ABSTRACT
In the current situation of coronavirus disease 2019, "to prevent import from abroad and to defend internal rebound" is the general principle. Facing the changes in the epidemic situation, especially the winter and spring epidemics, it is a huge challenge to carry out a scientific, precise and flexible program for the prevention and control of healthcare-associated infections so that to ensure the safety of healthcare workers and patients. After more than one year of anti-epidemic work, Peking Union Medical College Hospital has summarized and formulated a four-level retractable and releasable hierarchical program of prevention and control. It is dynamically adjusted according to the responsive level of public health emergencies in Beijing and the relevant regulations of epidemic prevention and control. All departments can also respond quickly to ensure the resumption of work. This program provides reference for the prevention and control of coronavirus disease 2019 and other sudden infectious diseases.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.
ABSTRACT
Under the Covid-19 situation, the older people's lack of understanding of the epidemic information, resulting in poor self-protection, limited travel, affects the purchase of life and medical items. These made a significant threat to their health. Due to the rules of home isolation, the Internet has become the primary source of information. But this leads to the digital divide faced by the elderly becoming more prominent, which has already existed before. This research studies the specific difficulties faced by the elderly in the digital divide in the epidemic. This paper used a semi-structured interview and recruited 25 older people to participate. By analyzing the interview content, this study used the content analysis method to analyze the difficulties of information acquisition and utilization of the elderly. In addition, this study analyzed the main reasons for the digital divide faced by the elderly from internal and external factors. Then, this study proposed suggestions for IT enterprises and government to solve the digital divide in the Covid-19 from the perspective of the elderly. Through this study, the findings can help solve the digital divide faced by the elderly in the epidemic, help them better obtain accurate information, and help them better protect their health. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Detecting protective measures (e.g., masks, goggles and protective clothing) is a momentous step in the fight against COVID-19. The detection mode of unmanned devices based on Simultaneous localization and mapping (SLAM) and fusion technology is more efficient, economical and safe than the traditional manual detection. In this paper, a tightly-coupled nonlinear optimization approach is used to augment the visual feature extraction of SLAM by the gyroscope of the IMU to obtain a high-precision visual inertial system for joint position and pose estimation. Based on the VINS-Mono frame, first, an LSD algorithm based on a conditional selection strategy is proposed to extract line features efficiently. Then, we propose recovering missing point features from line features. Moreover, we propose a strategy to recover vanishing point features from line features, and add residuals to the SLAM cost function based on optimization, which optimizes point-line features in real time to promote the tracking and matching accuracy. Second, the wavelet threshold denoising method based on the 3σ criterion is used to carry out real-time online denoising for gyroscope to improve the output precision. Our WD-PL-VINS was measured on publicly available EuRoC datasets, TUM VI datasets and evaluated and validated in lab testing with a unmanned vehicle (UV) based on the NVIDIA Jetson-TX2 development board. The results show that our method's APE and RPE on MH-03-easy sequences are improved by 69.28% and 97.66%, respectively, compared with VINS-Mono. © 2001-2012 IEEE.
ABSTRACT
SARS-CoV-2 continues to accumulate mutations to evade immunity, leading to breakthrough infections after vaccination. How researchers can anticipate the evolutionary trajectory of the virus in advance in the design of next-generation vaccines requires investigation. Here, we performed a comprehensive study of 11,650,487 SARS-CoV-2 sequences, which revealed that the SARS-CoV-2 spike (S) protein evolved not randomly but into directional paths of either high infectivity plus low immune resistance or low infectivity plus high immune resistance. The viral infectivity and immune resistance of variants are generally incompatible, except for limited variants such as Beta and Kappa. The Omicron variant has the highest immune resistance but showed high infectivity in only one of the tested cell lines. To provide cross-clade immunity against variants that undergo diverse evolutionary pathways, we designed a new pan-vaccine antigen (Span). Span was designed by analyzing the homology of 2675 SARS-CoV-2 S protein sequences from the NCBI database before the Delta variant emerged. The refined Span protein harbors high-frequency residues at given positions that reflect cross-clade generality in sequence evolution. Compared with a prototype wild-type (Swt) vaccine, which, when administered to mice, induced serum with decreased neutralization activity against emerging variants, Span vaccination of mice elicited broad immunity to a wide range of variants, including those that emerged after our design. Moreover, vaccinating mice with a heterologous Span booster conferred complete protection against lethal infection with the Omicron variant. Our results highlight the importance and feasibility of a universal vaccine to fight against SARS-CoV-2 antigenic drift.
