ABSTRACT
Airway segmentation is crucial for the examination, diagnosis, and prognosis of lung diseases, while its manual delineation is unduly burdensome. To alleviate this time-consuming and potentially subjective manual procedure, researchers have proposed methods to automatically segment airways from computerized tomography (CT) images. However, some small-sized airway branches (e.g., bronchus and terminal bronchioles) significantly aggravate the difficulty of automatic segmentation by machine learning models. In particular, the variance of voxel values and the severe data imbalance in airway branches make the computational module prone to discontinuous and false-negative predictions, especially for cohorts with different lung diseases. The attention mechanism has shown the capacity to segment complex structures, while fuzzy logic can reduce the uncertainty in feature representations. Therefore, the integration of deep attention networks and fuzzy theory, given by the fuzzy attention layer, should be an escalated solution for better generalization and robustness. This article presents an efficient method for airway segmentation, comprising a novel fuzzy attention neural network (FANN) and a comprehensive loss function to enhance the spatial continuity of airway segmentation. The deep fuzzy set is formulated by a set of voxels in the feature map and a learnable Gaussian membership function. Different from the existing attention mechanism, the proposed channel-specific fuzzy attention addresses the issue of heterogeneous features in different channels. Furthermore, a novel evaluation metric is proposed to assess both the continuity and completeness of airway structures. The efficiency, generalization, and robustness of the proposed method have been proved by training on normal lung disease while testing on datasets of lung cancer, COVID-19, and pulmonary fibrosis.
ABSTRACT
Discontinuity in the delineation of peripheral bronchioles hinders the potential clinical application of automated airway segmentation models. Moreover, the deployment of such models is limited by the data heterogeneity across different centres, and pathological abnormalities also make achieving accurate robust segmentation in distal small airways difficult. Meanwhile, the diagnosis and prognosis of lung diseases often rely on evaluating structural changes in those anatomical regions. To address this gap, this paper presents a patch-scale adversarial-based refinement network that takes in preliminary segmentation along with original CT images and outputs a refined mask of the airway structure. The method is validated on three different datasets encompassing healthy cases, cases with cystic fibrosis and cases with COVID-19. The results are quantitatively evaluated by seven metrics and achieved more than a 15% rise in detected length ratio and detected branch ratio, showing promising performance compared to previously proposed models. The visual illustration also proves our refinement guided by a patch-scale discriminator and centreline objective functions is effective in detecting discontinuities and missing bronchioles. Furthermore, the generalizability of our refinement pipeline is tested on three previous models and improves their segmentation completeness significantly.
Subject(s)
COVID-19 , Cystic Fibrosis , Fractures, Spontaneous , Lung DiseasesABSTRACT
Objective: To investigate the prevalence of anxiety and depression in graduating university students during the COVID-19 pandemic and determine the associated factors. Methods: A total of 681 graduating university students and 620 juniors enrolled in the first stage. The Self-rating Anxiety Scale (SAS) and Self-rating Depression Scale (SDS) were used to measure anxiety and depression. In the second stage, 578 of the 681 graduating students completed the SAS and SDS questionnaires after graduation. Results: The average SAS score of the graduating university students was significantly higher than that of the juniors (47.66±12.86 vs. 43.97±10.42, P<0.001). Depression was more prevalent among the graduating university students than in the control groups (39.06% vs. 9.19%, P<0.01). The percentages of anxiety and depression significantly decreased after graduation (t=8.602, P<0.001). The anxiety of graduating university students was associated with gender (OR=1.62, 95% CI: 1.10-2.37), monthly family income (OR=0.05, 95% CI: 0.02-0.11), and weekly exercise time (OR=0.53, 95% CI: 0.35-0.08). Their depression was related to their family’s monthly income (OR=0.09, 95% CI: 0.05-0.16) and father’s educational status (OR=2.24, 95% CI: 1.17-4.30). Conclusion: Anxiety and depression were rife within the graduating Chinese university students during the period of the COVID-19 pandemic and were both associated with monthly family income. Treatments tailored to specific targets are needed for graduating university students with mental problems.
ABSTRACT
Background: Open online forums like Reddit provide an opportunity to quantitatively examine COVID-19 vaccine perceptions early in the vaccine timeline. We examine COVID-19 misinformation on Reddit following vaccine scientific announcements, in the initial phases of the vaccine timeline. Methods: We collected all posts on Reddit from January 1 2020 - December 14 2020 (n=266,840) that contained both COVID-19 and vaccine-related keywords. We used topic modeling to understand changes in word prevalence within topics after the release of vaccine trial data. Social network analysis was also conducted to determine the relationship between Reddit communities (subreddits) that shared COVID-19 vaccine posts, and the movement of posts between subreddits. Results: There was an association between a Pfizer press release reporting 90\% efficacy and increased discussion on vaccine misinformation. We observed an association between Johnson and Johnson temporarily halting its vaccine trials and reduced misinformation. We found that information skeptical of vaccination was first posted in a subreddit (r/Coronavirus) which favored accurate information and then reposted in subreddits associated with antivaccine beliefs and conspiracy theories (e.g. conspiracy, NoNewNormal). Conclusions: Our findings can inform the development of interventions where individuals determine the accuracy of vaccine information, and communications campaigns to improve COVID-19 vaccine perceptions, early in the vaccine timeline. Such efforts can increase individual- and population-level awareness of accurate and scientifically sound information regarding vaccines and thereby improve attitudes about vaccines, especially in the early phases of vaccine roll-out. Further research is needed to understand how social media can contribute to COVID-19 vaccination services.
