasopharyngeal swab reverse transcription polymerase chain reaction (rt-PCR) when he presented with 8 days of acute respiratory symptoms, diarrhea, abdominal discomfort and pneumonia. Within 2 days‚ he required supplemental oxygen and prone-positioning, and was placed on a remdesivir trial. He recovered without ventilatory support. His blood pressure at admission was 165/92 mmHg. In hospital‚ it ranged from 130 to 170/80-110 mmHg. He was started on amlodipine 2.5 mg. His blood glucose ranged from 9 to 13 mmol/L and HbA1c was 8.8%. He was diagnosed with diabetes mellitus (DM) and given insulin and metformin.At day 13 of illness, as he was recuperating in the general ward with stable blood pressure and parameters, he developed right leg ischemia. Computed tomography (CT) aortogram showed a mural thrombus at the suprarenal aorta.
Computer-assisted measurement of erosion volume has good performance metrics. It had excellent intrareader and interreader reliability and was more sensitive to change than RAMRIS in this group of patients. www.ClinicalTrials.gov, NCT00451971.
Introduction: Detection of atrial fibrillation (AF) is challenging in patients after ischemic stroke due to its paroxysmal nature. We aim to determine the utility of a combined clinical, electrocardiographic and genetic variables model to predict AF in a post-stroke population.
Materials and Methods: We performed a cohort study at a single comprehensive stroke centre from 09/11/2009 to 31/10/2017. All patients recruited were diagnosed with acute ischemic stroke or transient ischemic attacks. Electrocardiographic variables including p-wave terminal force (PWTF), corrected QT interval (QTc) and genetic variables including single nucleotide polymorphisms (SNP) at the 4q25 (rs2200733) were evaluated. Clinical, electrocardiographic and genetic variables of patients without AF and those who developed AF were compared. Multiple logistic regression analysis and receiver operating characteristics were performed to identify parameters and determine their ability to predict the occurrence of AF.
Results: Out of 709 patients (median age of 59 years, IQR 52-67) recruited, sixty (8.5%) were found to develop AF on follow-up. Age (odds ratio (OR): 3.49, 95% confidence interval (CI): 2.03-5.98, p<0.0001), hypertension (OR: 2.76, 95% CI: 1.36-5.63, p=0.0052) and valvular heart disease (OR: 8.49, 95% CI: 2.62-27.6, p<0.004 were the strongest predictors of AF, with area under receiver operating value of 0.76 (95% CI: 0.70-0.82), and 0.82 (95% CI: 0.77-0.87) when electrocardiographic variables (PWTF and QTc) were added. SNP did not improve prediction modelling.
Conclusion: We demonstrated that a model combining clinical and electrocardiographic variables provided robust prediction of AF in our post-stroke population. Role of SNP in prediction of AF was limited.
Anti-leucine-rich glioma-inactivated 1 (LGI1) encephalitis can present with faciobrachial dystonic seizures (FBDS), with a subset of patients showing associated basal ganglia (BG) abnormalities on magnetic resonance imaging (MRI). 1,2 It is important to recognize these MRI features as a good response to immunotherapy can be achieved and early treatment may prevent subsequent cognitive impairment. 3 Herein, we present two patients with anti-LGI1 encephalitis who developed 'infarct-like' BG MRI changes, one did not have FBDS, whereas the other developed FBDS 2 months after initial presentation.
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