ABSTRACT
In epidemic prevention and control measures, unmanned devices based on autonomous driving technology have stepped into the front lines of epidemic prevention, playing a vital role in epidemic prevention measures such as protective measures detection. Autonomous positioning technology is one of the key technologies of autonomous driving. The realization of high-precision positioning can provide accurate location epidemic prevention services and a refined intelligent management system for the government and citizens. In this paper, we propose an unmanned vehicle (UV) positioning system REW_SLAM based on lidar and stereo camera, which realize real-time online pose estimation of UV by using high-precision lidar pose correction visual positioning data. A six-element extended Kalman filter (6-element EKF) is proposed to fusion lidar and stereo camera sensors information, which retains the second-order Taylor series of observation and state equation, and effectively improves the accuracy of data fusion. Meanwhile, considering improving lidar outputs quality, a modified wavelet denoising method is introduced to preprocess the original data of lidar. Our approach was tested on KITTI datasets and real UV platform, respectively. By comparing with the other two algorithms, the relative pose error and absolute trajectory error of this algorithm are increased by 0.26 m and 2.36 m on average, respectively, while the CPU occupancy rate is increased by 6.685% on average, thereby proving the robustness and effectiveness of the algorithm.
ABSTRACT
The COVID-19 pandemic provided the specialty of emergency medicine the opportunity to showcase what many knew all along: emergency physicians (EP) are well suited to deal with the unknown and can quickly adapt even with incomplete or limited information and resources. Emergency physicians in Missouri served in integral positions locally, nationally and internationally. Missouri EPs published numerous manuscripts on topics from basic science to clinical care. Device innovation also occurred with the development of protective devices for health care workers.As we approach the three-year mark of the COVID-19 pandemic, the burden of clinical care still weighs heavily on EPs. Each wave of the pandemic has brought challenges and spurred EPs to innovate in new ways. As Michigan EP Brian Zink, MD once said “Anyone, Anything, Anytime”. These words correctly sum up emergency medicine. When others hesitated to care for COVID-19 patients, EPs stepped up despite uncertainty and risks to their own health. Emergency medicine has led the way and continues to innovate and push the envelope of emergency care.
ABSTRACT
Non-pharmaceutical interventions (NPIs) are essential for the effective prevention and control of the COVID-19 pandemic. However, the scenarios for disease transmission are complicated and varied, and it remains unclear how real-world networks respond to the changes in NPIs. Here, we propose a multi-layer network combining structurally fixed social contact networks with a time-varying mobility network, select the COVID-19 outbreak in two metropolitans in China as case studies, and assess the effectiveness of NPIs. Human mobility, both in relatively fixed places and in urban commuting, is considered. Enclosed places are simulated by three different types of social contact networks, while urban commuting is represented by a time-varying commute network. We provide a composite framework that captures the heterogeneity and time variation of the real world and enables us to simulate large populations with low computational costs. We give out a thorough evaluation of the effectiveness of NPIs (i.e., work from home, school closure, close-off management, public transit limitation, quarantine, and mask use) under certain vaccine coverage varying with implementation timing and intensity. Our results highlight the strong correlation between the NPI pattern and the epidemic mitigation effect and suggest important operational strategies for epidemic control. Copyright © 2022 Chen, Guo, Jiao, Liang, Li, Yan, Huang, Liu and Fan.
