We analyzed reports on safety and efficacy of JAK-inhibitors in patients with coronavirus infectious disease-2019 (COVID-19) published between January 1st and March 6th 2021 using the Newcastle-Ottawa and Jadad scales for quality assessment. We used disease severity as a proxy for time when JAK-inhibitor therapy was started. We identified 6 cohort studies and 5 clinical trials involving 2367 subjects treated with ruxolitinib (N = 3) or baricitinib 45 (N = 8). Use of JAK-inhibitors decreased use of invasive mechanical ventilation (RR = 0.63; [95% Confidence Interval (CI), 0.47, 0.84]; P = 0.002) and had borderline impact on rates of intensive care unit (ICU) admission (RR = 0.24 [0.06, 1.02]; P = 0.05) and acute respiratory distress syndrome (ARDS; RR = 0.50 [0.19, 1.33]; P = 0.16). JAK-inhibitors did not decrease length of hospitalization (mean difference (MD) –0.18 [–4.54, 4.18]; P = 0.94). Relative risks of death for both drugs were 0.42 [0.30, 0.59] (P < 0.001), for ruxolitinib, RR = 0.33 (0.13, 0.88; P = 0.03) and for baricitinib RR = 0.44 (0.31, 0.63; P < 0.001). Timing of JAK-inhibitor treatment during the course of COVID-19 treatment may be important in determining impact on outcome. However, these data are not consistently reported.

Background and aims: Lung cancer patients suffer from deterioration in their physical and psychological function, which exerts a negative influence on their quality of life (QOL). Telemedicine has been proven to be an effective intervention for patients with several chronic diseases. The aim of this systematic review and meta-analysis was to investigate the efficacy of telemedicine in improving QOL in lung cancer patients. Methods: PubMed, Cochrane Library, EMBASE, Web of Science and Scopus databases were searched for randomized controlled trials that investigated the effectiveness of telemedicine in lung cancer patients. Review Manager 5.3 and Stata 15.1 were used to perform data analysis. Results: Our meta-analysis included eight clinical trials with a total of 635 lung cancer patients. The results showed that the telemedicine group had significantly higher QOL than the usual care group [standard mean difference (SMD) 0.96, 95% confidence interval (CI) 0.29–1.63, I² = 91%]. In addition, the telemedicine group had lower anxiety (SMD −0.44, 95% CI −0.66 to −0.23, I² = 3%) and depression scores (SMD −0.48, 95% CI −0.91 to −0.05, I² = 66%) than the usual care group. However, no significant differences were found in fatigue and pain outcomes between the two groups. Conclusion: Telemedicine may be an effective method of improving QOL in lung cancer patients and the further development and use of telemedicine care is recommended.

Background: This was a meta-analysis of continuous positive airway pressure (CPAP) compliance. We compared telemonitor (TM) care with usual care and supervised PAP titration (SPT) in the sleep unit with home auto-adjusting pressure titration (HAPT) in patients with obstructive sleep apnea (OSA). Methods: We searched PubMed, Web of Science, Scopus, and Medline for appropriate randomized controlled trials (RCTs) that compared TM care with usual care for patients with OSA. Review Manager 5.3 was used for all comparisons and analyses. Results: Our meta-analysis included 19 studies involving a total of 2464 patients with OSA; CPAP compliance was significantly higher in the TM care group [mean difference (MD) 0.68 h, 95% confidence interval (CI) 0.48–0.89 h, I² = 49%] compared with the usual care group. When we compared SPT and HAPT, two groups did not exhibit significantly different levels of CPAP compliance (MD −0.34 h, 95% CI −0.72–0.05 h, I² = 91%). Subgroup analysis comparing the SPT with HAPT in CPAP compliance was grouped by follow-up time (⩾3 months or <3 months). Once again, there were no between-group differences in either long-term (MD = 0.56 h, 95% CI = 1.39–0.26 h, I² = 91%), or short-term (MD = 0.34 h, 95% CI = 0.26–0.27 h, I² = 14%) follow up. Conclusions: TM care was associated with significantly greater CPAP compliance compared with usual care. Also, HAPT was not inferior to SPT for CPAP compliance.

