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IntroductionDeep learning-based methods can promote and save critical time for the diagnosis of pneumonia from computed tomography (CT) images of the chest, where the methods usually rely on large amounts of labeled data to learn good visual representations. However, medical images are difficult to obtain and need to be labeled by professional radiologists.MethodsTo address this issue, a novel contrastive learning model with token projection, namely CoTP, is proposed for improving the diagnostic quality of few-shot chest CT images. Specifically, (1) we utilize solely unlabeled data for fitting CoTP, along with a small number of labeled samples for fine-tuning, (2) we present a new Omicron dataset and modify the data augmentation strategy, i.e., random Poisson noise perturbation for the CT interpretation task, and (3) token projection is utilized to further improve the quality of the global visual representations.ResultsThe ResNet50 pre-trained by CoTP attained accuracy (ACC) of 92.35%, sensitivity (SEN) of 92.96%, precision (PRE) of 91.54%, and the area under the receiver-operating characteristics curve (AUC) of 98.90% on the presented Omicron dataset. On the contrary, the ResNet50 without pre-training achieved ACC, SEN, PRE, and AUC of 77.61, 77.90, 76.69, and 85.66%, respectively.ConclusionExtensive experiments reveal that a model pre-trained by CoTP greatly outperforms that without pre-training. The CoTP can improve the efficacy of diagnosis and reduce the heavy workload of radiologists for screening of Omicron pneumonia.

Considering the poor efficacy of drug treatment, the non-drug therapy is vital for Alzheimer’s disease (AD). As an ultimate form of Internet, Metaverse will become mainstream industry in the future. This thesis reviews advances in non-drug therapy (Reminiscence Therapy, Music Therapy, Horticultural Therapy, Animal-Assisted Therapy) of Alzheimer’s disease and introduce the Metaverse and its application in field of medicine. Finally, the author thinks Metaverse will be used to store human’s memories and proposed Metaverse Therapy for AD patients as one of the non-drug treatment in the future.

Over the last decade, artificial intelligence in medicine has attracted much attention and interest for its robust automation and efficiency in disease diagnosis, treatment and prognosis. It has shown great potential in bringing the revolutionary change in clinical practice. This review aimed to summarize the progress AI has made recently in several fields of medicine, including patient screening, diagnosis and treatment of cancerous and non-cancerous diseases, pharmaceutical development, clinical trial management and basic science. Meanwhile, we will discuss its future direction and important considerations, focusing on its utility, usability, validation, safety and ethnic problem.

Lung cancer is the leading cause of cancer-related deaths worldwide. Early diagnosis and treatment play a crucial role in improving the prognosis for lung cancer. However, the issue of overtreatment and delayed diagnosis remains prevalent due to the considerable limitations of manual film review in facilitating early detection and treatment of lung cancer. In recent years, artificial intelligence (AI) has emerged as a valuable tool for clinicians to screen and evaluate benign and malignant pulmonary nodules, offering numerous advantages. Nevertheless, the sensitivity and specificity of AI are neither sufficient to completely replace medical experts nor capable of assuming direct responsibility for clinical diagnosis and treatment.Therefore, we propose the concept of a Human-Computer Multi-Disciplinary Team (MDT), which involves collaborative decision-making between human physicians and AI systems. The human-computer MDT approach in pulmonary nodule evaluation presents a novel model for diagnosis and treatment, leveraging the respective strengths of human expertise and AI capabilities. This review provides an overview of the background, medical application, advantages and limitations, future trends, and reporting format of the Human-Computer MDT in pulmonary nodule evaluation.Its aim is to explore standardized methods for enhancing early diagnosis in lung cancer. With the rapid advancement of AI and the field of meta-cosmic medicine, human-computer MDT are expected to become more widespread and play an important role in the implementation of the Healthy China 2030 plan, particularly in improving primary medical care in the future.

Summary: Background: The prevalence, epidemiological and clinical heterogeneities, and impact profiles of individuals with preserved ratio impaired spirometry (PRISm), pre-COPD, young COPD, and mild COPD in general Chinese population were not known yet. Methods: Data were obtained from the China Pulmonary Health study (2012–2015), a nationally representative cross-sectional survey that recruited 50,991 adults aged 20 years or older. Definitions of the four early disease status were consistent with the latest publications and the Global Initiative for Chronic Obstructive Lung Disease criteria. Findings: The age-standardised prevalences of PRISm, pre-COPD, young COPD, and mild COPD were 5.5% (95% confidence interval, 4.3–6.9), 7.2% (5.9–8.8), 1.1% (0.7–1.8), and 3.1% (2.5–3.8), respectively. In summary, mild COPD was under more direct or established impact factor exposures, such as older age, male gender, lower education level, lower family income, biomass use, air pollution, and more accumulative cigarette exposures; young COPD and pre-COPD experienced more personal and parents’ events in earlier lives, such as history of bronchitis or pneumonia in childhood, frequent chronic cough in childhood, parental history of respiratory diseases, passive smoke exposure in childhood, and mother exposed to passive smoke while pregnant; pre-COPD coexisted with heavier symptoms and comorbidities burdens; young COPD exhibited worse airway obstruction; and most of the four early disease status harbored small airway dysfunction. Overall, older age, male gender, lower education level, living in the urban area, occupational exposure, frequent chronic cough in childhood, more accumulated cigarette exposure, comorbid with cardiovascular disease and gastroesophageal reflux disease were all associated with increased presence of the four early COPD status; different impact profiles were additionally observed with distinct entities. Over the four categories, less than 10% had ever taken pulmonary function test; less than 1% reported a previously diagnosed COPD; and no more than 13% had received pharmaceutical treatment. Interpretation: Significant heterogeneities in prevalence, epidemiological and clinical features, and impact profiles were noted under varied defining criteria of early COPD; a unified and validated definition for an early disease stage is warranted. Closer attention, better management, and further research need to be administrated to these population. Funding: Chinese Academy of Medical Sciences Institute of Respiratory Medicine Grant for Young Scholars (No. 2023-ZF-9); China International Medical Foundation (No. Z-2017-24-2301); Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (No. 2021-I2M-1-049); National High Level Hospital Clinical Research Funding (No. 2022-NHLHCRF-LX-01); Major Program of National Natural Science Foundation of China (No. 82090011).