ABSTRACT
Background: The coronavirus (COVID-19) outbreak in 2019 triggered psychological and emotional responses. This research investigates the psychological status and emotional problems of those who sought psychological assistance during the epidemic period by calling a mental health hotline. Methods: This study aims to combine qualitative and quantitative research. Descriptive analysis was used for undertaking qualitative research. We analyzed the data from group 1 (n = 706), in which the people used the mental health hotline from 25 January 2020 to 23 June 2020. A self-designed questionnaire was developed in accordance with the classification and summarized items from group 1’s psychological problems and emotional status. To implement the quantitative research, we conducted a cross-sectional descriptive survey and used the self-compiled scale and HADS to investigate group 2 (n = 553) from May 2020 to June 2020. Results: Descriptive statistics and comparative analysis revealed that: ①Visitors mainly reported behavior, emotional, family relationship problems and sleep disorders. ② Anxiety, comorbidities, sleep disorders and coping problems were the most frequently reported problems. ③ There were significant differences in the number of visitors experiencing various problems or exhibiting harmful behaviors (sorrow, worry, fear, depression, sleep disorders, self-harm or suicide, and coping problems, anxiety, hypochondria, and comorbidity) in the four stages of the epidemic. ④ More than a quarter of participants still suffered from anxiety or depression in the later stages of the epidemic. Conclusion: Different problems manifested at different stages of the epidemic, and psychological interventions and assistance should be tailored to reflect this. © 2022, Tech Science Press. All rights reserved.
ABSTRACT
Detecting protective measures (e.g., masks, goggles and protective clothing) is a momentous step in the fight against COVID-19. The detection mode of unmanned devices based on Simultaneous localization and mapping (SLAM) and fusion technology is more efficient, economical and safe than the traditional manual detection. In this paper, a tightly-coupled nonlinear optimization approach is used to augment the visual feature extraction of SLAM by the gyroscope of the IMU to obtain a high-precision visual inertial system for joint position and pose estimation. Based on the VINS-Mono frame, first, an LSD algorithm based on a conditional selection strategy is proposed to extract line features efficiently. Then, we propose recovering missing point features from line features. Moreover, we propose a strategy to recover vanishing point features from line features, and add residuals to the SLAM cost function based on optimization, which optimizes point-line features in real time to promote the tracking and matching accuracy. Second, the wavelet threshold denoising method based on the 3σcriterion is used to carry out real-time online denoising for gyroscope to improve the output precision. Our WD-PL-VINS was measured on publicly available EuRoC datasets, TUM VI datasets and evaluated and validated in lab testing with a unmanned vehicle (UV) based on the NVIDIA Jetson-TX2 development board. The results show that our method’s APE and RPE on MH 03 easy sequences are improved by 69.28% and 97.66%, respectively, compared with VINS-Mono. IEEE
ABSTRACT
Comprehensive analysis of respiratory gases may provide noninvasive health monitoring of lung diseases, such as corona virus 2019 pneumonia. Here, a self-powered wearable mask has been fabricated for real-time monitoring and uploading exhaling oxygen information. Tetrapod ZnO (T-ZnO) nanostructures are hybridized with polyvinylidene fluoride (PVDF) that adhere to flexible fabric substrate on a mask. The piezoelectric effect of T-ZnO/PVDF is coupled with the gas sensing properties. The sensing unit can convert breath energy into piezoelectric signal without any external power supply, and the outputting piezoelectric voltage increases with increasing oxygen concentration, acting as the sensing signal. The sensing unit integrated with data processing module and wireless Bluetooth module can transmit the exhaling oxygen information to the mobile device, realizing real-time monitoring the oxygenation capacity of the lungs. This self-powered wearable approach can promote the lung diagnosis outside of clinical settings. © 2022 IOP Publishing Ltd.
