Network rule extraction under the network formal context based on three-way decision.

Knowledge discovery combined with network structure is an emerging field of network data analysis and mining. Three-way concept analysis is a method that can fit the human mind in uncertain decisions and analysis. In reality, when three-way concept analysis is placed in the background of a network, not only the three-way rules need to be obtained, but also the network characteristic values of these rules should be obtained, which is of great significance for concept cognition in the network. This paper mainly combines complex network analysis with the formal context of three-way decision. Firstly, the network formal context of three-way decision (NFC3WD) is proposed to unify the two studies mentioned above into one data framework. Then, the network weaken-concepts of three-way decision (NWC3WD) and their corresponding sub-networks are studied. Therefore, we can not only find out the network weaken-concepts but also know the average influence of the sub-network, as well as the influence difference within the sub-network. Furthermore, the concept logic of network and the properties of its operators are put forward, which lays a foundation for designing the algorithm of rule extraction. Subsequently, the bidirectional rule extraction algorithm and reduction algorithm based on confidence degree are also explored. Meanwhile, these algorithms are applied to the diagnosis examples of COVID-19 from which we can not only get diagnostic rules, but also know the importance of the population corresponding to these diagnostic rules in the network through network eigenvalues. Finally, experimental analysis is made to show the superiority of the proposed method.

Does ACE2 mediate the detrimental effect of exposures related to COVID-19 risk: A Mendelian randomization investigation.

OBJECTIVES: Adiposity, smoking, and lower socioeconomic position (SEP) increase COVID-19 risk while the association of vitamin D, blood pressure, and glycemic traits in COVID-19 risk were less clear. Whether angiotensin-converting enzyme 2 (ACE2), the key receptor for SARS-CoV-2, mediates these associations has not been investigated. We conducted a Mendelian randomization study to assess the role of these exposures in COVID-19 and mediation by ACE2. METHODS: We extracted genetic variants strongly related to various exposures (vitamin D, blood pressure, glycemic traits, smoking, adiposity, and educational attainment [SEP proxy]), and ACE2 cis-variants from genome-wide association studies (GWAS, n ranged from 28 204 to 3 037 499) and applied them to GWAS summary statistics of ACE2 (n = 28 204) and COVID-19 (severe, hospitalized, and susceptibility, n ≤ 2 942 817). We used inverse variance weighted as the main analyses, with MR-Egger and weighted median as sensitivity analyses. Mediation analyses were performed based on product of coefficient method. RESULTS: Higher adiposity, lifetime smoking index, and lower educational attainment were consistently associated with higher risk of COVID-19 phenotypes while there was no strong evidence for an association of other exposures in COVID-19 risk. ACE2 partially mediates the detrimental effects of body mass index (ranged from 4.3% to 8.2%), waist-to-hip ratio (ranged from 11.2% to 16.8%), and lower educational attainment (ranged from 4.0% to 7.5%) in COVID-19 phenotypes while ACE2 did not mediate the detrimental effect of smoking. CONCLUSIONS: We provided genetic evidence that reducing ACE2 could partly lower COVID-19 risk amongst people who were overweight/obese or of lower SEP.

Network rule extraction under the network formal context based on three-way decision

Knowledge discovery combined with network structure is an emerging field of network data analysis and mining. Three-way concept analysis is a method that can fit the human mind in uncertain decisions and analysis. In reality, when three-way concept analysis is placed in the background of a network, not only the three-way rules need to be obtained, but also the network characteristic values of these rules should be obtained, which is of great significance for concept cognition in the network. This paper mainly combines complex network analysis with the formal context of three-way decision. Firstly, the network formal context of three-way decision (NFC3WD) is proposed to unify the two studies mentioned above into one data framework. Then, the network weaken-concepts of three-way decision (NWC3WD) and their corresponding sub-networks are studied. Therefore, we can not only find out the network weaken-concepts but also know the average influence of the sub-network, as well as the influence difference within the sub-network. Furthermore, the concept logic of network and the properties of its operators are put forward, which lays a foundation for designing the algorithm of rule extraction. Subsequently, the bidirectional rule extraction algorithm and reduction algorithm based on confidence degree are also explored. Meanwhile, these algorithms are applied to the diagnosis examples of COVID-19 from which we can not only get diagnostic rules, but also know the importance of the population corresponding to these diagnostic rules in the network through network eigenvalues. Finally, experimental analysis is made to show the superiority of the proposed method.

Identifying factors contributing to increased susceptibility to COVID-19 risk: a systematic review of Mendelian randomization studies.

BACKGROUND: To summarize modifiable factors for coronavirus disease 2019 (COVID-19) suggested by Mendelian randomization studies. METHODS: In this systematic review, we searched PubMed, EMBASE and MEDLINE, from inception to 15 November 2021, for Mendelian randomization studies in English. We selected studies that assessed associations of genetically predicted exposures with COVID-19-related outcomes (severity, hospitalization and susceptibility). Risk of bias of the included studies was evaluated based on the consideration of the three main assumptions for instrumental variable analyses. RESULTS: We identified 700 studies through systematic search, of which 50 Mendelian randomization studies were included. Included studies have explored a wide range of socio-demographic factors, lifestyle attributes, anthropometrics and biomarkers, predisposition to diseases and druggable targets in COVID-19 risk. Mendelian randomization studies suggested that increases in smoking, obesity and inflammatory factors were associated with higher risk of COVID-19. Predisposition to ischaemic stroke, combined bipolar disorder and schizophrenia, attention-deficit and hyperactivity disorder, chronic kidney disease and idiopathic pulmonary fibrosis was potentially associated with higher COVID-19 risk. Druggable targets, such as higher protein expression of histo-blood group ABO system transferase (ABO), interleukin (IL)-6 and lower protein expression of 2'-5' oligoadenylate synthetase 1 (OAS1) were associated with higher risk of COVID-19. There was no strong genetic evidence supporting the role of vitamin D, glycaemic traits and predisposition to cardiometabolic diseases in COVID-19 risk. CONCLUSION: This review summarizes modifiable factors for intervention (e.g. smoking, obesity and inflammatory factors) and proteomic signatures (e.g. OAS1 and IL-6) that could help identify drugs for treating COVID-19.