Summary: Background: Effective monitoring and management are crucial during long-term home noninvasive positive pressure ventilation (NPPV) in patients with hypercapnic chronic obstructive pulmonary disease (COPD). This study investigated the benefit of Internet of Things (IOT)-based management of home NPPV. Methods: This multicenter, prospective, parallel-group, randomized controlled non-inferiority trial enrolled patients requiring long-term home NPPV for hypercapnic COPD. Patients were randomly assigned (1:1), via a computer-generated randomization sequence, to standard home management or IOT management based on telemonitoring of clinical and ventilator parameters over 12 months. The intervention was unblinded, but outcome assessment was blinded to management assignment. The primary outcome was the between-group comparison of the change in health-related quality of life, based on severe respiratory insufficiency questionnaire scores with a non-inferiority margin of −5. This study is registered with Chinese Clinical Trials Registry (No. ChiCTR1800019536). Findings: Overall, 148 patients (age: 72.7 ± 6.8 years; male: 85.8%; forced expiratory volume in 1 s: 0.7 ± 0.3 L; PaCO2: 66.4 ± 12.0 mmHg), recruited from 11 Chinese hospitals between January 24, 2019, and June 28, 2021, were randomly allocated to the intervention group (n = 73) or the control group (n = 75). At 12 months, the mean severe respiratory insufficiency questionnaire score was 56.5 in the intervention group and 50.0 in the control group (adjusted between-group difference: 6.26 [95% CI, 3.71–8.80]; P

BackgroundMaternal smoking during pregnancy (MSDP) is a known risk factor for offspring developing chronic obstructive pulmonary disease (COPD), but the underlying mechanism remains unclear. ObjectiveThis study aimed to explore whether the increased COPD risk associated with MSDP could be attributed to tobacco dependence (TD). MethodsThis case-control study used data from the nationwide cross-sectional China Pulmonary Health study, with controls matched for age, sex, and smoking status. TD was defined as smoking within 30 minutes of waking, and the severity of TD was assessed using the Fagerstrom Test for Nicotine Dependence. COPD was diagnosed when the ratio of forced expiratory volume in 1 second to forced vital capacity was

Abstract Background Patients who possess various histological subtypes of early‐stage lung adenocarcinoma (LUAD) have considerably diverse prognoses. The simultaneous existence of several histological subtypes reduces the clinical accuracy of the diagnosis and prognosis of early‐stage LUAD due to intratumour intricacy. Methods We included 11 postoperative LUAD patients pathologically confirmed to be stage IA. Single‐cell RNA sequencing (scRNA‐seq) was carried out on matched tumour and normal tissue. Three formalin‐fixed and paraffin‐embedded cases were randomly selected for 10× Genomics Visium analysis, one of which was analysed by digital spatial profiler (DSP). Results Using DSP and 10× Genomics Visium analysis, signature gene profiles for lepidic and acinar histological subtypes were acquired. The percentage of histological subtypes predicted for the patients from samples of 11 LUAD fresh tissues by scRNA‐seq showed a degree of concordance with the clinicopathologic findings assessed by visual examination. DSP proteomics and 10× Genomics Visium transcriptomics analyses revealed that a negative correlation (Spearman correlation analysis: r = –.886; p = .033) between the expression levels of CD8 and the expression trend of programmed cell death 1(PD‐L1) on tumour endothelial cells. The percentage of CD8+ T cells in the acinar region was lower than in the lepidic region. Conclusions These findings illustrate that assessing patient histological subtypes at the single‐cell level is feasible. Additionally, tumour endothelial cells that express PD‐L1 in stage IA LUAD suppress immune‐responsive CD8+ T cells.

ObjectivesThis study aimed to explore the value of an artificial intelligence (AI)-assisted diagnostic system in the prediction of pulmonary nodules.MethodsThe AI system was able to make predictions of benign or malignant nodules. 260 cases of solitary pulmonary nodules (SPNs) were divided into 173 malignant cases and 87 benign cases based on the surgical pathological diagnosis. A stratified data analysis was applied to compare the diagnostic effectiveness of the AI system to distinguish between the subgroups with different clinical characteristics.ResultsThe accuracy of AI system in judging benignity and malignancy of the nodules was 75.77% (p

ABSTRACTAlthough gut microbiota has been linked to cancer, little is known about the crosstalk between gut- and intratumoral-microbiomes. The goal of this study was to determine whether gut Akkermansia muciniphila (Akk) is involved in the regulation of intratumoral microbiome and metabolic contexture, leading to an anticancer effect on lung cancer. We evaluated the effects of gut endogenous or gavaged exogenous Akk on the tumorigenesis using the Lewis lung cancer mouse model. Feces, blood, and tumor tissue samples were collected for 16S rDNA sequencing. We then conducted spatially resolved metabolomics profiling to discover cancer metabolites in situ directly and to characterize the overall Akk-regulated metabolic features, followed by the correlation analysis of intratumoral bacteria with metabolic network. Our results showed that both endogenous and exogenous gavaged Akk significantly inhibited tumorigenesis. Moreover, we detected increased Akk abundance in blood circulation or tumor tissue by 16S rDNA sequencing in the Akk gavaged mice, compared with the control mice. Of great interest, gavaged Akk may migrate into tumor tissue and influence the composition of intratumoral microbiome. Spatially resolved metabolomics analysis revealed that the gut-derived Akk was able to regulate tumor metabolic pathways, from metabolites to enzymes. Finally, our study identified a significant correlation between the gut Akk-regulated intratumoral bacteria and metabolic network. Together, gut-derived Akk may migrate into blood circulation, and subsequently colonize into lung cancer tissue, which contributes to the suppression of tumorigenesis by influencing tumoral symbiotic microbiome and reprogramming tumoral metabolism, although more studies are needed.