ABSTRACT
Background. Remdesivir (RDV) reduced time to recovery and mortality in some subgroups of hospitalized patients in the NIAID ACTT-1 RCT compared to placebo. Comparative effectiveness data in clinical practice are limited. Methods. Using the Premier Healthcare Database, we compared survival for adult non-mechanically ventilated hospitalized COVID-19 patients between Aug-Nov 2020 and treated with RDV within 2 days of hospitalization vs. those who did not receive RDV. Preferential within-hospital propensity score matching with replacement was used. Patients were matched on baseline O2 and 2-month admission period and were excluded if discharged within 3 days of RDV initiation (to exclude anticipated discharges/transfers within 72 hrs consistent with ACTT-1 study). Time to 14- and 28-day mortality was examined separately for patients on high-flow/non-invasive ventilation (NIV), low-flow, and no supplemental O2 using Cox Proportional Hazards models. Results. RDV patients (n=27,559) were matched to unique non-RDV patients (n=15,617) (Fig 1). The two groups were balanced;median age 66 yrs and 73% white (RDV);68 yrs and 74% white (non-RDV), and 55% male. At baseline, 21% required high-flow O2, 50% low-flow O2, and 29% no O2, overall. Mortality in RDV patients was 9.6% and 13.8% on days 14 and 28, respectively. For non-RDV patients, mortality was 14.0% and 17.3% on days 14 and 28, respectively. Kaplan-Meier curves for time to mortality are shown in Fig 2. After adjusting for baseline and clinical covariates, RDV patients on no O2 and low-flow O2 had a significantly lower risk of death within 14 days (no O2, HR: 0.69, 95% CI: 0.57-0.83;low-flow, HR: 0.67, 95% CI: 0.59-0.77) and 28 days (no O2, HR: 0.80, 95% CI: 0.68-0.94;low-flow, HR: 0.76, 95% CI: 0.68-0.86). Additionally, RDV patients on high-flow O2/NIV had a significantly lower risk of death within 14 days (HR: 0.81, 95% CI: 0.70-0.93);but not at 28 days (Fig 3). Conclusion. In this large study of patients in clinical care hospitalized with COVID-19, we observed a significant reduction of mortality in RDV vs. non-RDV treated patients in those on no O2 or low-flow O2. Mortality reduction was also seen in patients on high-flow O2 at day 14, but not day 28. These data support the use of RDV early in the course of COVID-19 in hospitalized patients.
ABSTRACT
Background. Evidence on outcomes after COVID-19 hospitalization is limited. This study aimed to characterize 30-day readmission beyond the initial COVID-19 hospitalization. Methods. This descriptive retrospective cohort study included adult patients admitted between 07/01/2020 and 01/31/2021 with a discharge diagnosis of COVID-19 (ICD-10-CM: U07.1), using a large hospital inpatient chargemaster with a linked open claims dataset. The first COVID-19 hospitalization was considered index hospitalization;baseline was defined as first 2 days of index hospitalization;readmission was assessed within 30 days of discharge from index hospitalization. We describe the demographics, treatments and outcomes of the index hospitalization and readmission. Results. For index hospitalization, we identified 111,624 COVID-19 patients from 327 hospitals across US. Mean age was 63 and 54% were male. Over the study period, use of remdesivir (RDV) increased from 11% to 50% while use of steroids (66% -73%) and anticoagulants (32% - 35%) remained relatively stable (Figure 1). Overall, 21% required ICU or CCU admission, 13% died, and median length of stay (LOS) was 7 days (range 4 -11 days). Among 61,182 (55%) with ≥ 30-day follow-up post discharge, all-cause 30-day readmission was 16% and remained stable (15% - 17%) over the study period;median days to readmission was 6 days (range 1-30). All-cause readmission (13 % vs 17%) was lower in patients treated with RDV during index hospitalization over time (Figure 2), particularly in those requiring high flow oxygen (17% vs 18%), low flow oxygen (13% vs 16%) or no oxygen (12% vs 17%), but not in ECMO or invasive ventilation (33% vs 29%). Compared to non-readmitted, readmitted patients were older (60 vs 65), had more comorbidities such as COPD (24% vs 37%) (see Table 1) and LOS (6 vs 7 days) in index hospitalization. Overall, the most frequent diagnoses of readmission were COVID-19 (63%), other viral pneumonia (36%), and acute respiratory failure with hypoxia (34%). Conclusion. In a large, geographically diverse cohort of hospitalized COVID-19 patients, 16% required readmission, especially in those with greater age and comorbidities. Over the study period, all-cause readmission remained stable and was lower in RDV treated patients.
