Improving the Accuracy of Diabetes Diagnosis Applications through a Hybrid Feature Selection Algorithm.

Artificial intelligence is a future and valuable tool for early disease recognition and support in patient condition monitoring. It can increase the reliability of the cure and decision making by developing useful systems and algorithms. Healthcare workers, especially nurses and physicians, are overworked due to a massive and unexpected increase in the number of patients during the coronavirus pandemic. In such situations, artificial intelligence techniques could be used to diagnose a patient with life-threatening illnesses. In particular, diseases that increase the risk of hospitalization and death in coronavirus patients, such as high blood pressure, heart disease and diabetes, should be diagnosed at an early stage. This article focuses on diagnosing a diabetic patient through data mining techniques. If we are able to diagnose diabetes in the early stages of the disease, we can force patients to stay home and care for their health, so the risk of being infected with the coronavirus would be reduced. The proposed method has three steps: preprocessing, feature selection and classification. Several combinations of Harmony search algorithm, genetic algorithm, and particle swarm optimization algorithm are examined with K-means for feature selection. The combinations have not examined before for diabetes diagnosis applications. K-nearest neighbor is used for classification of the diabetes dataset. Sensitivity, specificity, and accuracy have been measured to evaluate the results. The results achieved indicate that the proposed method with an accuracy of 91.65% outperformed the results of the earlier methods examined in this article.

Association Between Ischemic Stroke and COVID-19 in China: A Population-Based Retrospective Study.

Background and Purpose: To investigate the effect of prior ischemic stroke on the outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19), and to describe the incidence, clinical features, and risk factors of acute ischemic stroke (AIS) following COVID-19. Methods: In this population-based retrospective study, we included all the hospitalized positive patients with COVID-19 at Wuhan City from December 29, 2019 to April 15, 2020. Clinical data were extracted from administrative datasets coordinated by the Wuhan Health Commission. The propensity score matching and multivariate logistic regression analyses were used to adjust the confounding factors. Results: There are 36,358 patients in the final cohort, in which 1,160 (3.2%) had a prior stroke. After adjusting for available baseline characteristics, patients with prior stroke had a higher proportion of severe and critical illness and mortality. We found for the first time that the premorbid modified Rankin Scale (MRS) grouping (odds ratio [OR] = 1.796 [95% CI 1.334-2.435], p < 0.001) and older age (OR = 1.905 [95% CI 1.211-3.046], p = 0.006) imparted increased risk of death. AIS following COVID-19 occurred in 124 (0.34%) cases, and patients with prior stroke had a much higher incidence of AIS (3.4%). Logistic regression analyses confirmed an association between the severity of COVID-19 with the incidence of AIS. COVID-19 patients with AIS had a significantly higher mortality compared with COVID-19 patients without stroke and AIS patients without COVID-19. Conclusions: Coronavirus disease 2019 patients with prior stroke, especially those with the higher premorbid MRS or aged, have worse clinical outcomes. Furthermore, COVID-19 increases the incidence of AIS, and the incidence is positively associated with the severity of COVID-19.

Association Between Ischemic Stroke and COVID-19 in China: A Population-Based Retrospective Study

Background and Purpose To investigate the effect of prior ischemic stroke on the outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19), and to describe the incidence, clinical features, and risk factors of acute ischemic stroke (AIS) following COVID-19. Methods In this population-based retrospective study, we included all the hospitalized positive patients with COVID-19 at Wuhan City from December 29, 2019 to April 15, 2020. Clinical data were extracted from administrative datasets coordinated by the Wuhan Health Commission. The propensity score matching and multivariate logistic regression analyses were used to adjust the confounding factors. Results There are 36,358 patients in the final cohort, in which 1,160 (3.2%) had a prior stroke. After adjusting for available baseline characteristics, patients with prior stroke had a higher proportion of severe and critical illness and mortality. We found for the first time that the premorbid modified Rankin Scale (MRS) grouping (odds ratio [OR] = 1.796 [95% CI 1.334–2.435], p < 0.001) and older age (OR = 1.905 [95% CI 1.211–3.046], p = 0.006) imparted increased risk of death. AIS following COVID-19 occurred in 124 (0.34%) cases, and patients with prior stroke had a much higher incidence of AIS (3.4%). Logistic regression analyses confirmed an association between the severity of COVID-19 with the incidence of AIS. COVID-19 patients with AIS had a significantly higher mortality compared with COVID-19 patients without stroke and AIS patients without COVID-19. Conclusions Coronavirus disease 2019 patients with prior stroke, especially those with the higher premorbid MRS or aged, have worse clinical outcomes. Furthermore, COVID-19 increases the incidence of AIS, and the incidence is positively associated with the severity of COVID-19.

