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Background: Prediction tools without patient-reported symptoms could facilitate widespread identification of OSA., Research Question: What is the diagnostic performance of OSA prediction tools derived from machine learning using readily available data without patient responses to questionnaires? Also, how do they compare with STOP-BANG, an OSA prediction tool, in clinical and community-based samples?, Study Design and Methods: Logistic regression and machine learning techniques, including artificial neural network (ANN), random forests (RF), and kernel support vector machine, were used to determine the ability of age, sex, BMI, and race to predict OSA status. A retrospective cohort of 17,448 subjects from sleep clinics within the international Sleep Apnea Global Interdisciplinary Consortium (SAGIC) were randomly split into training (n = 10,469) and validation (n = 6,979) sets. Model comparisons were performed by using the area under the receiver-operating curve (AUC). Trained models were compared with the STOP-BANG questionnaire in two prospective testing datasets: an independent clinic-based sample from SAGIC (n = 1,613) and a community-based sample from the Sleep Heart Health Study (n = 5,599)., Results: The AUCs (95% CI) of the machine learning models were significantly higher than logistic regression (0.61 [0.60-0.62]) in both the training and validation datasets (ANN, 0.68 [0.66-0.69]; RF, 0.68 [0.67-0.70]; and kernel support vector machine, 0.66 [0.65-0.67]). In the SAGIC testing sample, the ANN (0.70 [0.68-0.72]) and RF (0.70 [0.68-0.73]) models had AUCs similar to those of the STOP-BANG (0.71 [0.68-0.72]). In the Sleep Heart Health Study testing sample, the ANN (0.72 [0.71-0.74]) had AUCs similar to those of STOP-BANG (0.72 [0.70-0.73])., Interpretation: OSA prediction tools using machine learning without patient-reported symptoms provide better diagnostic performance than logistic regression. In clinical and community-based samples, the symptomless ANN tool has diagnostic performance similar to that of a widely used prediction tool that includes patient symptoms. Machine learning-derived algorithms may have utility for widespread identification of OSA., (Copyright © 2021 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)

Background: Anti-NMDA receptor encephalitis (ANRE) is a rare autoimmune neurologic disorder characterized by encephalitis and a constellational of symptoms, including seizures, psychiatric disturbances, autonomic instability, and respiratory insufficiency. It is caused by the anti-NMDA receptor antibody. The most common etiologies for ANRE include malignancy and infection. Ovarian teratoma is the most commonly associated malignancy., Case Description: We describe the first reported case to our knowledge of ovarian teratoma causing ANRE resulting in nonconvulsive status epilepticus (NCSE), which was terminated with vagus nerve stimulation (VNS)., Conclusions: This case report provides a temporal correlation suggesting that VNS significantly altered the natural history of this patient's NCSE-ANRE. As more data are collected, and the VNS treatment modality more liberally used to treat NCSE, especially in the situation of ANRE, stronger layers of evidence will emerge to fill the gaps of understanding beyond this case report., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Extreme phenotypes of OSA have not been systematically defined., Research Question: This study developed objective definitions of extreme phenotypes of OSA by using a multivariate approach. The utility of these definitions for identifying characteristics that confer predisposition toward or protection against OSA is shown in a new prospective sample., Study Design and Methods: In a large international sample, race-specific liability scores were calculated from a weighted logistic regression that included age, sex, and BMI. Extreme cases were defined as individuals with an apnea-hypopnea index (AHI) ≥ 30 events/hour but low likelihood of OSA based on age, sex, and BMI (liability scores > 90th percentile). Similarly, extreme controls were individuals with an AHI < 5 events/hour but high likelihood of OSA (liability scores < 10th percentile). Definitions were applied to a prospective sample from the Sleep Apnea Global Interdisciplinary Consortium, and differences in photography-based craniofacial and intraoral phenotypes were evaluated., Results: This study included retrospective data from 81,338 individuals. A total of 4,168 extreme cases and 1,432 extreme controls were identified by using liability scores. Extreme cases were younger (43.1 ± 14.7 years), overweight (28.6 ± 6.8 kg/m 2 ), and predominantly female (71.1%). Extreme controls were older (53.8 ± 14.1 years), obese (34.0 ± 8.1 kg/m 2 ), and predominantly male (65.8%). These objective definitions identified 29 extreme cases and 87 extreme controls among 1,424 Sleep Apnea Global Interdisciplinary Consortium participants with photography-based phenotyping. Comparisons suggest that a greater cervicomental angle increases risk for OSA in the absence of clinical risk factors, and smaller facial widths are protective in the presence of clinical risk factors., Interpretation: This objective definition can be applied in sleep centers throughout the world to consistently define OSA extreme phenotypes for future studies on genetic, anatomic, and physiologic pathways to OSA., (Copyright © 2020 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)

Cataract, opacification of the lens, is one of the commonest causes of loss of useful vision, with an estimated 16 million people worldwide affected. Several risk factors have been identified in addition to increasing age--genetic composition, exposure to ultraviolet light, and diabetes. However, no method to halt the formation of a cataractous lens has been shown to be effective. Nevertheless, advances in surgical removal of cataracts, including small-incision surgery, use of viscoelastics, and the development of intraocular lenses, have made treatment very effective and visual recovery rapid in most cases. Despite these advances, cataract continues to be a leading public-health issue that will grow in importance as the population increases and life expectancy is extended worldwide.

Fifty-four subjects with initial intraocular pressures under 20 mm Hg received a different commercial corticosteroid ester of prednisolone or dexamethasone in each eye for three to six weeks. Compliance was controlled. The intraocular pressure responses of the two eyes of a subject were similar. It was concluded that the absorptions of all four corticosteroids were in excess of the minimum amounts needed to maximally elevate pressure. Subjects complained that prednisolone acetate was irritating. Corticosteroid-induced uveitis developed in 3% (3) of the eyes.

Succinyldicholine 2 mg/kg body weight returned the eyes of 20 anesthetized subjects to the same basic horizontal position as when conscious. The distance between the two eyes, as measured from motion pictures, agreed when the patient was in the conscious state and succinyldicholine-stimulated unconscious state by 99 +/- 10%. Since succinyldicholine has been shown by others to selectively produce a sustained contraction of en grappe muscle fibers, these muscle fibers are implicated as determinants of the basic ocular position and a cause of strabismus.