Objectives A significant proportion of COVID‐19 patients may have cardiac involvement including arrhythmias. Although arrhythmia characterisation and possible predictors were previously reported, there are conflicting data regarding the exact prevalence of arrhythmias. Clinically applicable algorithms to classify COVID patients' arrhythmic risk are still lacking, and are the aim of our study. Methods We describe a single‐centre cohort of hospitalised patients with a positive nasopharyngeal swab for COVID‐19 during the initial Israeli outbreak between 1/2/2020 and 30/5/2020. The study's outcome was any documented arrhythmia during hospitalisation, based on daily physical examination, routine ECG's, periodic 24‐hour Holter, and continuous monitoring. Multivariate analysis was used to find predictors for new arrhythmias and create classification trees for discriminating patients with high and low arrhythmic risk. Results Out of 390 COVID‐19 patients included, 28 (7.2%) had documented arrhythmias during hospitalisation, including 23 atrial tachyarrhythmias, combined atrial fibrillation (AF), and ventricular fibrillation, ventricular tachycardia storm, and 3 bradyarrhythmias. Only 7/28 patients had previous arrhythmias. Our study showed a significant correlation between disease severity and arrhythmia prevalence (P < .001) with a low arrhythmic prevalence amongst mild disease patients (2%). Multivariate analysis revealed background heart failure (CHF) and disease severity are independently associated with overall arrhythmia while age, CHF, disease severity, and arrhythmic symptoms are associated with tachyarrhythmias. A novel decision tree using age, disease severity, CHF, and troponin levels was created to stratify patients into high and low risk for developing arrhythmia. Conclusions Dominant arrhythmia amongst COVID‐19 patients is AF. Arrhythmia prevalence is associated with age, disease severity, CHF, and troponin levels. A novel simple Classification tree, based on these parameters, can discriminate between high and low arrhythmic risk patients.

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Background: Papillary thyroid carcinoma is the most common thyroid cancer (85%). Follicular thyroid carcinoma is the second most common type of thyroid cancer, accounting for up to 10% of all thyroid cancers. Medullary thyroid carcinoma accounts for only 5-8% of thyroid cancers. Concurrent medullary, follicular, and papillary carcinomas of the thyroid gland are extremely rare and reported scarcely. Case Report: A 72-year-old male presented with nonspecific neck pain. The workup revealed a nodular thyroid gland with a follicular lesion on fine-needle aspiration. Total thyroidectomy was performed and pathological examination identified a 25-mm follicular carcinoma, two papillary microcarcinomas, and two medullary microcarcinomas. The genetic workup was negative and no other family members were diagnosed with any endocrinopathy. Two months after surgery, the patient was diagnosed with Cushing's syndrome that was treated with laparoscopic left adrenalectomy. On 3-year follow-up, the patient is asymptomatic with no evidence of recurrent disease. Conclusion: We present a rare case of a patient with follicular, papillary, and medullary thyroid carcinoma, and Cushing's syndrome. To date, no known genetic mutation or syndrome can account for this combination of neoplastic thyroid and adrenal pathologies, although future research may prove differently.

Purpose To characterize which clinical features are associated with the occurrence of atypical birefringence patterns (ABP) occasionally seen with scanning laser polarimetry (SLP). Methods Sixty-one subjects, including glaucoma patients, glaucoma suspects, and normal subjects, underwent a full clinical examination, standard visual field (VF) test, and a GDx-VCC SLP examination. One eye was selected from each patient. The magnitude of ABP was determined in two independent ways: using a support vector machine analysis (typical scan score (TSS)) and by a masked experienced observer. We assessed whether the magnitude of ABP was correlated with age, gender, the refractive state of the eye, corneal polarization axis and magnitude, GDx global parameters (TSNIT and NFI), and the VF status, as evident from glaucoma hemifield test (GHT), mean deviation (MD), and the pattern standard deviation (PSD). Results Of the 61 study eyes, 27 (44%) showed an ABP, based on a TSS cutoff (o82.5). A very high correlation was found between the TSS score and the masked experienced observer score (r 2 ¼ 0.80; Po0.001). The following clinical parameters were found, on bivariate analysis, to be significantly correlated with the presence of an ABP: age (r 2 ¼ 0.086; P ¼ 0.02); corneal polarization magnitude (r 2 ¼ 0.069; P ¼ 0.04); TSNIT (r 2 ¼ 0.16; Po0.001). Conclusion The presence and magnitude of ABP did not seem to be closely correlated with most clinical parameters. A low, but statistically significant, correlation was found for age and corneal polarization magnitude (r 2 ¼ 0.086 and 0.069, respectively). A lowmedium correlation was found for TSNIT (r 2 ¼ 0.16); however, we speculate that this might represent a confounding effect, rather than an underlying association. We conclude that none of the clinical parameters investigated in this study appears to be strongly correlated with the presence of an ABP on SLP scans performed using the commercially available GDx-VCC.

Objectives: A significant proportion of COVID-19 patients may have cardiac involvement including arrhythmias. Although arrhythmia characterization and possible predictors were previously reported, there are conflicting data regarding the exact prevalence of arrhythmias. Clinically applicable algorithms to classify COVID patients' arrhythmic risk are still lacking, and are the aim of our study. Methods: We describe a single center cohort of hospitalized patients with a positive nasopharyngeal swab for COVID-19 during the initial Israeli outbreak between 1/2/2020-30/5/2020. The study's outcome was any documented arrhythmia during hospitalization, based on daily physical examination, routine ECG's, periodic 24-hour Holter, and continuous monitoring. Multivariate analysis was used to find predictors for new arrhythmias and create classification trees for discriminating patients with high and low arrhythmic risk. Results: Out of 390 COVID-19 patients included, 28 (7.2%) had documented arrhythmias during hospitalization, including: 23 atrial tachyarrhythmias, combined atrial fibrillation (AF) and ventricular fibrillation, ventricular tachycardia storm, and 3 bradyarrhythmias. Only 7/28 patients had previous arrhythmias. Our study showed significant correlation between disease severity and arrhythmia prevalence (p<0.001) with a low arrhythmic prevalence among mild disease patients (2%). Multivariate analysis revealed background heart failure (CHF) and disease severity are independently associated with overall arrhythmia while age, CHF, disease severity, and arrhythmic symptoms are associated with tachyarrhythmias. A novel decision tree using age, disease severity, CHF, and troponin levels was created to stratify patients into high and low risk for developing arrhythmia. Conclusions: Dominant arrhythmia among COVID-19 patients is AF. Arrhythmia prevalence is dependent on age, disease severity, CHF, and troponin levels. A novel simple Classification tree, based on these parameters, can discriminate between high and low arrhythmic risk patients. WHAT'S KNOWN? • A significant proportion of COVID-19 patients may have cardiac involvement including arrhythmias. • There is a correlation between disease severity in general and cardiac involvement specifically to occurrence of cardiac arrhythmias. • Arrhythmia characterization and possible predictors. WHAT'S NEW? • Using a 24-hour Holter monitoring among hospitalized COVID-19 patients, for better arrythmias detection. • Among of all hospitalized COVID-19 patients, 7.2% had new arrhythmias during hospitalization. • Classification tree which discriminate between high and low arrhythmic risk patients