Age-Related Risk Factors and Complications of Patients With COVID-19: A Population-Based Retrospective Study

Objective: To study the differences in clinical characteristics, risk factors, and complications across age-groups among the inpatients with the coronavirus disease 2019 (COVID-19). Methods: In this population-based retrospective study, we included all the positive hospitalized patients with COVID-19 at Wuhan City from December 29, 2019 to April 15, 2020, during the first pandemic wave. Multivariate logistic regression analyses were used to explore the risk factors for death from COVID-19. Canonical correlation analysis (CCA) was performed to study the associations between comorbidities and complications. Results: There are 36,358 patients in the final cohort, of whom 2,492 (6.85%) died. Greater age (odds ration [OR] = 1.061 [95% CI 1.057–1.065], p < 0.001), male gender (OR = 1.726 [95% CI 1.582–1.885], p < 0.001), alcohol consumption (OR = 1.558 [95% CI 1.355–1.786], p < 0.001), smoking (OR = 1.326 [95% CI 1.055–1.652], p = 0.014), hypertension (OR = 1.175 [95% CI 1.067–1.293], p = 0.001), diabetes (OR = 1.258 [95% CI 1.118–1.413], p < 0.001), cancer (OR = 1.86 [95% CI 1.507–2.279], p < 0.001), chronic kidney disease (CKD) (OR = 1.745 [95% CI 1.427–2.12], p < 0.001), and intracerebral hemorrhage (ICH) (OR = 1.96 [95% CI 1.323–2.846], p = 0.001) were independent risk factors for death from COVID-19. Patients aged 40–80 years make up the majority of the whole patients, and them had similar risk factors with the whole patients. For patients aged <40 years, only cancer (OR = 17.112 [95% CI 6.264–39.73], p < 0.001) and ICH (OR = 31.538 [95% CI 5.213–158.787], p < 0.001) were significantly associated with higher odds of death. For patients aged >80 years, only age (OR = 1.033 [95% CI 1.008–1.059], p = 0.01) and male gender (OR = 1.585 [95% CI 1.301–1.933], p < 0.001) were associated with higher odds of death. The incidence of most complications increases with age, but arrhythmias, gastrointestinal bleeding, and sepsis were more common in younger deceased patients with COVID-19, with only arrhythmia reaching statistical difference (p = 0.039). We found a relatively poor correlation between preexisting risk factors and complications. Conclusions: Coronavirus disease 2019 are disproportionally affected by age for its clinical manifestations, risk factors, complications, and outcomes. Prior complications have little effect on the incidence of extrapulmonary complications.

Modeling for COVID-19 with the contacting distance.

COVID-19 is a public health emergency for human beings and brings some very harmful consequences in social and economic fields. In order to model COVID-19 and develop the effective control measures, this paper proposes an SEIR-type epidemic model with the contacting distance between the healthy individuals and the asymptomatic or symptomatic infected individuals, and the immigration rate of the healthy individuals since the contacting distance and the immigration rate are two critical factors which determine the transmission of COVID-19. Firstly, the threshold values of the contacting distance and the immigration rate are obtained to analyze the presented model. Secondly, based on the data from January 10, 2020, to March 18, 2020, for Wuhan city, all parameters are estimated. Finally, based on the estimated parameters, the sensitivity analysis and the numerical study are conducted. The results show that the contacting distance and the immigration rate play an important role in controlling COVID-19. Meanwhile, the extinct lag decreases as the contacting distance increases and/or the immigration rate decreases. Our study could give some reasonable suggestions for the health officials and the public and provide a theoretical issue for globally controlling the COVID-19 pandemic.