ABSTRACT
Objectives: With over 90 million cases reported in the globe, the COVID-19 pandemic caused by SARS-CoV-2 has been a serious public health crisis. Development of novel and specific antiviral drugs against the SARS-CoV-2 has been an urgent demand. One such drug is Favipiravir, initially developed as an antiviral drug against influenza. Now Favipiravir has received approvals for emergency use against SARS-CoV-2 in many countries. A better understanding of Favipiravir’s biodistribution and pharmacokinetics in vivo will facilitate the clinical development of antiviral drugs against the SARS-CoV-2. Herein, we reported the evaluation of [18 F]Favipiravir with PET in cross-species studies to demonstrate the drug’s biodistribu-tion and pharmacokinetics and investigate the potentially increased risk of neurodegenerative diseases and/or neuroinflammation to COVID-19. Methods: The radiosynthesis of [18 F]Favipiravir was via labeling a commercially available precursor, methyl-5-chloroisoxazolo[4,5-b] pyrazine-3-carboxylate with K[18F]F/K222 and K2CO3 in DMSO at 130°C for 10 min, followed by hydrolysis with NaOH (aq.) at 110°C for 15 min.1 The whole body distribution on CD-1 mice was performed at four time points (5, 15, 30, 60 min). PET studies were carried out in CD-1 mice and AD mice (5XFAD) and naïve rhesus monkeys. We also performed the radiometabolite analysis of [18 F]Favipiravir in plasma and brain of CD-1 mice at 30 min post-injection. Results: [18 F]Favipiravir was obtained in 29% isolated radiochemi-cal yield (decay corrected). The radiochemical purity of the tracer was greater than 99%. No sign of radiolysis was observed for [18F] Favipiravir up to 120 min after formulation with 10% EtOH/saline. High radioactivity accumulation was observed in blood, lung, liver, kidney, and bone (around or more than 5% ID/g, injected dose per gram of wet tissue). The radioactivity level reached a plateau in small intestine, kidney and liver at 30,15 and 5 min, respectively, followed by slow washout, indicating that [18F]Favipiravir was possibly eliminated via the hepatobiliary and urinary pathway. For the radio-metabolic analysis of [18F]Favipiravir, average 41% and 89% of the radioactivity was parent fraction in the mice brain and plasma at 30 min post-injection (n=2), respectively. In PET imaging of CD-1 mice, the standard uptake value (SUV) of [18F]Favipiravir in brain reached its max value of 0.5 at 10 min and slowly reduced to 0.4 at 60 min. The results of PET imaging of AD mice with [18 F]Favipiravir were similar with that of CD-1 mice. In PET imaging of Rhesus monkeys, the brain uptake of [18 F]Favipiravir reached the max value of 0.5 SUV at 5 min and subsequently decreased to 50-60% of the maximum at 60 min. Conclusion: The evaluation of [18F]Favipiravir has demonstrated with bio-distribution and PET in mice and NHPs. Further evaluation of pharmacokinetics of [18F]Favipiravir in whole body monkey scans and LPS-induced neuroinflammation models is underway.
ABSTRACT
AlGaN-based deep ultraviolet light-emitting diodes (UV LEDs) have gained rapidly growing attention due to their wide applications in water purification, air disinfection, and sensing as well as optical communication. Moreover, deep UV radiation has been verified as one of effective way to inactivate COVID-19. However, although numerous efforts have been made in deep UV LED chips, the reported highest external quantum efficiency (EQE) of them is 20.3%, which is far lower than that of visible LEDs. The EQE of commercial packaged AlGaN-based deep UV LEDs is usually lower than 5%, which will cause serious reliability problems as well. Therefore, it is very urgent to improve EQE and reliability of the devices from packaging level. In this review, a systematical summarization about the packaging technologies of AlGaN-based deep UV LEDs has been analyzed and future prospects have been made as well. Firstly, this work provides a brief overview of the devices and analyzes why the packaging level reduces EQE and reliability in theory. Then, systematically reviews the recent advances in packaging technologies and deep UV micro-LEDs. Finally, conclusions and outlooks are given as well. This review is of great significance for promoting the development of the packaging technologies for AlGaN-based deep UV LEDs. © 2022 Wiley-VCH GmbH
ABSTRACT
In this paper, we present a hybrid deep learning framework named CTNet which combines convolutional neural network (CNN) and transformer together for the detection of COVID-19 via 3D chest CT images. It consists of a CNN feature extractor module with SE attention to extract sufficient features from CT scans, together with a transformer model to model the discriminative features of the 3D CT scans. Compared to previous works, CTNet provides an effective and efficient method to perform COVID-19 diagnosis via 3D CT scans with data resampling strategy. Advanced results on a large and public benchmarks, COV19-CT-DB database, was achieved by the proposed CTNet with a macro F1 score of 88.21% on the validation set, which lead ten percentage over the state-of-the-art baseline approach proposed together with the dataset. Notably, the inference speed of the proposed framework is about ten times faster than that of the typical CNN frameworks which make it more promising in actual applications.
