Chylothorax found in a patient with COVID-19.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its clinical spectrum ranges from mild to moderate or severe illness. A 78-year-old male was presented at emergency department with dyspnoea, dry cough and severe asthenia. The nasopharyngeal swab by real-time polymerase chain reaction confirmed a SARS-CoV-2 infection. The x-ray and the thoracic ultrasound revealed right pleural effusion. A diagnostic-therapeutic thoracentesis drained fluid identified as chylothorax. Subsequently, the patient underwent a chest computed tomography which showed the radiological hallmarks of COVID-19 and in the following weeks he underwent a chest magnetic resonance imaging to obtain a better view of mediastinal and lymphatic structures, which showed a partial thrombosis affecting the origin of superior vena cava and the distal tract of the right subclavian vein. For this reason, anticoagulant therapy was optimized and in the following weeks the patient was discharged for clinical and radiological improvement. This case demonstrates chylothorax as a possible and uncommon complication of COVID-19.

Machine learning-based prediction of adherence to continuous positive airway pressure (CPAP) in obstructive sleep apnea (OSA).

Continuous positive airway pressure (CPAP) is the "gold-standard" therapy for obstructive sleep apnea (OSA), but the main problem is the poor adherence. Therefore, we have searched for the causes of poor adherence to CPAP therapy by applying predictive machine learning (ML) methods. The study was conducted on OSAs in nighttime therapy with CPAP. An outpatient follow-up was planned at 3, 6, 12 months. We collected several parameters at the baseline visit and after dividing all patients into two groups (Adherent and Non-adherent) according to therapy adherence, we compared them. Statistical differences between the two groups were not found according to baseline characteristics, except gender (P< .01). Therefore, we applied ML to predict CPAP adherence, and these predictive models showed an accuracy and sensitivity of 68.6% and an AUC (area under the curve) of 72.9% through the SVM (support vector machine) classification method. The identification of factors predictive of long-term CPAP adherence is complex, but our proof of concept seems to demonstrate the utility of ML to identify subjects poorly adherent to therapy. Therefore, application of these models to larger samples could aid in the careful identification of these subjects and result in important savings in healthcare spending.

The Role of Transthoracic Ultrasound in the Study of Interstitial Lung Diseases: High-Resolution Computed Tomography Versus Ultrasound Patterns: Our Preliminary Experience.

Transthoracic ultrasound (TUS) is a readily available imaging tool that can provide a quick real-time evaluation. The aim of this preliminary study was to establish a complementary role for this imaging method in the approach of interstitial lung diseases (ILDs). TUS examination was performed in 43 consecutive patients with pulmonary fibrosis and TUS findings were compared with the corresponding high-resolution computed tomography (HRCT) scans. All patients showed a thickened hyperechoic pleural line, despite no difference between dominant HRCT patterns (ground glass, honeycombing, mixed pattern) being recorded (p > 0.05). However, pleural lines' thickening showed a significant difference between different HRCT degree of fibrosis (p < 0.001) and a negative correlation with functional parameters. The presence of >3 B-lines and subpleural nodules was also assessed in a large number of patients, although they did not demonstrate any particular association with a specific HRCT finding or fibrotic degree. Results allow us to suggest a complementary role for TUS in facilitating an early diagnosis of ILD or helping to detect a possible disease progression or eventual complications during routine clinical practice (with pleural line measurements and subpleural nodules), although HRCT remains the gold standard in the definition of ILD pattern, disease extent and follow-up.