Subject(s)
COVID-19ABSTRACT
Objectives: As COVID-19 vaccinations accelerate in many countries, narratives skeptical of vaccination have also spread through social media. Open online forums like Reddit provide an opportunity to quantitatively examine COVID-19 vaccine perceptions over time. We examine COVID-19 misinformation on Reddit following vaccine scientific announcements. Methods: We collected all posts on Reddit from January 1 2020 - December 14 2020 (n=266,840) that contained both COVID-19 and vaccine-related keywords. We used topic modeling to understand changes in word prevalence within topics after the release of vaccine trial data. Social network analysis was also conducted to determine the relationship between Reddit communities (subreddits) that shared COVID-19 vaccine posts, and the movement of posts between subreddits. Results: There was an association between a Pfizer press release reporting 90% efficacy and increased discussion on vaccine misinformation. We observed an association between Johnson and Johnson temporarily halting its vaccine trials and reduced misinformation. We found that information skeptical of vaccination was first posted in a subreddit (r/Coronavirus) which favored accurate information and then reposted in subreddits associated with antivaccine beliefs and conspiracy theories (e.g. conspiracy, LockdownSkepticism). Conclusions: Our findings can inform the development of interventions where individuals determine the accuracy of vaccine information, and communications campaigns to improve COVID-19 vaccine perceptions. Such efforts can increase individual- and population-level awareness of accurate and scientifically sound information regarding vaccines and thereby improve attitudes about vaccines. Further research is needed to understand how social media can contribute to COVID-19 vaccination services.
Subject(s)
COVID-19ABSTRACT
BACKGROUND The top priority for the control of COVID-19 pandemic currently is the development of a vaccine. A phase 2 trial conducted to further evaluate the immunogenicity and safety of a SARS-CoV-2 inactivated vaccine (CoronaVac). METHODS We conducted a randomized, double-blind, placebo-controlled trial to evaluate the optimal dose, immunogenicity and safety of the CoronaVac. A total of 600 healthy adults aged 18-59 years were randomly assigned to receive 2 injections of the trial vaccine at a dose of 3 g/0.5 mL or 6 g /0.5mL, or placebo on Day 0,14 schedule or Day 0,28 schedule. For safety evaluation, solicited and unsolicited adverse events were collected after each vaccination within 7 days and 28 days, respectively. Blood samples were taken for antibody assay. RESULTS CoronaVac was well tolerated, and no dose-related safety concerns were observed. Most of the adverse reactions fell in the solicited category and were mild in severity. Pain at injection site was the most frequently reported symptoms. No Grade 3 adverse reaction or vaccine related SAEs were reported. CoronaVac showed good immunogenicity with the lower 3 g dose eliciting 92.4% seroconversion under Day 0,14 schedule and 97.4% under Day 0,28 schedule. 28 days after two-dose vaccination, the Nab levels of individual schedules range from 23.8 to 65.4 among different dosage and vaccination schedules. CONCLUSIONS Favorable safety and immunogenicity of CoronaVac was demonstrated on both schedules and both dosages, which support the conduction of phase 3 trial with optimum schedule/dosage per different scenarios.
Subject(s)
COVID-19 , PainABSTRACT
Objectives : A pneumonia associated with 2019 novel coronavirus (2019-nCoV, subsequently named SARS-CoV2) emerged worldwide since December, 2019. We aimed to describe the epidemiological characteristics of 2019 coronavirus disease (COVID-19) in Shaanxi province of China. Results: 1. Among the 245 patients, 132 (53.9%) were males and 113 (46.1%) were females. The average age was 46.15±16.43 years, ranging from 3 to 89 years. 2. For the clinical type, 1.63% (4/245) patients were mild type , 84.90% (208/245) were moderate type, 7.76% (19/245) were severe type, 5.31% (13/245) were critical type and only 0.41% (1/245) was asymptomatic. 3. Of the 245 patients, 116 (47.35%) were input case, 114 (46.53%) were non-input case , and 15 (6.12%) were unknown exposure. 4. 48.57% (119/245) cases were family cluster , involving 42 families. The most common pattern of COVID-19 family cluster was between husband and wife or between parents and children.