ABSTRACT
There are a lot of ongoing efforts to combat the COVID-19 pandemic using different combinations of low-cost sensing technologies, information/communication technologies, and smart computation. To provide COVID-19 situational awareness and early warnings, a scalable, real-time sensing solution is needed to recognize risky behaviors in COVID-19 virus spreading such as coughing and sneezing. Various coughing and sneezing recognition methods use audio-only or video-only sensors and Deep Learning (DL) algorithms for smart event recognition. However, each of these recognition processes experiences several types of failure behaviors due to false detection. Sensor integration is a solution to overcome such failures. Moreover, it improves event recognition precision. With the wide availability of low-cost audio and video sensors, we proposed a real-time integrated Internet of Things (IoT) architecture to improve the results of coughing and sneezing recognition. Implemented architecture joins edge and cloud computing. In edge computing, the microphone and camera are connected to the internet and embedded with a DL engine. Audio and video streams are fed to edge computing to detect coughing and sneezing actions in realtime. Cloud computing, which is developed based on the Amazon Web Service (AWS), combines the results of audio and video processing. In this paper, a scenario of a person coughing and sneezing was developed to demonstrate the capabilities of the proposed architecture. The experimental results show that the proposed architecture improved the reliability of coughing and sneezing recognition in the integrated cloud system compared to audio-only and video-only detectors. Three factors have been considered to compare the results of the proposed architecture: F-score, precision, and recall. The precision and recall of the cloud detector are improved on average by %43 and %15, respectively, compared to audio-only and video-only detectors. The F-score improved on average 1.24 times. © 2021 IEEE.
ABSTRACT
Objectives: This study aimed to characterize the 30-day readmission in hospitalized COVID-19 patients. Methods: We conducted an observational cohort study including adult hospitalized COVID-19 patients admitted between 07/01/2020 and 01/31/2021 using a large inpatient chargemaster (billing) linked with open administrative healthcare claims database. The first COVID-19 hospitalization in the study period was considered as the index hospitalization. Readmission was assessed within 30 days of discharge. Results: We identified 111,624 COVID-19 patients admitted to 327 hospitals with 13% (N=14,763) mortality rate during index hospitalization. Among 61,182 patients discharged alive with ≥30-day follow-up, the overall all-cause readmission rate was 16% (N=9,748) and remained stable between 15% and 17% over the study period. 32% (N=19,770) of the discharged patients were treated with remdesivir (RDV) during their index hospitalization, and readmission was lower in RDV-treated patients (13%, N=2,627) compared to those not treated with RDV during their index hospitalization (17%, N=7,121). Among patients who received RDV in their initial hospitalization, those who started therapy upon admission (Day 1 or 2) had lower readmission rates (12%), compared to those who received RDV later in the hospitalization course, 15% (Day 3-5) and 27% (Day >5). The most frequent diagnoses upon readmission were COVID-19 (63%), other viral pneumonia (36%), and acute respiratory failure with hypoxia (34%). Compared to non-readmitted, readmitted patients were older (60 vs 65), had more comorbidities such as COPD (24% vs 37%) and congestive heart failure (28% vs 44%), and longer median LOS (6 vs 7 days) during index hospitalization. Conclusions: This study of a large and geographically diverse population revealed substantial burden on patients beyond the initial COVID-19 hospitalization, as 16% of the patients were re-admitted within 30-days. Over the study period, lower readmission was observed in patients who were treated with RDV during their index hospitalization.