Comparison of Clinical Features and Outcomes of Medically Attended COVID-19 and Influenza Patients in a Defined Population in the 2020 Respiratory Virus Season.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2), which is causing the coronavirus disease-2019 (COVID-19) pandemic, poses a global health threat. However, it is easy to confuse COVID-19 with seasonal influenza in preliminary clinical diagnosis. In this study, the differences between influenza and COVID-19 in epidemiological features, clinical manifestations, comorbidities and pathogen biology were comprehensively compared and analyzed. SARS-CoV-2 causes a higher proportion of pneumonia (90.67 vs. 17.07%) and acute respiratory distress syndrome (12.00 vs. 0%) than influenza A virus. The proportion of leukopenia for influenza patients was 31.71% compared with 12.00% for COVID-19 patients (P = 0.0096). The creatinine and creatine kinase were significantly elevated when there were COVID-19 patients. The basic reproductive number (R0) for SARS-CoV-2 is 2.38 compared with 1.28 for seasonal influenza A virus. The mutation rate of SARS-CoV-2 ranges from 1.12 × 10-3 to 6.25 × 10-3, while seasonal influenza virus has a lower evolutionary rate (0.60-2.00 × 10-6). Overall, this study compared the clinical features and outcomes of medically attended COVID-19 and influenza patients. In addition, the S477N and N439K mutations on spike may affect the affinity with receptor ACE2. This study will contribute to COVID-19 control and epidemic surveillance in the future.

Clinical characteristics of 41 patients with pneumonia due to 2019 novel coronavirus disease (COVID-19) in Jilin, China.

BACKGROUND: The clinical characteristics of patients with confirmed 2019 novel coronavirus disease (COVID-19) in Jilin Province, China were investigated. METHODS: Clinical, laboratory, radiology, and treatment data of 41 hospitalized patients with confirmed COVID-19 were retrospectively collected. The population was stratified by disease severity as mild, moderate, or severe, based on guidelines of the National Health and Medical Commission of China. RESULTS: The 41 hospitalized patients with COVID-19 were studied, and the median age was 45 years (interquartile range [IQR], 31-53; range, 10-87 years) and 18 patients (43.9%) were female. All of the patients had recently visited Wuhan or other places (ie, Beijing, Thailand) or had Wuhan-related exposure. Common symptoms included fever (32[78%]) and cough (29[70.7%]). All patients were without hepatitis B/C virus hepatitis. CRP (C-reactive protein, 11.3 mg/L [interquartile range {IQR}, 2.45-35.2]) was elevated in 22 patients (53.7%), and cardiac troponin I (1.5 ng/mL [IQR, 0.8-5.0]) was elevated in 41 patients (100%). Chest computed tomographic scans showed bilateral ground glass opacity (GGO) or GGO with consolidation in the lungs of 27(65.9%) patients. 31(75.6%) patients had an abnormal electrocardiograph (ECG). Comparing the three groups, the levels of CRP and cardiac troponin I, GGO distribution in bilateral lungs, and electrocardiogram changes were statistically significant (p < 0.05). Cardiac troponin I had a strong positive correlation with CRP (r = 0.704, p = 0.042) and LDH (r = 0.738, p = 0.037). CONCLUSION: Significant differences among the groups suggest that several clinical parameters may serve as biomarkers of COVID-19 severity at hospital admission. Elevated cTnI could be considered as a predictor of severe COVID-19, reflecting the prognosis of patients with severe COVID-19. The results warrant further inspection and confirmation.

Genetic characteristics and genetic evolution of porcine epidemicdiarrhea virus strain FJLY1703 in western Fujian province

In order to clarify the recombination and genetic evolution of porcine epidemic diarrhea virus (PEDV) isolates inwestern Fujian, a PEDV strain (FILY1703) was isolated from PEDV infected piglet samples in western Fujian, and its N, E, M and Sgenes were amplified by PCR and further sequenced and analyzed by bioinformatics software in this study. The homology andevolutionary analysis results showed that FJLY1703 had low homology and distant relationship with classical strains such as CV777, but high homology and close evolutionary relationship with the prevalent variants isolated in domestic after 2010. The amino acidsequence analysis showed the COE of FJLY1703 strain S protein had 8 mutations that were similar to prevalent variants in Chinaafter 2010 in comparison with the vaccine strain CV777. Further more, the amino acid sequence of FJLY1703 strain E, M and N genes had 1, 3 and 12 mutation sites respectively, which were the same as the prevalent variants in China. Recombination analysis ofS gene showed that FJLY1703 was a recombination strain of classical strain CV777 and mutant strain that prevalent variants after2010, and suggested the need to develop a vaccine against PEDV epidemic strains to control the infection of PEDV. This studyprovided data support for the epidemiological study of PEDV in China.