Subject(s)
Coronavirus Infections , Pneumonia , COVID-19ABSTRACT
Background: Intravenous immunoglobulin (IVIG) is usually used as supportive therapy, but the treatment of COVID-19 by IVIG is controversial. This rapid review aims to explore the clinical effectiveness and safety of IVIG in the treatment of children with severe COVID-19. Methods: We systematically searched the literature on the use of IVIG in patients with COVID-19, Severe Acute Respiratory Syndrome (SARS) or Middle East Respiratory Syndrome (MERS), including both adults and children. We assessed the risk of bias and quality of evidence and reported the main findings descriptively. Results: A total of 1519 articles were identified by initial literature search, and finally six studies, included one randomized controlled trial (RCT), four case series and one case report involving 198 patients. One case series showed the survival of COVID-19 patients with acute respiratory distress syndrome (ARDS) was not improved by IVIG. One case report showed high-dose IVIG could improve the outcome of COVID-19 adults. Three observational studies showed inconsistent results of the effect of IVIG on SARS patients. One RCT showed that IVIG did not reduce mortality or the incidence of nosocomial infection in adults with severe SARS. The quality of evidence was between low and very low. Conclusions: The existing evidence is insufficient to support the efficacy or safety of IVIG in the treatment of COVID-19. Keywords: COVID-19; children; intravenous immunoglobulin; rapid review.
Subject(s)
Coronavirus Infections , Respiratory Distress Syndrome , Severe Acute Respiratory Syndrome , Cross Infection , COVID-19ABSTRACT
Abstract Background: Existing recommendations on whether mothers with COVID-19 should continue breastfeeding are still conflicting. We aimed to conduct a rapid review of mother-to-child transmission of COVID-19 during breastfeeding. Methods: We systematically searched Medline, Embase, Web of Science, Cochrane library, China Biology Medicine disc, China National Knowledge Infrastructure, Wanfang, and preprint articles up to March 2020. We included studies relevant to transmission through milk and respiratory droplets during breastfeeding of mothers with COVID-19, SARS, MERS and influenza. Two reviewers independently screened studies for eligibility, extracted data, assessed risk of bias and used GRADE to assess certainty of evidence. Results: A total of 4481 records were identified in our literature search. Six studies (five case reports and one case series) involving 58 mothers (16 mothers with COVID-19, 42 mothers with influenza) and their infants proved eligible. Five case reports showed that the viral nucleic acid tests for all thirteen collected samples of breast milk from mothers with COVID-19 were negative. A case series of 42 influenza infected postpartum mothers taking precautions (hand hygiene and wearing masks) before breastfeeding showed that no neonates were infected with influenza during one-month of follow-up. Conclusions: The current evidence indicates that SARS-CoV-2 viral nucleic acid has not been detected in breast milk. The benefits of breastfeeding may outweigh the risk of SARS-CoV-2 infection in infants. Mothers with COVID-19 should take appropriate precautions to reduce the risk of transmission via droplets and close contact during breastfeeding. Keywords: Breastfeeding; COVID-19; infant; mother-to-child transmission; rapid Review.
Subject(s)
COVID-19 , Coronavirus Infections , Breast NeoplasmsABSTRACT
Background: The outbreak of the coronavirus disease 2019 (COVID-19) has had a massive impact on the whole world. Computed tomography (CT) has been widely used in the diagnosis of this novel pneumonia. This study aims to understand the role of CT for the diagnosis and the main imaging manifestations of patients with COVID-19. Methods: We conducted a rapid review and meta-analysis on studies about the use of chest CT for the diagnosis of COVID-19. We comprehensively searched databases and preprint servers on chest CT for patients with COVID-19 between 1 January 2020 and 31 March 2020. The primary outcome was the sensitivity of chest CT imaging. We also conducted subgroup analyses and evaluated the quality of evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Results: A total of 104 studies with 5694 patients were included. Using RT-PCR results as reference, a meta-analysis based on 64 studies estimated the sensitivity of chest CT imaging in COVID-19 was 99% (95% CI, 0.97-1.00). If case reports were excluded, the sensitivity in case series was 96% (95% CI, 0.93-0.99). The sensitivity of CT scan in confirmed patients under 18 years old was only 66% (95% CI, 0.11-1.00). The most common imaging manifestation was ground-glass opacities (GGO) which was found in 75% (95% CI, 0.68-0.82) of the patients. The pooled probability of bilateral involvement was 84% (95% CI, 0.81-0.88). The most commonly involved lobes were the right lower lobe (84%, 95% CI, 0.78-0.90) and left lower lobe (81%, 95% CI, 0.74-0.87). The quality of evidence was low across all outcomes. Conclusions: In conclusion, this meta-analysis indicated that chest CT scan had a high sensitivity in diagnosis of patients with COVID-19. Therefore, CT can potentially be used to assist in the diagnosis of COVID-19.