ABSTRACT
Introduction: Chinese patent medicine (CPM) is an indispensable part of traditional Chinese medicine. Coronavirus Disease 2019 (COVID-19) manifests is an acute respiratory infectious disease. This systematic review aimed to evaluate the therapeutic effects and safety of oral CPM for COVID-19. Methods: We included randomized controlled trials (RCTs) that tested oral CPM for the treatment of COVID-19 identified from publications in CNKI, Wanfang, VIP, Web of Science, SinoMed, PubMed, Embase, BioRxiv, MedRxiv and arXiv before November 2nd, 2020. The risk of bias for each trial was assessed using the Cochrane Risk of Bias Tool 2.0. RevMan 5.4 software was used for data analyses. The certainty of the evidence was assessed using the online GRADEpro tool. Results: Seven RCTs including 1079 participants were identified. The overall bias was assessed as “some concerns” for all included trials. Oral CPM investigated were: Lianhua Qingwen capsule/granules (连花清瘟胶囊/颗粒, LHQW), Jinhua Qinggan granules (金花清感颗粒, JHQG), Huoxiang Zhengqidripping pills (藿香正气滴丸, HXZQ), Toujie Quwen granules (透解祛瘟颗粒, TJQW) and Lianhua Qingke granules (连花清咳颗粒, LHQK). Compared with conventional western therapy alone for people with COVID-19: regarding the main outcomes, the results showed that oral CPM combined with conventional western therapy improved cure rate (RR = 1.20, 95% CI 1.04 to 1.38, involving LHQW and TJQW), reduced aggravation rate (RR = 0.50, 95% CI 0.29 to 0.85, involving LHQW, JHQG, LHQK and TJQW);with regard to additional outcomes, the results showed that add-on oral CPM shortened the duration of fever, cough and fatigue, improved the recovery rate of cough and fatigue, and increased the improvement and recovery rate of chest CT manifestations. There were some differences in therapeutic effects among various CPMs for the same COVID-19 outcome. The use of TJQW and LHQG appeared not to increase the risk of adverse events, but JHQG may cause mild diarrhea. Conclusions: Low-certainty or very low-certainty evidence demonstrated that oral CPM may have add-on potential therapeutic effects for patients with non-serious COVID-19. There are some differences in therapeutic effects between different oral CPMs for the same outcome of COVID-19. The use of TJQW and LHQG probably does not increase the risk of adverse events, but JHQG may cause mild diarrhea in patients. The conclusion of this review needs to be further confirmed by well-designed clinical trials with adequate sample sizes. Keywords: Coronavirus Disease 2019;COVID-19;Chinese patent medicine;Chinese herbal medicine;Systematic review;Meta-analysis
ABSTRACT
Introduction: Coronavirus Disease 2019 (COVID-19) is an acute respiratory infectious disease. At present, there is no specific and effective therapy for the treatment and prevention of this disease. Traditional Chinese medicine (TCM) has accumulated thousands of years of experience on the use of Chinese herbal medicine (CHM) to prevent and treat infectious diseases. The aim of this study was to present the evidence on the therapeutic effects and safety of Chinese herbal medicine (CHM) used with or without conventional western therapy for COVID-19. Methods: Clinical studies on the therapeutic effects and safety of CHM for COVID-19 were included. We summarized the general characteristics of included studies, evaluated methodological quality of randomized controlled trials (RCTs) using the Cochrane risk of bias tool, analyzed the use of CHM, used Revman 5.4 software to present the risk ratio (RR) or mean difference (MD) and their 95% confidence interval (CI) to estimate the therapeutic effects and safety of CHM. Results: A total of 58 clinical studies were identified including RCTs (17.24%, 10), non-randomized controlled trials (1.72%, 1), retrospective studies with a control group (18.97%, 11), case-series (20.69%, 12) and case-reports (41.38%, 24). Fig.1 shows the flow diagram for the searching and screening of published articles. No RCTs of high methodological quality were identified. The most frequently tested oral Chinese patent medicine, Chinese herbal medicine