Clinical characteristics of family-clustered onset of coronavirus disease 2019 in Jilin Province, China.

Eight members of a big family with laboratory-confirmed COVID-19 pneumonia were admitted to First Hospital of Jilin University, Changchun, China, from 28 January to 5 February 2020. The clinical records, laboratory results, and chest computed tomography (CT) scans were retrospectively reviewed. Throat swab samples were positive for severe acute respiratory syndrome coronavirus 2, confirmed by the Center for Disease Control and Prevention of Changchun. All eight patients had fever of different degrees; and 6, 3, and 2 had cough; diarrhea; and sore throat. With disease progression, the percentage of lymphocytes in older patients increased, CT images worsened, and the ratio of lymphocytes increased when images revealed inflammation absorption. Although the CT images showed ground-glass opacities in the youngest patient, his lymphocyte count did not decrease with mild clinical symptoms, and the images showed that inflammation was quickly absorbed. Only the oldest patient developed critical illness. The C reaction protein (CRP) levels of Patient 5 increased significantly, and the rate of decline was the slowest, while his condition was the most severe. The clinical manifestations of COVID-19 in this family cluster varied with contact, age, and underlying disease. Lymphocyte count and quality of chest CT images appeared inversely associated with disease severity. CRP changes may be an indicator of disease severity and prognosis.

Mental Health Disorders and Associated Risk Factors in Quarantined Adults During the COVID-19 Outbreak in China: Cross-Sectional Study.

BACKGROUND: People undergoing mass home- and community-based quarantine are vulnerable to mental health disorders during outbreaks of coronavirus disease (COVID-19), but few studies have evaluated the associated psychosocial factors. OBJECTIVE: This study aimed to estimate the prevalence of anxiety and depressive symptoms and identify associated demographic and psychosocial factors in the general Chinese population during the COVID-19 pandemic quarantine period. METHODS: Participants aged 18 years or above were recruited in a cross-sectional online survey using snowball sampling from February 26-29, 2020. The survey included questions on demographics, family relationships, chronic diseases, quarantine conditions, lifestyle, COVID-19 infection, and anxiety and depressive symptoms. Logistic regression analyses were conducted to identify factors associated with elevated anxiety or depressive symptoms. RESULTS: Out of 2331 participants, 762 (32.7%) experienced elevated anxiety or depressive symptoms. Nine risk factors associated with anxiety or depressive symptoms included younger age, reduced income, having cancer or other chronic diseases, having family members living with cancer, concerns related to COVID-19 infection for themselves or family members, living alone, having family conflicts, having <3 or >8 hours of sedentary time per day, and worsened sleep quality. CONCLUSIONS: The findings highlight an urgent need for psychological support for populations at high risk for elevated anxiety or depressive symptoms during the COVID-19 pandemic.

A case series describing the epidemiology and clinical characteristics of COVID-19 infection in Jilin Province.

Since its outbreak in Wuhan, Hubei Province China, 2019-coronavirus infected disease (COVID-19) had been widely spread all over the world, the control of which calls for a better understanding of its epidemiology and clinical characteristics. We included 12 confirmed cases of COVID-19 in First Affiliated Hospital of Jilin University from 23 January 2020 to 11 February 2020, which were retrospectively analyzed for epidemiological, demographic, clinical, laboratory, and radiological features. All the patients were confirmed by nucleic acid detection, the average age of whom was 45.25 years (range, 23-79 years). Most patients had a history of Wuhan traveling or had contact with Wuhan travelers or infected cases. Obvious family cluster was observed. Clinical manifestations included fever (12/12), fatigue (10/12), cough (6/12), sore throat (4/12), headache (3/12), and diarrhea (2/12). Only three out of eight patients had pneumonia manifestation on radiography. Most patients had a normal white blood cell (WBC) count and normal or reduced lymphocyte (LY) count. Pneumonia changes were observed in all the four patients who underwent a chest CT scan. Only one elderly patient developed severe pneumonia, while all the rest were mild disease and had a self-limiting course.