IntroductionTumor-associated autoantibodies have been revealed as promising biomarkers for the early detection of lung cancer. This study was designed to develop an autoantibody panel for early detection of lung cancer in the Chinese population.MethodsRecruited prospectively in three clinical centers, the subjects (n = 991) who had a definite diagnosis during follow-up were included in the development of the autoantibody panel. The levels of 14 autoantibody candidates in plasma were detected.ResultsA panel of nine autoantibody markers (named as CN9), namely, P53, SOX2, SSX1, HuD, NY-ESO-1, CAGE, MAGE-A4, P62, and CK20, was preferably selected from 14 candidates. The overall specificity, sensitivity, and AUC were 90.5%, 40.8%, and 0.64, respectively. The CN9 panel demonstrated a reasonable detection rate in lung cancer patients at all stages, histological types, sizes of lesions, and risk levels. Its estimated overall accuracy is 85.5% and 90%, with PPV at 0.32 and 0.04, and NPV at 0.93 and 0.99 in the scenario of pulmonary nodules' characterizing and lung cancer screening, respectively. Two risk models were developed within the subgroups of malignant and benign pulmonary nodules in this study. By adding the CN9 result to the Mayo model indicators, it achieved a sensitivity of 41.3% and an AUC of 0.74 at a specificity of 91.3%. By adding the CN9 result to the Brock model indicators, it achieved a sensitivity of 47.7% and an AUC of 0.78 at a specificity of 91.3%. Both were improved compared with either the standalone Mayo or Brock model.DiscussionThis multi-center prospective study indicates a panel of nine autoantibody markers that can help in the detection of lung cancer and the classification of pulmonary nodules in the Chinese population.

Background and objective There have been many significant advances in the diagnosis and treatment of non-small cell lung cancer (NSCLC). However, the mechanism underlying the progression of NSCLC is still not clear. Plant homodomain finger-like domain-containing protein 5A (PHF5A) plays an important role in processes of chromatin remodeling, morphological development of tissues and organs and maintenance of stem cell pluripotency. This study aims to investigate the role of PHF5A in the proliferation and migration of NSCLC. Methods A549 and PC-9 PHF5A overexpression cell lines were constructed. PHF5A expression was decreased in H292 and H1299 cells by using siRNA. Flow cytometry was used to detect the cell cycle. MTT assay and clone formation assay were used to examine the proliferative ability of NSCLC, while migration assay and wound healing assay were performed to evaluate the ability of migration. Western blot analysis was used to measure the expressions of PI3K, p-AKT and the associated downstream factors. Results Up-regulation of PHF5A in A549 and PC-9 cells increased the proliferation rate, while down-regulation of PHF5A in H292 and H1299 cells inhibited the proliferation rate at 24 h, 48 h and 72 h (P

Abstract Background Evidence from previous studies has suggested that ginger extract exhibits the potential as an alternative treatment for Coronavirus disease 2019 (COVID-19). Here, we want to investigate whether ginger supplement improves the clinical manifestation of hospitalized COVID-19 individuals. Methods A total of 227 hospitalized individuals with COVID-19 were randomized to either the control (n = 132) or intervention group (n = 95). The intervention group took ginger supplement orally at the dosage of 1.5 g twice daily, until they were discharged from the hospital. Both groups received the same standard of general medical care during hospitalization, and the length of stay was recorded and compared between groups. Results Among all participants, a significant reduction in hospitalization time (the difference between the treatment and control groups was 2.4 d, 95% CI 1.6–3.2) was detected in response to the ginger supplement. This effect was more pronounced in men, participants aged 60 years or older, and participants with pre-existing medical conditions, relative to their counterparts (P-interactions

Background: Recently, Professor Chunxue Bai and colleagues have proposed a definition of the Metaverse in Medicine as the medical Internet of Things (MIoT) facilitated using AR and/or VR glasses. Methods: A multi-disciplinary panel of doctors and IT experts from Asia, the United States, and Europe analyzed published articles regarding expert consensus on the Medical Internet of Things, with reference to study results in the field of metaverse technology. Findings: It is feasible to implement the three basic functions of the MIoT, namely, comprehensive perception, reliable transmission, and intelligent processing, by applying a metaverse platform, which is composed of AR and VR glasses and the MIoT system, and integrated with the technologies of holographic construction, holographic emulation, virtuality-reality integration, and virtuality-reality interconnection. In other words, through interactions between virtual and real cloud experts and terminal doctors, we will be able to carry out medical education, science popularization, consultation, graded diagnosis and treatment, clinical research, and even comprehensive healthcare in the metaverse. The interaction between virtual and real cloud experts and terminal users (including terminal doctors, patients, and even their family members) could also facilitate different medical services, such as disease prevention, healthcare, physical examination, diagnosis and treatment of diseases, rehabilitation, management of chronic diseases, in-home care, first aid, outpatient attendance, consultation, etc. In addition, it is noteworthy that security is a prerequisite for the Metaverse in Medicine, and a reliable security system is the foundation to ensure the normal operation of such a platform. Conclusion: The application of a Cloud Plus Terminal platform could enable interaction between virtual and real cloud experts and terminal doctors, in order to realize medical education, science popularization, consultation, graded diagnosis and treatment, clinical research, and even comprehensive healthcare in the metaverse.

The emergence of the Medical Internet of Things (MIoT) has presented an opportune solution to these problems, as it provides effective technological support. Based on the current MIoT theory, it is feasible to realize efficient and accurate graded diagnosis and treatment through the linkage between doctors in large hospitals (the ‘Cloud Experts’) and doctors in small hospitals (the ‘Terminal Doctors’), and to contribute to the research and development of related technologies to improve graded diagnosis and treatment in China. Nevertheless, the following issues remain in clinical practice: (1) The Cloud Experts are not available to dedicate themselves to popular science education, or to give professional lectures, at all times and in all settings. (2) The Cloud Experts are not available to provide guidance for the Terminal Doctors on diagnosis and treatment at all times and in all settings. (3) In clinical trials, the main researchers are not available to monitor the research or guide the team at all times and in all settings. (4) Due to the lack of real-time quality control at all times and in all settings, non-standard diagnosis and treatment, with the features of a handicraft workshop, still exist to a considerable degree. The real cause lies in the limitations of the Internet technology itself, which cannot facilitate communication at all times and in all settings between the Cloud Experts and the Terminal Doctors involved in graded diagnosis and treatment. Therefore, the MIoT-based digital platforms need to be further improved, especially concerning the communication and interactions between humans and computers, and the integration and linkage between the virtual and real worlds. It is gratifying that the concept of the metaverse has been introduced, which provides a possible solution to all these problems, and serves as a foundation for the proposal and development of the Metaverse in Medicine.

