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Obstructive sleep apnea (OSA) is a prevalent respiratory condition in children and is characterized by partial or complete obstruction of the upper airway during sleep. The respiratory events in OSA induce transient alterations of the cardiovascular system that ultimately can lead to increased cardiovascular risk in affected children. Therefore, a timely and accurate diagnosis is of utmost importance. However, polysomnography (PSG), the standard diagnostic test for pediatric OSA, is complex, uncomfortable, costly, and relatively inaccessible, particularly in low-resource environments, thereby resulting in substantial underdiagnosis. Here, we propose a novel deep-learning approach to simplify the diagnosis of pediatric OSA using raw electrocardiogram tracing (ECG). Specifically, a new convolutional neural network (CNN)-based regression model was implemented to automatically predict pediatric OSA by estimating its severity based on the apnea-hypopnea index (AHI) and deriving 4 OSA severity categories. For this purpose, overnight ECGs from 1,610 PSG recordings obtained from the Childhood Adenotonsillectomy Trial (CHAT) database were used. The database was randomly divided into approximately 60%, 20%, and 20% for training, validation, and testing, respectively. The diagnostic performance of the proposed CNN model largely outperformed the most accurate previous algorithms that relied on ECG-derived features (4-class Cohen's kappa coefficient of 0.373 versus 0.166). Specifically, for AHI cutoff values of 1, 5, and 10 events/hour, the binary classification achieved sensitivities of 84.19%, 76.67%, and 53.66%; specificities of 46.15%, 91.39%, and 98.06%; and accuracies of 75.92%, 86.96%, and 91.97%, respectively. Therefore, pediatric OSA can be readily identified by our proposed CNN model, which provides a simpler, faster, and more accessible diagnostic test that can be implemented in clinical practice., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

A case of orbital metastasis from Whitmore stage D adenocarcinoma of the prostate is described. Clinically, it presented as rapidly progressing exophthalmos of the right eye with elevation (ptosis) and abduction paralysis. The associated clinical picture of a one-year history of prostatism prompted patient referral to our department. When a patient presents with an orbital tumor and a history of cancer localized to another site, the metastatic origin of the condition should be suspected and metastasis to other sites sought. A negative finding warrants performing orbital biopsy to confirm the diagnosis. Although excision of single metastatic tumors in this site has been described, coexisting metastasis to bone and lymph nodes, the hormone dependence that these present and prostatic cancer contraindicate resection of the orbital metastatic tumor. Following bilateral orchiectomy and hormone therapy with antiandrogens micturitional symptomatology improved, tumor size was reduced, and exophthalmos disappeared. The case described herein is not the first case of this type of metastatic lesion reported in the literature; 28 cases have been reported to date. This uncommon clinical presentation with extraurological manifestations gives us an idea of the broad clinical spectrum the biological behaviour of this tumor type can adopt.