Background: Skeletal muscle weakness with loss of fat-free mass (FFM) is one of the main systemic effects of chronic obstructive pulmonary disease (COPD). The diaphragm is also involved, leading to disadvantageous conditions and poor contractile capacities. Objectives: We measured the thickness of the diaphragm (TD) by ultrasonography to evaluate the relationships between echographic measurements, parameters of respiratory function and body composition data. Methods: Thirty-two patients (23 males) underwent (1) pulmonary function tests, (2) echographic assessment of TD in the zone of apposition at various lung volumes, i.e. TD at residual volume (TDRV), TD at functional residual capacity (TDFRC) and TD at total lung capacity (TDTLC), and (3) bioelectrical body impedance analysis. The BMI and the BODE (BMI-Obstruction-Dyspnea-Exercise) index values were reported. Results: TDRV, TDFRC and TDTLC measured 3.3, 3.6 and 6 mm, respectively, with good intraobserver reproducibility (0.97, 0.97 and 0.96, respectively). All the TDs were found to be related to FFM, with the relationship being greater for TDFRC (r² = 0.39 and p = 0.0002). With regard to lung volumes, inspiratory capacity (IC) was found to be closely related to TDTLC (r² = 0.42 and p = 0.0001). The difference between TDTLC and TDRV, as a thickening value (TDTLCRV), was closely related to FVC (r² = 0.34 and p = 0.0004) and to air-trapping indices (RV/TLC, FRC/TLC and IC/TLC): the degree of lung hyperinflation was greater and the TDTLCRV was less. Finally, we found a progressive reduction of both thicknesses and thickenings as the severity of IC/TLC increased, with a significant p value for the trend in both analyses (p = 0.02). Conclusions: Ultrasonographic assessment of the diaphragm could be a useful tool for studying disease progression in COPD patients, in terms of lung hyperinflation and the loss of FFM.

Coronavirus disease 2019 (COVID-19) is a pandemic infection due to the spread of a novel coronavirus (severe acute respiratory syndrome coronavirus 2), resulting in a wide range of clinical features, from asymptomatic carriers to ARDS. The gold standard for diagnosis is nucleic acid detection by real-time reverse transcriptase-polymerase chain reaction in nasopharyngeal swabs. However, due to limitations in this technique's sensitivity, thoracic imaging plays a crucial, complementary role in diagnostic evaluation and also allows for detection of atypical findings and potential alternative targets for sampling (eg, pleural effusion). Although less common, pleural involvement has been described in a minority of patients. This report describes the first case of reverse transcriptase-polymerase chain reaction detection of severe acute respiratory syndrome coronavirus 2 in pleural fluid obtained by means of ultrasoundguided thoracentesis, and its main characteristics are detailed. Pleural effusion is not a common finding in COVID-19 infection, but a prompt recognition of this potential localization may be useful to optimize diagnostic evaluation as well as the management of these patients.

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Obstructive sleep apnea (OSA) has a high prevalence in patients with obesity. Only patients with clinical symptoms of OSA are admitted to polysomnography; however, many patients with OSA are asymptomatic. We aimed to create and validate a population-based risk score that predicts the severity of OSA in patients with obesity. We here report the cross-sectional analysis at baseline of an ongoing study investigating the long-term effect of bariatric surgery on OSA. One-hundred sixty-one patients of the Obesity Center of the Catholic University Hospital in Rome, Italy were included in the study. The patients underwent overnight cardiorespiratory monitoring, blood chemistry analyses, hepatic ultrasound, and anthropometric measurements. The patients were divided into 2 groups according OSA severity assessed by the apnea-hypopnea index (AHI): AHI < 15 = no or mild and AHI ≥ 15 moderate to severe OSA. A statistical prediction model was created and validated. C statistics was used to evaluate the discrimination performance of the model. The prevalence of OSA was 96.3% with 74.5% of the subjects having moderate/severe OSA. Sex, body mass index, diabetes, and age were included in the final prediction model that had excellent discrimination ability (C statistics equals to 83%). An OSA risk chart score for clinical use was created. Patients with severe obesity are at a very high risk for moderate or severe OSA in particular if they are men, older, more obese, and/or with type 2 diabetes. The OSA risk chart can be useful for general practitioners and patients as well as for bariatric surgeons to select patients with high risk of moderate to severe OSA for further polysomnography.