Early Fever Is Associated With Clinical Outcomes in Patients With Coronavirus Disease.

Fever is one of the typical symptoms of coronavirus disease (COVID-19). We aimed to investigate the association between early fever (EF) and clinical outcomes in COVID-19 patients. A total of 1,014 COVID-19 patients at the Leishenshan Hospital were enrolled and classified into the EF and non-EF groups based on whether they had fever within 5 days of symptom onset. Risk factors for clinical outcomes in patients with different levels of disease severity were analyzed using multivariable analyses. Time from symptom onset to symptom alleviation, CT image improvement, and discharge were longer for patients with moderate and severe disease in the EF group than in the non-EF group. Multivariable analysis showed that sex, EF, eosinophil number, C-reactive protein, and IL-6 levels were positively correlated with the time from symptom onset to hospital discharge in moderate cases. The EF patients showed no significant differences in the development of acute respiratory distress syndrome, compared with the non-EF patients. The Kaplan-Meier curve showed no obvious differences in survival between the EF and non-EF patients. However, EF patients with increased temperature showed markedly lower survival than the non-EF patients with increased temperature. EF had no significant impact on the survival of critically ill patients, while an increase in temperature was identified as an independent risk factor. EF appears to be a predictor of longer recovery time in moderate/severe COVID-19 infections. However, its value in predicting mortality needs to be considered for critically ill patients with EF showing increasing temperature.

Clinical features in coronavirus disease 2019 (COVID-19) patients with early clearance and prolonged shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA.

BACKGROUND: Since the outbreak of coronavirus disease 2019 (COVID-19), the pattern of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA shedding has not been well characterized. METHODS: In our study, 652 patients in Wuhan Designated Hospital were recruited, and their clinical and laboratory findings were extracted and analyzed. RESULTS: The median duration of SARS-CoV-2 RNA detection was 23 days [interquartile range (IQR), 18 days] from symptom onset. Compared to patients with early viral RNA clearance (<23 days after illness onset), we found that patients with late viral RNA clearance (≥23 days) had a higher proportion of clinical features, as follows: symptoms, including fever, dry cough, and sputum production; comorbidities, including hypertension, chronic kidney disease, uremia, chronic liver disease, anemia, hyperlipidemia, and bilateral lung involvement; complications, such as liver injury; delayed admission to hospital; laboratory parameters at baseline, including higher eosinophils, uric acid, cholesterol, triglycerides, and lower hemoglobin; and less treatment with arbidol, chloroquine, or any antivirals. After generalized linear regression, prolonged SARS-CoV-2 RNA shedding was independently associated with younger age; delayed admission to hospital; symptoms including fever, shivering, and sputum production; comorbidities including hypertension, diabetes, cardiovascular disease, anemia, hyperlipidemia, uremia, and lung involvement; and higher alanine aminotransferase (ALT), uric acid, and cholesterol levels at baseline. CONCLUSIONS: In conclusion, the factors mentioned above are associated with the negative conversion of SARS-CoV-2 RNA. A deeper insight into virological dynamics will be helpful for establishing patient discharge and quarantine release criteria.

Wearing a N95 mask increases rescuer's fatigue and decreases chest compression quality in simulated cardiopulmonary resuscitation.

OBJECTIVES: N95 mask is essential for healthcare workers dealing with the coronavirus disease 2019 (COVID-19). However, N95 mask causes discomfort breathing with marked reduction in air exchange. This study was designed to investigate whether the use of N95 mask affects rescuer's fatigue and chest compression quality during cardiopulmonary resuscitation (CPR). METHODS: After a brief review of CPR, each participant performed a 2-minute continuous chest compression on a manikin wearing N95 (N95 group, n = 40) or surgical mask (SM group, n = 40). Compression rate and depth, the proportions of correct compression rate, depth, complete chest recoil and hand position were documented. Participants' fatigue was assessed using Borg score. RESULTS: Significantly lower mean chest compression rate and depth were both achieved in the N95 group than in the SM group (p < 0.05, respectively). In addition, the proportion of correct compression rate (61 ± 19 vs. 75 ± 195, p = 0.0067), depth (67 ± 16 vs. 90 ± 14, p < 0.0001) and complete recoil (91 ± 16 vs. 98 ± 5%, p = 0.0248) were significantly decreased in the N95 group as compared to the SM group. At the end of compression, the Borg score in the N95 group was significantly higher than that in the SM group (p = 0.027). CONCLUSION: Wearing a N95 mask increases rescuer's fatigue and decreases chest compression quality during CPR. Therefore, the exchange of rescuers during CPR should be more frequent than that recommended in current guidelines when N95 masks are applied.