Background The use of high-flow nasal cannula (HFNC) and noninvasive ventilation (NIV) in patients with COVID-19 is debated. Methods This study was performed in four hospitals of China from January to March 2020. We retrospectively enrolled 23 and 13 COVID-19 patients who used HFNC and NIV as first-line therapy, respectively. Results Among the 23 patients who used HFNC as first-line therapy, 10 experienced HFNC failure and used NIV as rescue therapy. Among the 13 patients who used NIV as first-line therapy, one (8%) used HFNC as rescue therapy due to NIV intolerance. The duration of HFNC + NIV (median 7.1, IQR: 3.5–12.2 vs. 7.3, IQR: 5.3–10.0 days), intubation rate (17% vs. 15%) and mortality (4% vs. 8%) did not differ between patients who used HFNC and NIV as first-line therapy. In total cohorts, 6 (17%) patients received intubation. Time from initiation of HFNC or NIV to intubation was 8.4 days (IQR: 4.4–18.5). And the time from initiation of HFNC or NIV to termination in patients without intubation was 7.1 days (IQR: 3.9–10.3). Among all the patients, C-reactive protein was independently associated with intubation (OR = 1.04, 95% CI: 1.01–1.07). In addition, no medical staff got nosocomial infection who participated in HFNC and NIV management. Conclusions In critically ill patients with COVID-19 who used HFNC and NIV as first-line therapy, the duration of HFNC + NIV, intubation rate and mortality did not differ between two groups. And no medical staff got nosocomial infection during this study.

Background Heart rate, acidosis, consciousness, oxygenation, and respiratory rate (HACOR) have been used to predict noninvasive ventilation (NIV) failure. However, the HACOR score fails to consider baseline data. Here, we aimed to update the HACOR score to take into account baseline data and test its predictive power for NIV failure primarily after 1–2 h of NIV. Methods A multicenter prospective observational study was performed in 18 hospitals in China and Turkey. Patients who received NIV because of hypoxemic respiratory failure were enrolled. In Chongqing, China, 1451 patients were enrolled in the training cohort. Outside of Chongqing, another 728 patients were enrolled in the external validation cohort. Results Before NIV, the presence of pneumonia, cardiogenic pulmonary edema, pulmonary ARDS, immunosuppression, or septic shock and the SOFA score were strongly associated with NIV failure. These six variables as baseline data were added to the original HACOR score. The AUCs for predicting NIV failure were 0.85 (95% CI 0.84–0.87) and 0.78 (0.75–0.81) tested with the updated HACOR score assessed after 1–2 h of NIV in the training and validation cohorts, respectively. A higher AUC was observed when it was tested with the updated HACOR score compared to the original HACOR score in the training cohort (0.85 vs. 0.80, 0.86 vs. 0.81, and 0.85 vs. 0.82 after 1–2, 12, and 24 h of NIV, respectively; all p values < 0.01). Similar results were found in the validation cohort (0.78 vs. 0.71, 0.79 vs. 0.74, and 0.81 vs. 0.76, respectively; all p values < 0.01). When 7, 10.5, and 14 points of the updated HACOR score were used as cutoff values, the probability of NIV failure was 25%, 50%, and 75%, respectively. Among patients with updated HACOR scores of ≤ 7, 7.5–10.5, 11–14, and > 14 after 1–2 h of NIV, the rate of NIV failure was 12.4%, 38.2%, 67.1%, and 83.7%, respectively. Conclusions The updated HACOR score has high predictive power for NIV failure in patients with hypoxemic respiratory failure. It can be used to help in decision-making when NIV is used.

In this study, we investigate the potential driving factors that lead to the disparity in the time-series of home dwell time in a data-driven manner, aiming to provide fundamental knowledge that benefits policy-making for better mitigation strategies of future pandemics. Taking Metro Atlanta as a study case, we perform a trend-driven analysis by conducting Kmeans time-series clustering using fine-grained home dwell time records from SafeGraph. Furthermore, we apply ANOVA (Analysis of Variance) coupled with post-hoc Tukey’s test to assess the statistical difference in sixteen recoded demographic/socioeconomic variables (from ACS 2014–2018 estimates) among the identified time-series clusters. We find that demographic/socioeconomic variables can explain the disparity in home dwell time in response to the stay-at-home order, which potentially leads to disparate exposures to the risk from the COVID-19. The results further suggest that socially disadvantaged groups are less likely to follow the order to stay at home, pointing out the extensive gaps in the effectiveness of social distancing measures that exist between socially disadvantaged groups and others. Our study reveals that the long-standing inequity issue in the U.S. stands in the way of the effective implementation of social distancing measures.

Objective The mechanisms of lung injury in acute respiratory distress syndrome (ARDS) are not well understood.Piezo1 was recently identified as a mechanotransduction protein. The present study found the expression of Piezo1 in type II pneumocytes and investigated its role in mediating ARDS-related lung injury. Methods Sprague-Dawley rats were used to establish an ARDS model, the expression of Piezo1,lung injuries, apoptosis as well as calcium influx were assessed. Results Piezo1 was expressed in type II pneumocytes as shown by immunofluorescence staining and expression was increased in the ARDS model. Knockdown of Piezo1 reduced apoptosis which was related to the elevation of Bcl-2.Calcium influx played a vital role in Piezo1-induced apoptosis. Conclusion Piezo1 was expressed in type II pneumocytes. Mechanical stretch of alveoli during ARDS induced activation of the Piezo1 channel,which resulted in calcium influx. The increased intracellular Ca2+ induced the apoptosis of type II pneumocytes, which may be related to the Bcl-2 pathway. Electronic supplementary material The online version of this article (10.1186/s12931-019-1083-1) contains supplementary material, which is available to authorized users.

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