Severe/critical COVID-19 early warning system based on machine learning algorithms using novel imaging scores.

BACKGROUND: Early identification of severe/critical coronavirus disease 2019 (COVID-19) is crucial for timely treatment and intervention. Chest computed tomography (CT) score has been shown to be a significant factor in the diagnosis and treatment of pneumonia, however, there is currently a lack of effective early warning systems for severe/critical COVID-19 based on dynamic CT evolution. AIM: To develop a severe/critical COVID-19 prediction model using a combination of imaging scores, clinical features, and biomarker levels. METHODS: This study used an improved scoring system to extract and describe the chest CT characteristics of COVID-19 patients. The study also took into consideration the general clinical indicators such as dyspnea, oxygen saturation, alternative lengthening of telomeres (ALT), and androgen suppression treatment (AST), which are commonly associated with severe/critical COVID-19 cases. The study employed lasso regression to evaluate and rank the significance of different disease characteristics. RESULTS: The results showed that blood oxygen saturation, ALT, IL-6/IL-10, combined score, ground glass opacity score, age, crazy paving mode score, qsofa, AST, and overall lung involvement score were key factors in predicting severe/critical COVID-19 cases. The study established a COVID-19 severe/critical early warning system using various machine learning algorithms, including XGBClassifier, Logistic Regression, MLPClassifier, RandomForestClassifier, and AdaBoost Classifier. The study concluded that the prediction model based on the improved CT score and machine learning algorithms is a feasible method for early detection of severe/critical COVID-19 evolution. CONCLUSION: The findings of this study suggest that a prediction model based on improved CT scores and machine learning algorithms is effective in detecting the early warning signals of severe/critical COVID-19.

Ethical review of off-label drugs during the COVID-19 pandemic.

High-quality scientific research is very important in attempting to effectively control the coronavirus disease 2019 (COVID-19) pandemic and ensure people's health and safety. Chloroquine (CQ) and hydroxychloroquine (HCQ) have received much attention. This article comprehensively investigates the ethical review of off-label CQ and HCQ research during the COVID-19 pandemic with regard to strictly abiding by review standards, improving review efficiency, ensuring the rights and interests of subjects and that ethics committees conduct independent reviews, and achieving full ethics supervision of research conducted during an emergency. Research must be both rigorous and prudent to ensure the best outcome, with the maximization of benefits as the core principle. Standardization of the application, implementation and ethical review processes are needed to prevent unnecessary risk.

The imaging and clinical characteristics of patients with immune breakthrough Omicron-variant infected patients, Tianjin China: Is the vaccine effective? (preprint)

Background The protective effect of the inactivated vaccine against the omicron variant of COVID-19 is unclear. The purpose of this study was to investigate the protective effect of different vaccination status on omicron infection.Methods In this retrospective study, we analyzed patients over 14 years old, and were diagnosed with immune breakthrough Omicron-variant infection between December 2021 and February 2022 in Tianjin, China, as well as data from several previous study infected by other types of SARS-CoV-2. The data were subdivided into three groups: patients with fully, partially and unvaccine. Differences of clinical and imaging characteristics were compared based on the different vaccination status using Pearson Chi-square test, Fisher's accuracy test and non-parametric test. All of the data were also compared with other types of SARS-CoV-2. Logistic regression and mediation effect analysis were used to assess the association between vaccination status and pneumonia progression during hospitalization.Results Among the 314 cases of immune breakthrough Omicron-variant infected patients, 21(7%) patients were unvaccinated, 134 (43%) were partially vaccinated, and 159 (50%) were full vaccinated. Among fully vaccinated patients, the proportion of patients with positive CT findings (32%) and CT score 2 (6%) was significantly lower than that of partially vaccinated (46%, 14%) and unvaccinated patients (67%, 19%) (P < 0.05). CT score by vaccination status are similar between Omicron and other types, only partially vaccinated group of Omicron infected patients show lower CT score than other types infected patients (P = 0.005). Increased age and lower IgG levels were associated with the risk of disease progression. IgG level had a complete mediating effect between vaccination status/ days after vaccination and disease progression.Conclusion The inactivated vaccine provided similar protection against Omicron infection of SARS-CoV-2, compared to the patients who received other types vaccines. Compared with partially vaccinated and unvaccinated patients, fully vaccinated patients had a higher CT negative rate and a lower rate of severe pneumonia. Vaccination status and days after vaccination affect disease progression through IgG levels.

The effect of mental health on sleep quality of front-line medical staff during the COVID-19 outbreak in China: A cross-sectional study.