We performed a meta-analysis to determine safety and efficacy of tocilizumab in persons with coronavirus disease-2019 (COVID-19). We searched PubMed, Web of Science and Medline using Boolean operators for studies with the terms coronavirus OR COVID-19 OR 2019-nCoV OR SARS-CoV-2 AND tocilizumab. Review Manager 5.4 was used to analyze data and the modified Newcastle–Ottawa and Jadad scales for quality assessment. We identified 32 studies in 11,487 subjects including three randomized trials and 29 cohort studies with a comparator cohort, including historical controls (N = 5), a matched cohort (N = 12), or concurrent controls (N = 12). Overall, tocilizumab decreased risk of death (Relative Risk [RR] = 0.74; 95% confidence interval [CI], 0.59, 0.93; P = 0.008; I² = 80%) but not of surrogate endpoints including ICU admission (RR = 1.40 [0.64,3.06]; P = 0.4; I² = 88%), invasive mechanical ventilation (RR = 0.83 [0.57,1.22]; P = 0.34; I² = 65%) or secondary infections (RR = 1.30 [0.97,1.74]; P = 0.08; I² = 65%) and increased interval of hospitalization of subjects discharged alive(mean difference [MD] = 2 days [<1, 4 days]; P = 0.006; I² = 0). RRs of death in studies with historical controls (RR = 0.28 [0.16,0.49; P < 0.001]; I² = 62%) or a matched cohort (RR = 0.68 [0.53, 0.87]; P = 0.002; I² = 42%) were decreased. In contrast, RRs of death in studies with a concurrent control (RR = 1.10 [0.77, 1.56]; P = 0.60; I² = 85%) or randomized (RR = 1.18 [0.57,2.44]; P = 0.66; I² = 0) were not decreased. A reduced risk of death was not confirmed in our analyses which questions safety and efficacy of tocilizumab in persons with COVID-19.

Background: Artificial intelligence (AI) technology has been used for finding lesions via gastrointestinal endoscopy. However, there were few AI-associated studies that discuss bronchoscopy. Objectives: To use convolutional neural network (CNN) to recognize the observed anatomical positions of the airway under bronchoscopy. Design: We designed the study by comparing the imaging data of patients undergoing bronchoscopy from March 2022 to October 2022 by using EfficientNet (one of the CNNs) and U-Net. Methods: Based on the inclusion and exclusion criteria, 1527 clear images of normal anatomical positions of the airways from 200 patients were used for training, and 475 clear images from 72 patients were utilized for validation. Further, 20 bronchoscopic videos of examination procedures in another 20 patients with normal airway structures were used to extract the bronchoscopic images of normal anatomical positions to evaluate the accuracy for the model. Finally, 21 respiratory doctors were enrolled for the test of recognizing corrected anatomical positions using the validating datasets. Results: In all, 1527 bronchoscopic images of 200 patients with nine anatomical positions of the airway, including carina, right main bronchus, right upper lobe bronchus, right intermediate bronchus, right middle lobe bronchus, right lower lobe bronchus, left main bronchus, left upper lobe bronchus, and left lower lobe bronchus, were used for supervised machine learning and training, and 475 clear bronchoscopic images of 72 patients were used for validation. The mean accuracy of recognizing these 9 positions was 91% (carina: 98%, right main bronchus: 98%, right intermediate bronchus: 90%, right upper lobe bronchus: 91%, right middle lobe bronchus 92%, right lower lobe bronchus: 83%, left main bronchus: 89%, left upper bronchus: 91%, left lower bronchus: 76%). The area under the curves for these nine positions were >0.98. In addition, the accuracy of extracting the images via the video by the trained model was 94.7%. We also conducted a deep learning study to segment 10 segment bronchi in right lung, and 8 segment bronchi in Left lung. Because of the problem of radial depth, only segment bronchi distributions below right upper bronchus and right middle bronchus could be correctly recognized. The accuracy of recognizing was 84.33 ± 7.52% by doctors receiving interventional pulmonology education in our hospital over 6 months. Conclusion: Our study proved that AI technology can be used to distinguish the normal anatomical positions of the airway, and the model we trained could extract the corrected images via the video to help standardize data collection and control quality.

Background: Septic shock is one of the major healthcare problems, affecting millions of people around the world every year. The object of this study is to find the best kind of regimen of vasopressors treatment in septic shock. Methods: The PubMed, and the Web of Science were used to find the included studies. Stata 15.1 was performed to this systemic review and network meta-analysis. Results: After searching and screening the articles, finally we included articles about 31 randomized controlled trials (RCTs), 11 arms (dopamine, dopexamine, epinephrine, norepinephrine, norepinephrine + dobutamine, norepinephrine + dopexamine, norepinephrine + epinephrine, norepinephrine + vasopressin, phenylephrine, terlipressin, vasopressin) and total 5,928 patients with septic shock. Compared with dopamine, the regimens (epinephrine, norepinephrine, norepinephrine + dobutamine, and vasopressin) have significantly lower 28-day mortality. Ranking the regimens in the order of estimated probabilities of each treatment by using the network meta-analysis for 28-day mortality, the result showed that norepinephrine + dopexamine was the best one (57.3%), followed by norepinephrine + epinephrine (14.8%), norepinephrine + dobutamine (10.9%), dopexamine (11.2%), terlipressin (9.8%), norepinephrine + vasopressin (2.4%), phenylephrine (1.2%), epinephrine (1.0%), vasopressin (0.5%), norepinephrine (0.0%), and dopamine (0.0%). In addition, for the results of arrhythmia and increased heart rate, the combination regimens groups did not showed inferiority to other single regimen groups. Conclusions: Single dopamine had significantly higher 28d mortality. Combination regimens of vasopressors accounted for the best three therapeutic regimens. In treating patients with septic shock, using combining regimens probably gets more benefits.