Background: The outbreak of coronavirus disease 2019 (COVID-19) has become a global pandemic acute infectious disease, especially with the features of possible asymptomatic carriers and high contagiousness. Currently, it is difficult to quickly identify asymptomatic cases or COVID-19 patients with pneumonia due to limited access to reverse transcription-polymerase chain reaction (RT-PCR) nucleic acid tests and CT scans. Goal: This study aimed to develop a scientific and rigorous clinical diagnostic tool for the rapid prediction of COVID-19 cases based on a COVID-19 clinical case database in China, and to assist doctors to efficiently and precisely diagnose asymptomatic COVID-19 patients and cases who had a false-negative RT-PCR test result. Methods: With online consent, and the approval of the ethics committee of Zhongshan Hospital Fudan University (NCT04275947, B2020-032R) to ensure that patient privacy is protected, clinical information has been uploaded in real-time through the New Coronavirus Intelligent Auto-diagnostic Assistant Application of cloud plus terminal (nCapp) by doctors from different cities (Wuhan, Shanghai, Harbin, Dalian, Wuxi, Qingdao, Rizhao, and Bengbu) during the COVID-19 outbreak in China. By quality control and data anonymization on the platform, a total of 3,249 cases from COVID-19 high-risk groups were collected. The effects of different diagnostic factors were ranked based on the results from a single factor analysis, with 0.05 as the significance level for factor inclusion and 0.1 as the significance level for factor exclusion. Independent variables were selected by the step-forward multivariate logistic regression analysis to obtain the probability model. Findings: We applied the statistical method of a multivariate regression model to the training dataset (1,624 cases) and developed a prediction model for COVID-19 with 9 clinical indicators that are accessible. The area under the receiver operating characteristic (ROC) curve (AUC) for the model was 0.88 (95% CI: 0.86, 0.89) in the training dataset and 0.84 (95% CI: 0.82, 0.86) in the validation dataset (1,625 cases). Discussion: With the assistance of nCapp, a mobile-based diagnostic tool developed from a large database that we collected from COVID-19 high-risk groups in China, frontline doctors can rapidly identify asymptomatic patients and avoid misdiagnoses of cases with false-negative RT-PCR results.

Chronic respiratory diseases are staggering health burdens affecting the lives of hundreds of millions of people around the world, contributing substantially to mortality and morbidity globally, including in the United States, China and Europe. Chronic obstructive pulmonary disease (COPD), lung cancer, pneumonia, interstitial lung disease (ILD) and asthma are among the leading diseases that urges the development of effective prevention, diagnosis, treatment and management of these diseases. Medical Internet-of-Things (MIOT) is fast becoming one of the most promising approaches to achieve this largely due to its cost effectiveness, non-invasive deployments and automation capabilities. Coupled together with strategically leveraging artificial intelligence, continuous data collection and real time monitoring and response systems, MIOT shows potential to be an effective and efficient solution.

The metaverse has entered people's horizons through virtual reality, digital twinning, the Internet of Things, blockchain technology, etc. In the current healthcare system, the management of chronic diseases, such as chronic obstructive pulmonary disease (COPD) and obstructive sleep apnea-hypopnea syndrome (OSAHS), still faces challenges, such as uneven distribution of medical resources, and difficulty in follow-up, overburdening of specialists, and so on. However, metaverse medical platforms incorporating advanced AI technologies, such as industrial-scale digital twins, may address these issues. In this article, we discuss the application prospect of these technologies in digital medicine and the future of the medical metaverse.

Lung cancer is the leading cause of cancer deaths. Although targeted therapies and programmed cell death protein 1 (PD-1) blockade have offered great advances, five-year survival rates remained low. Diagnosis of lung cancer at an earlier stage is the most efficient approach to improve survival. Tumor associated autoantibodies (TAAb) have been proven a promising innovative biomarker of lung cancer. We aimed to comprehensively evaluate the sensitivity, specificity, and accuracy of TAAbs in lung cancer detection, especially in early-stage patients, through a multicenter prospective observational clinical trial, and to screen out the novel combination of TAAbs with the best detection value for Chinese population. We aimed to enroll 1,400 participants from three clinical centers and divide into two cohorts. One cohort is participants with newly pathologically confirmed lung cancer as the case cohort, and the other is participants with benign nodules, matched healthy controls and other benign lung diseases as the control cohort. Cases and controls were randomly distributed into training or validation set. The level of 14 autoantibody candidates in their plasma were detected. A Monte-Carlo Simulated Annealing method was implemented to develop a composite panel of autoantibodies to distinguish between matched lung cancer cases and controls in the training set. The newly developed autoantibody panel was tested in the validation set for sensitivity, specificity and accuracy. This is the first and largest clinical trial designed to develop a novel autoantibody panel for lung cancer detection specifically for Chinese people. We performed a multicenter, prospective, observational study to find a novel panel of autoantibody markers that can help the diagnosis of lung cancer and the characterization of pulmonary nodules in Chinese population. The results may help to provide evidence-based recommendations to clinicians for lung cancer early detection and pulmonary nodule management. This study is registered in the ClinicalTrials.gov (NCT04216511).

Objective We aimed to establish an easy-to-use screening questionnaire with risk factors and suspected symptoms of COPD for primary health care settings. Methods Based on a nationwide epidemiological study of pulmonary health among adults in mainland China (China Pulmonary Health, CPH study) between 2012 and 2015, participants ≥40 years who completed the questionnaire and spirometry tests were recruited and randomly divided into development set and validation set by the ratio of 2:1. Parameters including sex, age, BMI, residence, education, smoking status, smoking pack-years, biomass exposure, parental history of respiratory diseases and daily respiratory symptoms were initially selected for the development of scoring system. Receiver operating characteristic (ROC) curve, area under curve (AUC), positive and negative predictive values were calculated in development set and validation set. Results After random split by 2:1 ratio, 22443 individuals were assigned to development set and 11221 to validation set. Ten variables were significantly associated with COPD independently in development set after a stepwise selection by multivariable logistic model and used to develop scoring system. The scoring system yielded good discrimination, as measured by AUC of 0.7737, and in the validation set, the AUC was 0.7711. When applying a cutoff point of ≥16, the sensitivity in development set was 0.69 (0.67 − 0.71); specificity 0.72 (0.71 − 0.73), PPV 0.25 (0.24 − 0.26) and NPV 0.94 (0.94 − 0.95). Conclusion We developed and validated a comprehensive screening questionnaire, COPD-CPHS, with good discrimination. The score system still needs to be validated by large cohort in the future. Supplemental data for this article is available online at https://doi.org/10.1080/15412555.2022.2042504 .