BACKGROUND: The 2019 coronavirus disease (COVID-19) pandemic is a public health emergency of international concern and poses a challenge to the mental health and sleep quality of front-line medical staff (FMS). The aim of this study was to investigate the sleep quality of FMS during the COVID-19 outbreak in China and analyze the relationship between mental health and sleep quality of FMS. METHODS: From February 24, 2020 to March 22, 2020, a cross-sectional study was performed with 543 FMS from a medical center in Western China. A self-reported questionnaire was used to collect data anonymously. The following tests were used: The Self-Rating Anxiety Scale (SAS) for symptoms of anxiety, the Beck Depression Inventory (BDI) for depressive symptoms, and the Pittsburgh Sleep Quality Index (PSQI) for sleep quality assessment. RESULTS: Of the 543 FMS, 216 (39.8%) were classified as subjects with poor sleep quality. Anxiety (P<0.001), depression (P<0.001), and the prevalence of those divorced or widowed (P<0.05) were more common in FMS with poor sleep quality than in participants with good sleep quality. The FMS exhibiting co-occurrence of anxiety and depression were associated with worse scores on sleep quality than those medical staff in the other three groups/categories. The difference in sleep quality between the FMS with only depression and the FMS experiencing co-occurrence of anxiety and depression was statistically significant (P<0.05). However, there was no significant difference in sleep quality between the FMS experiencing only anxiety and the FMS with co-occurrence of anxiety and depression (P > 0.05). CONCLUSIONS: During the COVID-19 pandemic, there was a noteworthy increase in the prevalence of negative emotions and sentiments among the medical staff, along with poor overall sleep quality. We anticipate that this study can stimulate more research into the mental state of FMS during outbreaks and other public health emergencies. In addition, particular attention must be paid to enhance the sleep quality of FMS, along with better planning and support for FMS who are continuously exposed to the existing viral epidemic by virtue of the nature of their profession.

Associations Between the Use of Renin-Angiotensin System Inhibitors and the Risks of Severe COVID-19 and Mortality in COVID-19 Patients With Hypertension: A Meta-Analysis of Observational Studies.

Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) share a target receptor with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The use of ACEIs/ARBs may cause angiotensin-converting enzyme 2 receptor upregulation, facilitating the entry of SARS-CoV-2 into host cells. There is concern that the use of ACEIs/ARBs could increase the risks of severe COVID-19 and mortality. The impact of discontinuing these drugs in patients with COVID-19 remains uncertain. We aimed to assess the association between the use of ACEIs/ARBs and the risks of mortality and severe disease in patients with COVID-19. A systematic search was performed in PubMed, EMBASE, Cochrane Library, and MedRxiv.org from December 1, 2019, to June 20, 2020. We also identified additional citations by manually searching the reference lists of eligible articles. Forty-two observational studies including 63,893 participants were included. We found that the use of ACEIs/ARBs was not significantly associated with a reduction in the relative risk of all-cause mortality [odds ratio (OR) = 0.87, 95% confidence interval (95% CI) = 0.75-1.00; I 2 = 57%, p = 0.05]. We found no significant reduction in the risk of severe disease in the ACEI subgroup (OR = 0.95, 95% CI = 0.88-1.02, I 2 = 50%, p = 0.18), the ARB subgroup (OR = 1.03, 95% CI = 0.94-1.13, I 2 = 62%, p = 0.48), or the ACEI/ARB subgroup (OR = 0.83, 95% CI = 0.65-1.08, I 2 = 67%, p = 0.16). Moreover, seven studies showed no significant difference in the duration of hospitalization between the two groups (mean difference = 0.33, 95% CI = -1.75 to 2.40, p = 0.76). In conclusion, the use of ACEIs/ARBs appears to not have a significant effect on mortality, disease severity, or duration of hospitalization in COVID-19 patients. On the basis of the findings of this meta-analysis, there is no support for the cessation of treatment with ACEIs or ARBs in patients with COVID-19.

Chronic Active Hepatitis B with COVID-19 in Pregnancy: A Case Report.

Currently, infection with coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), during pregnancy is a problem worthy of attention, especially in patients with underlying diseases. In this case report, we present a case of chronic active hepatitis B with COVID-19 in pregnancy. A 31-year-old woman at 29 weeks of gestation who had a history of chronic hepatitis B virus infection discontinued antiviral treatment, was admitted to the hospital with chronic active hepatitis B, and tested positive for SARS-CoV-2 infection. In this case, we applied liver protective and antiviral agents, and low-dose dexamethasone therapy to successfully treat the critically ill pregnant woman suffering from chronic active hepatitis B combined with COVID-19.