injection or prescribed herbal decoction were: Lianhua Qingwen granule/capsule, Xuebijing injection and Maxing Shigan Tang. Table 1 lists the CHM used at least twice. In terms of aggravation rate, pooled analyses showed that there were statistical differences between the intervention group and the comparator group (RR 0.42, 95% CI 0.21 to 0.82, six RCTs;RR 0.38, 95% CI 0.23 to 0.64, five retrospective studies with a control group), that is, CHM plus conventional western therapy appeared better than conventional western therapy alone in reducing aggravation rate. In addition, compared with conventional western therapy, CHM plus conventional western therapy had potential advantages in increasing the recovery rate and shortening the duration of fever, cough and fatigue, improving the negative conversion rate of nucleic acid test, and increasing the improvement rate of chest CT manifestations and shortening the time from receiving the treatment to the beginning of chest CT manifestations improvement. For adverse events, pooled data showed that there were no statistical differences between the CHM and the control groups. Conclusion: Current low certainty evidence suggests that there may be a tendency that CHM plus conventional western therapy is superior to conventional western therapy alone. The use of CHM did not increase the risk of adverse events. Keywords: traditional Chinese medicine, Chinese herbal medicine, novel coronavirus pneumonia, coronavirus disease 2019, COVID-19, SARS-CoV-2, review, clinical study
ABSTRACT
Introduction: Standard frontline therapy for patients with advanced ALK-NSCLC has rapidly evolved to 2nd generation ALK TKIs based on superior survival. Regardless, resistance to treatment is inevitable. Most will receive multiple lines of TKIs +/- chemotherapy before eventually dying from the disease. Lorlatinib is a 3rd generation ALK TKI active against a broad range of acquired ALK kinase domain (KD) resistance mutations. A recent report demonstrated re-sensitization to crizotinib by the lorlatinib ALK resistance mutation L1198F. Increased knowledge of the resistance mechanisms is key to overcoming its emergence. Recent reports have detailed diverse compound ALK mutations and frequent ALK independent mechanisms, including MET activation. Based on knowledge of the varying patterns of resistance to different ALK TKIs, ALKternate is testing the hypothesis that treatment with alternating TKIs will re-equilibrate the selection pressure for enrichment of resistant clones. Methods: ALKternate is a proof of concept open label multi-centre translational study alternating lorlatinib (100mg OD) with crizotinib (250mg BD) (Figure 1. including eligibility). The aim is to identify whether this fixed alternating schedule of ALK TKI is: safe;feasible and active, resulting in prolonged systemic and intracranial disease control via delaying the emergence of ALK TKI resistance. A secondary aim is to investigate whether plasma ALK-dependent and independent resistance profiles can be used to monitor therapy effectiveness. The primary outcome measure is time to treatment failure (TTTF) with alternating therapy. Secondary end points include best OR, PK analysis, PFS, DCR (systemic and CNS) after lorlatinib induction and the first cycle of alternating therapy, OS, toxicity, PROs and QOL measures. Plasma ctDNA and proteomic biomarkers will be analysed. See preliminary results in accompanying abstract #418. Enrolled patients must demonstrate disease control after induction lorlatinib to continue alternating therapy. Imaging occurs more frequently initially (Figure 1.), before 12- weekly after two alternating cycles in those with disease control. Enrollment began Q3 2019. In 2020 the trial saw delays and halted recruitment due to the COVID-19 pandemic. In 2021 it is open and recruiting. Trial registration number: ACTRN12619000844145. [Formula presented] RECIST PD- Radiological Response Evaluation Criteria in Solid Tumors, Version 1.1, defined progressive disease Figure 1. ALKternate trial schema Results: ▪▪▪ Conclusion: ▪▪▪ Keywords: Drug resistance, ALK, Clinical trial