Background: Early diagnosis and treatment are key to improving survival and prognosis of patients with lung cancer. Liquid biopsy and artificial intelligence (AI) can help diagnose early lung cancer. Case presentation: We present a 68-year-old female with a family history of pulmonary nodules without smoking history who found multiple nodules in the lungs on physical examination. Malignant lung nodules were diagnosed based on AI evaluation and 341 circulating abnormal cells (CACs). Surgical resection confirmed the diagnosis of pulmonary adenocarcinoma and the CACs decreased to 151 at postoperative follow-up in one month and to 54 six months after surgery. Conclusion: CACs helps to improve the accuracy of AI diagnosis of early lung cancer and the prognosis of patients with lung cancer at follow-up.

ObjectivesTo evaluate COVID-19 vaccines in primary prevention against infections and lessen the severity of illness following the most recent outbreak of the SARS-CoV-2 Omicron variant in Shanghai.Data sourcesData from 153,544 COVID-19 patients admitted to the Shanghai “Four-Leaf Clover” Fangcang makeshift shelter hospital were collected using a structured electronic questionnaire, which was then merged with electronic medical records of the hospital. For healthy controls, data on vaccination status and other information were obtained from 228 community-based residents, using the same structured electronic questionnaire.MethodsTo investigate whether inactivated vaccines were effective in protecting against SARS-CoV-2 virus, we estimated the odds ratio (OR) of the vaccination by comparing cases and matched community-based healthy controls. To evaluate the potential benefits of vaccination in lowering the risk of symptomatic infection (vs. asymptomatic), we estimated the relative risk (RR) of symptomatic infections among diagnosed patients. We also applied multivariate stepwise logistic regression analyses to measure the risk of disease severity (symptomatic vs. asymptomatic and moderate/severe vs. mild) in the COVID-19 patient cohort with vaccination status as an independent variable while controlling for potential confounding factors.ResultsOf the 153,544 COVID-19 patients included in the analysis, the mean age was 41.59 years and 90,830 were males (59.2%). Of the study cohort, 118,124 patients had been vaccinated (76.9%) and 143,225 were asymptomatic patients (93.3%). Of the 10,319 symptomatic patients, 10,031 (97.2%), 281 (2.7%), and 7 (0.1%) experienced mild, moderate, and severe infections, respectively. Hypertension (8.7%) and diabetes (3.0%) accounted for the majority of comorbidities. There is no evidence that the vaccination helped protect from infections (OR = 0.82, p = 0.613). Vaccination, however, offered a small but significant protection against symptomatic infections (RR = 0.92, p

Background and objective Perioperative treatment has become an increasingly important aspect of the management of patients with non-small cell lung cancer (NSCLC). Small-scale clinical studies performed in recent years have shown improvements in the major pathological remission rate after neoadjuvant therapy, suggesting that it will soon become an important part of NSCLC treatment. Nevertheless, neoadjuvant immunotherapy may be accompanied by serious adverse reactions that lead to delay or cancelation of surgery, additional illness, and even death, and have therefore attracted much attention. The purpose of the clinical recommendations is to form a diagnosis and treatment plan suitable for the current domestic medical situation for the immune-related adverse event (irAE). Methods This recommendation is composed of experts in thoracic surgery, oncologists, thoracic medicine and irAE related departments (gastroenterology, respirology, cardiology, infectious medicine, hematology, endocrinology, rheumatology, neurology, dermatology, emergency section) to jointly complete the formulation. Experts make full reference to the irAE guidelines, large-scale clinical research data published by thoracic surgery, and the clinical experience of domestic doctors and publicly published cases, and repeated discussions in multiple disciplines to form this recommendation for perioperative irAE. Results This clinical recommendation covers the whole process of prevention, evaluation, examination, treatment and monitoring related to irAE, so as to guide the clinical work comprehensively and effectively. Conclusion Perioperative irAE management is an important part of immune perioperative treatment of lung cancer. With the continuous development of immune perioperative treatment, more research is needed in the future to optimize the diagnosis and treatment of perioperative irAE.

HypothesisPatients with cancer have different impedances or conductances than patients with benign normal tissue; thus, we can apply electrical impedance analysis (EIA) to identify patients with cancer.MethodTo evaluate EIA’s efficacy and safety profile in diagnosing pulmonary lesions, we conducted a prospective, multicenter study among patients with pulmonary lesions recruited from 4 clinical centers (Zhongshan Hospital Ethics Committee, Approval No. 2015-16R and 2017-035(3). They underwent EIA to obtain an Algorithm Composite Score or ‘Prolung Index,’ PI. The classification threshold of 29 was first tested in an analytical validation set of 144 patients and independently validated in a clinical validation set of 418 patients. The subject’s final diagnosis depended on histology and a 2-year follow-up.ResultsIn total, 418 patients completed the entire protocol for clinical validation, with 186 true positives, 145 true negatives, 52 false positives, and 35 false negatives. The sensitivity, specificity, and diagnostic yield were 84% (95% CI 79.3%-89.0%), 74% (95% CI 67.4%-79.8%), and 79% (95%CI 75.3%-83.1%), respectively, and did not differ according to age, sex, smoking history, body mass index, or lesion types. The sensitivity of small lesions was comparable to that of large lesions (p = 0.13). Four hundred eighty-four patients who underwent the analysis received a safety evaluation. No adverse events were considered to be related to the test.ConclusionElectrical impedance analysis is a safe and efficient tool for risk stratification of pulmonary lesions, especially for patients with a suspicious lung lesion.

Background Chronic cough is a common complaint, but there are no population-based data on its burden in China. We determined the prevalence of chronic cough and its impact on health status in adults stratified by sex, age and the diagnosis of COPD or the presence of small airway dysfunction (SAD). Methods A representative sample of 57 779 Chinese adults aged 20 years or older was recruited and pulmonary function test was measured. Chronic cough was defined as cough lasting for >3 months in each year. Quality of life was assessed by the 12-item Short Form Health Survey (SF-12), and self-reported history of hospital visits was recorded. Results Chronic cough was found in 3.6% (95% CI 3.1–4.1) of Chinese adults, 2.4% (95% CI 1.9–3.1) of those aged 20–49 years and 6.0% (95% CI 5.3–6.8) of those aged 50 years or older. Individuals with chronic cough had an impaired physical component summary (PCS) score of the SF-12 (p

