Pulmonology最新文献

Background: The severe acute respiratory syndrome Coronarovirus-2 associated still causes a significant number of deaths and hospitalizations mainly by the development of respiratory failure. We aim to validate lung ultrasound score in order to predict mortality and the severity of the clinical course related to the need of respiratory support.

Methods: In this prospective multicenter hospital-based cohort study, all adult patients with diagnosis of SARS-CoV-2 infection, performed by real-time reverse transcription polymerase chain reaction were included. Upon admission, all patients underwent blood gas analysis and lung ultrasound by expert operators. The acquisition of ultrasound scan was performed on 12 peculiar anatomic landmarks of the chest. Lung ultrasound findings were classified according to a scoring method, ranging 0 to 3: Score 0: normal A-lines. Score 1: multiple separated B-lines. Score 2: coalescent B-lines, alteration of pleural line. Score 3: consolidation area.

Results: One thousand and seven patients were included in statistical analysis (male 62.4 %, mean age 66.3). Oxygen support was needed in 811 (80.5 %) patients. The median ultrasound score was 24 and the risk of having more invasive respiratory support increased in relation to higher values score computed. Lung ultrasound score showed negative strong correlation (rho: -0.71) with the P/F ratio and a significant association with in-hospital mortality (OR 1.11, 95 %CI 1.07-1.14; p < 0.001), even after adjustment with the following variables (age, sex, P/F ratio, SpO2, lactate, hypertension, chronic renal failure, diabetes, and obesity).

Conclusions: The novelty of this research corroborates and validates the 12-field lung ultrasound score as tool for predicting mortality and severity clinical course in COVID-19 patients. Baseline lung ultrasound score was associated with in-hospital mortality and requirement of intensive respiratory support and predict the risk of IOT among COVID-19 patients.

Introduction and objectives: Quantifying breathing effort in non-intubated patients is important but difficult. We aimed to develop two models to estimate it in patients treated with high-flow oxygen therapy.

Patients and methods: We analyzed the data of 260 patients from previous studies who received high-flow oxygen therapy. Their breathing effort was measured as the maximal deflection of esophageal pressure (ΔPes). We developed a multivariable linear regression model to estimate ΔPes (in cmH₂O) and a multivariable logistic regression model to predict the risk of ΔPes being >10 cmH₂O. Candidate predictors included age, sex, diagnosis of the coronavirus disease 2019 (COVID-19), respiratory rate, heart rate, mean arterial pressure, the results of arterial blood gas analysis, including base excess concentration (BEa) and the ratio of arterial tension to the inspiratory fraction of oxygen (PaO₂:FiO₂), and the product term between COVID-19 and PaO₂:FiO₂.

Results: We found that ΔPes can be estimated from the presence or absence of COVID-19, BEa, respiratory rate, PaO₂:FiO_2, and the product term between COVID-19 and PaO₂:FiO_2. The adjusted R² was 0.39. The risk of ΔPes being >10 cmH₂O can be predicted from BEa, respiratory rate, and PaO₂:FiO₂. The area under the receiver operating characteristic curve was 0.79 (0.73-0.85). We called these two models BREF, where BREF stands for BReathing EFfort and the three common predictors: BEa (B), respiratory rate (RE), and PaO₂:FiO₂ (F).

Conclusions: We developed two models to estimate the breathing effort of patients on high-flow oxygen therapy. Our initial findings are promising and suggest that these models merit further evaluation.

Air pollution is a major global environment and health concern. Recent studies have suggested an association between air pollution and COVID-19 mortality and morbidity. In this context, a close association between increased levels of air pollutants such as particulate matter ≤2.5 to 10 µM, ozone and nitrogen dioxide and SARS-CoV-2 infection, hospital admissions and mortality due to COVID 19 has been reported. Air pollutants can make individuals more susceptible to SARS-CoV-2 infection by inducing the expression of proteins such as angiotensin converting enzyme (ACE)2 and transmembrane protease, serine 2 (TMPRSS2) that are required for viral entry into the host cell, while causing impairment in the host defence system by damaging the epithelial barrier, muco-ciliary clearance, inhibiting the antiviral response and causing immune dysregulation. The aim of this review is to report the epidemiological evidence on impact of air pollutants on COVID 19 in an up-to-date manner, as well as to provide insights on in vivo and in vitro mechanisms.