BackgroundPatients with features of both asthma and chronic obstructive pulmonary disease (COPD) are seen commonly in the clinic but less is known in the general population. We investigated the prevalence and the heterogeneity of COPD with concomitant features of asthma in Chinese adult population.MethodsCOPD was defined as post-bronchodilator ratio of forced expiratory volume in 1s (FEV1) to forced vital capacity of less than the lower limits of normal. COPD with concomitant features of asthma was defined as either COPD with asthma diagnosed by self-reported physician-diagnosis or by presence of current wheeze, or as COPD with high bronchodilator response (HBR) defined as an increase in FEV1 >15% and >400 ml after bronchodilator.ResultsCOPD with concomitant features of asthma was found in 1.62% (95% CI 1.31–2.00) of adults (≥20 years) or in 15.2% (95% CI 13.0–17.7) of COPD patients. Compared with COPD with HBR, COPD with asthma diagnosis or wheeze were older (61.8 ± 1.1 years vs. 47.4 ± 2.8 years, P < 0.001), and with a lower post-bronchodilator FEV1%pred (68.2 ± 2.3 vs. 96.6 ± 3.4, P < 0.001). Age, smoking status, biomass use and allergic rhinitis were associated with increasing prevalence of COPD with asthma diagnosis or wheeze, and had greater impaired health status, more comorbidities and more acute exacerbations in the preceding 12 months.ConclusionsCOPD with concomitant features of asthma is common in people with COPD and those with COPD with asthma diagnosis or wheeze experience worse clinical severity than COPD with HBR. These findings will help toward the definition of the asthma-COPD overlap condition.

Abstract Background The impact of corticosteroid therapy on outcomes of patients with coronavirus disease 2019 (COVID-19) is highly controversial. We aimed to compare the risk of death between COVID-19-related ARDS patients with corticosteroid treatment and those without. Methods In this single-center retrospective observational study, patients with ARDS caused by COVID-19 between January 20, 2020, and February 24, 2020, were enrolled. The primary outcome was 60-day in-hospital death. The exposure was prescribed systemic corticosteroids or not. Time-dependent Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for 60-day in-hospital mortality. Results A total of 382 patients [60.7 ± 14.1 years old (mean ± SD), 61.3% males] were analyzed. The median of sequential organ failure assessment (SOFA) score was 2.0 (IQR 2.0–3.0). Of these cases, 94 (24.6%) patients had invasive mechanical ventilation. The number of patients received systemic corticosteroids was 226 (59.2%), and 156 (40.8%) received standard treatment. The maximum dose of corticosteroids was 80.0 (IQR 40.0–80.0) mg equivalent methylprednisolone per day, and duration of corticosteroid treatment was 7.0 (4.0–12.0) days in total. In Cox regression analysis using corticosteroid treatment as a time-varying variable, corticosteroid treatment was associated with a significant reduction in risk of in-hospital death within 60 days after adjusting for age, sex, SOFA score at hospital admission, propensity score of corticosteroid treatment, comorbidities, antiviral treatment, and respiratory supports (HR 0.42; 95% CI 0.21, 0.85; p = 0.0160). Corticosteroids were not associated with delayed viral RNA clearance in our cohort. Conclusion In this clinical practice setting, low-dose corticosteroid treatment was associated with reduced risk of in-hospital death within 60 days in COVID-19 patients who developed ARDS.

Abstract Background Chromodomain helicase DNA-binding protein 4 (CHD4) has been shown to contribute to DNA repair and cell cycle promotion; however, its roles in cancer initiation and progression remain largely unknown. This study aimed to demonstrate the role of CHD4 in the development of non-small cell lung cancer (NSCLC) and determine the potential mechanisms of action. Methods By using immunohistochemistry, the expression levels were evaluated in both cancer and non-cancerous tissues. Subsequently, CHD4 knockdown and overexpression strategies were employed to investigate the effects of CHD4 on cell proliferation, migration, along with the growth and formation of tumors in a xenografts mouse model. The protein expression levels of CHD4, PHF5A and ROCK/RhoA markers were determined by Western blot analysis. Results Compared with non-cancerous tissues, CHD4 was overexpressed in cancer tissues and CHD4 expression levels were closely related to clinical parameters of NSCLC patients. In H292 and PC-9 cell lines, CHD4 overexpression could promote the proliferative and migratory potential of NSCLC cells. Furthermore, down-regulation of CHD4 could reduce the proliferative and migratory ability in A549 and H1299 cell lines. Meanwhile, knockdown of CHD4 could decrease the tumorigenicity in nude mice. Finally, we demonstrated that one of the mechanisms underlying the promotive effect of CHD4 on NSCLC proliferation and migration may be through its interaction with PHD finger protein 5A (PHF5A) and subsequent activation of the RhoA/ROCK signaling pathway. Conclusions CHD4, which is highly expressed in cancer tissue, could be an independent prognostic factor for NSCLC patients. CHD4 plays an important role in regulating the proliferative and migratory abilities of NSCLC via likely the RhoA/ROCK pathway by regulating PHF5A.

Abstract An ongoing outbreak of 2019-nCoV pneumonia was first identified in Wuhan, Hubei province, China at the end of 2019. With the spread of the new coronavirus accelerating, person-to-person transmission in family homes or hospitals, and intercity spread of 2019-nCoV occurred. At least 40,261 cases confirmed, 23,589 cases suspected, 909 cases death and 3444 cases cured in China and worldwide 24 countries confirmed 383 cases being diagnosed, 1 case death in February 10th, 2020. At present, the mortality of 2019-nCoV in China is 2.3%, compared with 9.6% of SARS and 34.4% of MERS reported by WHO. It seems the new virus is not as fatal as many people thought. Chinese authorities improved surveillance network, made the laboratory be able to recognize the outbreak within a few weeks and announced the virus genome that provide efficient epidemiological control. More comprehensive information is required to understand 2019-nCoV feature, the epidemiology of origin and spreading, and the clinical phenomina. According to the current status, blocking transmission, isolation, protection, and alternative medication are the urgent management strategies against 2019-nCoV.

Lung cancer is the leading cause of cancer-related deaths worldwide and in China. Screening for lung cancer by low dose computed tomography (LDCT) can reduce mortality but has resulted in a dramatic rise in the incidence of indeterminate pulmonary nodules, which presents a major diagnostic challenge for clinicians regarding their underlying pathology and can lead to overdiagnosis. To address the significant gap in evaluating pulmonary nodules, we conducted a prospective study to develop a prediction model for individuals at intermediate to high risk of developing lung cancer. Univariate and multivariate logistic analyses were applied to the training cohort (n = 560) to develop an early lung cancer prediction model. The results indicated that a model integrating clinical characteristics (age and smoking history), radiological characteristics of pulmonary nodules (nodule diameter, nodule count, upper lobe location, malignant sign at the nodule edge, subsolid status), artificial intelligence analysis of LDCT data, and liquid biopsy achieved the best diagnostic performance in the training cohort (sensitivity 89.53%, specificity 81.31%, area under the curve [AUC] = 0.880). In the independent validation cohort (n = 168), this model had an AUC of 0.895, which was greater than that of the Mayo Clinic Model (AUC = 0.772) and Veterans’ Affairs Model (AUC = 0.740). These results were significantly better for predicting the presence of cancer than radiological features and artificial intelligence risk scores alone. Applying this classifier prospectively may lead to improved early lung cancer diagnosis and early treatment for patients with malignant nodules while sparing patients with benign entities from unnecessary and potentially harmful surgery.Clinical Trial Registration NumberChiCTR1900026233, URL: http://www.chictr.org.cn/showproj.aspx?proj=43370.

Abstract Tumour vascularization plays an important role in tumour development and progression. Tumour endothelial cells (TECs) form the inner lining of tumour blood vessels. TECs are mainly derived from endothelial progenitor cells (EPCs); however, it is increasingly evident that in some tumours, TECs are also transformed from cancer stem cells. TECs are different from normal endothelial cells (NECs) in many aspects. On the one hand, the hierarchy of TECs is disorganized, leading to perturbed blood flow, and creating a hypoxic microenvironment in the tumour tissues, which stimulates tumour blood vessels to grow into the tumour tissues. However, the normal endothelial structure is intact, and blood flow is smooth. On the other hand, TECs are more dependent on glycolysis, mitochondrial respiration, and fatty acid metabolism, so there are many potential targets for anti‐angiogenesis therapy. TECs and NECs differ in their gene expressions; biological function experiments have demonstrated that TECs and NECs have different phenotypes. This is essentially caused by gene mutations in TECs. Previous reports mostly described TECs as endothelial cells covering the inner surface of tumour blood vessels. Up to now, there is no clear definition of a group of cells as TECs. Based on this, we summarize the characteristics of TECs as follows. (1) They are derived from EPCs or tumour stem cells. (2) They have up‐regulation of glycolysis, mitochondrial respiration, and fatty acid metabolism. (3) They secrete different cytokines. (4) Some TECs highly express epidermal growth factor receptor and interleukin‐4 receptor. (5) They are distributed around or in tumours and play an important role in the processes of tumour growth, development, and metastasis.

The associations of long-term exposure to various constituents of fine particulate matter (≤2.5 μm in aerodynamic diameter, PM2.5) air pollution with lung function were not clearly elucidated in developing countries. The aim was to evaluate the associations of long-term exposure to main constituents of PM2.5 with lung function in China. This is a nationwide, cross-sectional analysis among 50,991 study participants from the China Pulmonary Health study. Multivariable linear regression models were used to obtain differences of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC, peak expiratory flow (PEF), and forced expiratory flow at 25–75% of exhaled FVC (FEF25-75%) associated with an interquartile range (IQR) change of PM2.5 or its constituents. Residential annual PM2.5 levels varied from 26 μg/m3 to 92 μg/m3 (average: 53 μg/m3). An IQR increase of PM2.5 concentrations was associated with lower FEV1 (19.82 mL, 95% CI: 11.30–28.33), FVC (17.45 mL, 95% CI: 7.16–27.74), PEF (86.64 mL/s, 95% CI: 59.77–113.52), and FEF25-75% (31.93 mL/s, 95% CI: 16.64–47.22). Black carbon, organic matter, ammonium, sulfate, and nitrate were negatively associated with most lung function indicators, with organic matter and nitrate showing consistently larger magnitude of associations than PM2.5 mass. This large-scale study provides first-hand epidemiological evidence that long-term exposure to ambient PM2.5 and some constituents, especially organic matter and nitrate, were associated with lower large- and small- airway function.

The aim is to diagnose COVID-19 earlier and to improve its treatment by applying medical technology, the “COVID-19 Intelligent Diagnosis and Treatment Assistant Program (nCapp)” based on the Internet of Things. Terminal eight functions can be implemented in real-time online communication with the “cloud” through the page selection key. According to existing data, questionnaires, and check results, the diagnosis is automatically generated as confirmed, suspected, or suspicious of 2019 novel coronavirus (2019-nCoV) infection. It classifies patients into mild, moderate, severe or critical pneumonia. nCapp can also establish an online COVID-19 real-time update database, and it updates the model of diagnosis in real time based on the latest real-world case data to improve diagnostic accuracy. Additionally, nCapp can guide treatment. Front-line physicians, experts, and managers are linked to perform consultation and prevention. nCapp also contributes to the long-term follow-up of patients with COVID-19. The ultimate goal is to enable different levels of COVID-19 diagnosis and treatment among different doctors from different hospitals to upgrade to the national and international through the intelligent assistance of the nCapp system. In this way, we can block disease transmission, avoid physician infection, and epidemic prevention and control as soon as possible.

The Internet of Things (IoT) includes three core procedures: full spectrum perception, reliable transmission, and intelligent processing. It can be applied for the prevention and control of SARI (severe acute respiratory infection). By combining sensors, information technology, artificial intelligence, and available dynamic networking devices, IoT could realize long-distance communication between hospitals, patients, and medical devices, which could ultimately improve current medical conditions.

Abstract Background The Nature Step to Respiratory Health was the overarching theme of the 12th General Meeting of the Global Alliance against Chronic Respiratory Diseases (GARD) in Helsinki, August 2018. New approaches are needed to improve respiratory health and reduce premature mortality of chronic diseases by 30% till 2030 (UN Sustainable Development Goals, SDGs). Planetary health is defined as the health of human civilization and the state of the natural systems on which it depends. Planetary health and human health are interconnected, and both need to be considered by individuals and governments while addressing several SDGs. Results The concept of the Nature Step has evolved from innovative research indicating, how changed lifestyle in urban surroundings reduces contact with biodiverse environments, impoverishes microbiota, affects immune regulation and increases risk of NCDs. The Nature Step calls for strengthening connections to nature. Physical activity in natural environments should be promoted, use of fresh vegetables, fruits and water increased, and consumption of sugary drinks, tobacco and alcohol restricted. Nature relatedness should be part of everyday life and especially emphasized in the care of children and the elderly. Taking “nature” to modern cities in a controlled way is possible but a challenge for urban planning, nature conservation, housing, traffic arrangements, energy production, and importantly for supplying and distributing food. Actions against the well-known respiratory risk factors, air pollution and smoking, should be taken simultaneously. Conclusions In Finland and elsewhere in Europe, successful programmes have been implemented to reduce the burden of respiratory disorders and other NCDs. Unhealthy behaviour can be changed by well-coordinated actions involving all stakeholders. The growing public health concern caused by NCDs in urban surroundings cannot be solved by health care alone; a multidisciplinary approach is mandatory.

Abstract Background Drug resistance is common in cancer chemotherapy. This study investigates the role of Glycerol kinase 5 (GK5) in mediating gefitinib resistance in NSCLC. Methods The exosomal mRNA of GK5 was detected using a tethered cationic lipoplex nanoparticle (TCLN) biochip. Real-time PCR and Western blot were used to examine the expression of GK5 mRNA and protein in gefitinib-sensitive and -resistant human lung adenocarcinoma cells. The cell counting kit-8, EdU assay, flow cytometry, and JC-1 dye were used to measure cell proliferation, cell cycle, and the mitochondrial membrane potential. Results We found that the exosomal mRNA of GK5 in the plasma of patients with gefitinib-resistant adenocarcinoma was significantly higher compared with that of gefitinib-sensitive patients. The mRNA and protein levels of GK5 were significantly upregulated in gefitinib-resistant human lung adenocarcinoma PC9R and H1975 cells compared with gefitinib-sensitive PC9 cells. Silencing GK5 in PC9R cells induced mitochondrial damage, caspase activation, cell cycle arrest, and apoptosis via SREBP1/SCD1 signaling pathway. Conclusions We demonstrated that GK5 confers gefitinib resistance in lung cancer by inhibiting apoptosis and cell cycle arrest. GK5 could be a novel therapeutic target for treatment of NSCLC with resistance to EGFR tyrosine kinase inhibitors.

BackgroundLung cancer screening using low-dose computed tomography (LDCT) often leads to unnecessary biopsy because of the low specificity among patients with pulmonary nodules ≤10 mm. Circulating genetically abnormal cells (CACs) can be used to discriminate lung cancer from benign lung disease. To examine the diagnostic value of CACs in detecting lung cancer for patients with malignant pulmonary nodules ≤10 mm.MethodsIn this prospective study, patients with pulmonary nodules ≤10 mm who were detected at four hospitals in China from January 2019 to January 2020 were included. CACs were detected using fluorescence in-situ hybridization. All patients were confirmed as lung cancer or benign disease by further histopathological examination. Multivariable logistic regression models were established to detect the presence of lung cancer using CACs and other associated characteristics. Receiver operating characteristic analysis was used to evaluate the performance of CACs for lung cancer diagnosis.ResultsOverall, 125 patients were included and analyzed. When the cutoff value of CACs was >2, the sensitivity and specificity for lung cancer were 70.5 and 86.4%. Male (OR = 0.330, P = 0.005), maximum solid nodule (OR = 2.362, P = 0.089), maximum nodule located in upper lobe (OR = 3.867, P = 0.001), and CACs >2 (OR = 18.525, P < 0.001) met the P < 0.10 criterion for inclusion in the multivariable models. The multivariable logistic regression model that included the dichotomized CACs (>2 vs. ≤2) and other clinical factors (AUC = 0.907, 95% CI = 0.842–0.951) was superior to the models that only considered dichotomized CACs or other clinical factors and similar to the model with numerical CACs and other clinical factors (AUC = 0.913, 95% CI = 0.850–0.956).ConclusionCACs presented a significant diagnostic value in detecting lung cancer for patients with pulmonary nodules ≤10 mm.

Background Increasing evidence indicates that gut microbiota plays an important role in cancer progression. However, the underlying mechanism remains largely unknown. Here, we report that broad-spectrum antibiotics (ABX) treatment leads to enhanced metastasis by the alteration of gut microbiome composition. Methods Cancer LLC and B16-F10 cell metastasis mouse models, and microarray/RNA sequencing analysis were used to reveal the regulatory functions of microbiota-mediated circular RNA (circRNA)/microRNA (miRNA) networks that may contribute to cancer metastasis. Results The specific pathogen-free (SPF) mice with ABX treatment demonstrated enhanced lung metastasis. Fecal microbiota transplantation (FMT) from SPF mice or Bifidobacterium into germ-free mice significantly suppressed lung metastasis. Mechanistically, gut microbiota impacts circRNA expression to regulate levels of corresponding miRNAs. Specifically, such modulations of gut microbiota inhibit mmu_circ_0000730 expression in an IL-11-dependent manner. Bioinformatics analysis combined with luciferase reporter assays revealed reciprocal repression between mmu_circ_0000730 and mmu-miR-466i-3p. We further showed that both mmu-miR-466i-3p and mmu-miR-466 f-3p suppresses a number of genes involved in epithelial-mesenchymal transition (EMT) and stemness of cancer stem cells such as SOX9. Conclusions These results provide evidence of a previously unrecognized regulatory role of non-coding RNAs in microbiota-mediated cancer metastasis, and thus, the microbiome may serve as a therapeutic target.

Background Coronavirus disease 2019 (COVID-19) is a disease caused by severe acute respiratory syndrome-coronavirus-2. Consensus suggestions can standardise care, thereby improving outcomes and facilitating future research. Methods An International Task Force was composed and agreement regarding courses of action was measured using the Convergence of Opinion on Recommendations and Evidence (CORE) process. 70% agreement was necessary to make a consensus suggestion. Results The Task Force made consensus suggestions to treat patients with acute COVID-19 pneumonia with remdesivir and dexamethasone but suggested against hydroxychloroquine except in the context of a clinical trial; these are revisions of prior suggestions resulting from the interim publication of several randomised trials. It also suggested that COVID-19 patients with a venous thromboembolic event be treated with therapeutic anticoagulant therapy for 3 months. The Task Force was unable to reach sufficient agreement to yield consensus suggestions for the post-hospital care of COVID-19 survivors. The Task Force fell one vote shy of suggesting routine screening for depression, anxiety and post-traumatic stress disorder. Conclusions The Task Force addressed questions related to pharmacotherapy in patients with COVID-19 and the post-hospital care of survivors, yielding several consensus suggestions. Management options for which there is insufficient agreement to formulate a suggestion represent research priorities.