Timeliness of information disclosure during the low transmission period of COVID-19: resident-level observational study in China.

BACKGROUND: Only when people feel they have received timely disclosure will they have sufficient incentive to implement community prevention and control measures. The timely and standardized information published by authorities as a response to the crisis can better inform the public and enable better preparations for the pandemic during the low transmission period of COVID-19; however, there is limited evidence of whether people consent that information is disclosed timely and influencing factors. METHODS: A cross-sectional survey was conducted in China from 4 to 26 February 2021. Convenient sampling strategy was adopted to recruit participators. Participants were asked to filled out the questions that assessed questionnaire on the residents' attitudes to information disclosure timely. A binary logistic regression analysis was performed to identify the risk factors affecting the residents' attitudes. RESULTS: A total of 2361 residents filled out the questionnaire. 1704 (72.17%) consented COVID-19 information has been disclosed timely. Furthermore, age (OR = 0.093, 95%CI = 0.043 ~ 0.201), gender (OR = 1.396, 95%CI = 1.085 ~ 1.797), place of residence (OR = 0.650, 95%CI = 0.525 ~ 0.804), employed status (OR = 2.757, 95%CI = 1.598 ~ 4.756), highest educational level (OR = 0.394, 95%CI = 0.176 ~ 0.880), region (OR = 0.561, 95%CI = 0.437 ~ 0.720) and impact on life by the COVID-19 (OR = 0.482, 95%CI = 0.270 ~ 0.861) were mainly factors associated with residents' attitudes. CONCLUSIONS: The aims of this study were to evaluate the residents attitudes to information disclosure timely during the low transmission period in China and to provide a scientific basis for effective information communication in future public health crises. Timely and effective efforts to disclose information need to been made during the low transmission period. Continued improvements to local authority reporting will contribute to more effective public communication and efficient public health research responses. The development of protocols and the standardization of epidemic message templates-as well as the use of uniform operating procedures to provide regular information updates-should be prioritized to ensure a coordinated national response.

The characteristics and evolution of pulmonary fibrosis in COVID-19 patients as assessed by AI-assisted chest HRCT.

The characteristics and evolution of pulmonary fibrosis in patients with coronavirus disease 2019 (COVID-19) have not been adequately studied. AI-assisted chest high-resolution computed tomography (HRCT) was used to investigate the proportion of COVID-19 patients with pulmonary fibrosis, the relationship between the degree of fibrosis and the clinical classification of COVID-19, the characteristics of and risk factors for pulmonary fibrosis, and the evolution of pulmonary fibrosis after discharge. The incidence of pulmonary fibrosis in patients with severe or critical COVID-19 was significantly higher than that in patients with moderate COVID-19. There were significant differences in the degree of pulmonary inflammation and the extent of the affected area among patients with mild, moderate and severe pulmonary fibrosis. The IL-6 level in the acute stage and albumin level were independent risk factors for pulmonary fibrosis. Ground-glass opacities, linear opacities, interlobular septal thickening, reticulation, honeycombing, bronchiectasis and the extent of the affected area were significantly improved 30, 60 and 90 days after discharge compared with at discharge. The more severe the clinical classification of COVID-19, the more severe the residual pulmonary fibrosis was; however, in most patients, pulmonary fibrosis was improved or even resolved within 90 days after discharge.

A risk score based on baseline risk factors for predicting mortality in COVID-19 patients.

BACKGROUND: To develop a sensitive and clinically applicable risk assessment tool identifying coronavirus disease 2019 (COVID-19) patients with a high risk of mortality at hospital admission. This model would assist frontline clinicians in optimizing medical treatment with limited resources. METHODS: 6415 patients from seven hospitals in Wuhan city were assigned to the training and testing cohorts. A total of 6351 patients from another three hospitals in Wuhan, 2169 patients from outside of Wuhan, and 553 patients from Milan, Italy were assigned to three independent validation cohorts. A total of 64 candidate clinical variables at hospital admission were analyzed by random forest and least absolute shrinkage and selection operator (LASSO) analyses. RESULTS: Eight factors, namely, Oxygen saturation, blood Urea nitrogen, Respiratory rate, admission before the date the national Maximum number of daily new cases was reached, Age, Procalcitonin, C-reactive protein (CRP), and absolute Neutrophil counts, were identified as having significant associations with mortality in COVID-19 patients. A composite score based on these eight risk factors, termed the OURMAPCN-score, predicted the risk of mortality among the COVID-19 patients, with a C-statistic of 0.92 (95% confidence interval [CI] 0.90-0.93). The hazard ratio for all-cause mortality between patients with OURMAPCN-score >11 compared with those with scores ≤ 11 was 18.18 (95% CI 13.93-23.71; p < .0001). The predictive performance, specificity, and sensitivity of the score were validated in three independent cohorts. CONCLUSIONS: The OURMAPCN score is a risk assessment tool to determine the mortality rate in COVID-19 patients based on a limited number of baseline parameters. This tool can assist physicians in optimizing the clinical management of COVID-19 patients with limited hospital resources.

Clinical features of patients with coronavirus disease 2019 from a designated hospital in Beijing, China.

Clinical and laboratory data on patients with coronavirus disease 2019 (COVID-19) in Beijing, China, remain extremely limited. In this study, we summarized the clinical characteristics of patients with COVID-19 from a designated hospital in Beijing. In total, 55 patients with laboratory-confirmed SARS-CoV-2 infection in Beijing 302 Hospital were enrolled in this study. Demographic data, symptoms, comorbidities, laboratory values, treatments, and clinical outcomes were all collected and retrospectively analyzed. A total of 15 (27.3%) patients had severe symptoms, the mean age was 44.0 years (interquartile range [IQR], 34.0-56.0), and the median incubation period was 7.5 days (IQR, 5.0-11.8). A total of 26 (47.3%) patients had exposure history in Wuhan of less than 2 weeks, whereas 20 (36.4%) patients were associated with familial clusters. Also, eighteen (32.7%) patients had underlying comorbidities including hypertension. The most common symptom of illness was fever (45; 81.8%); 51 (92.7%) patients had abnormal findings on chest computed tomography. Laboratory findings showed that neutrophil count, percentage of lymphocyte, percentage of eosinophil, eosinophil count, erythrocyte sedimentation rate, albumin, and serum ferritin are potential risk factors for patients with a poor prognosis. A total of 26 patients (47.3%) were still hospitalized, whereas 29 (52.7%) patients had been discharged. Compared with patients in Wuhan, China, the symptoms of patients in Beijing are relatively mild. Older age, more comorbidities, and more abnormal prominent laboratory markers were associated with a severe condition. On the basis of antiviral drugs, it is observed that antibiotics treatment, appropriate dosage of corticosteroid, and gamma globulin therapy significantly improve patients' outcomes. Early identification and timely medical treatment are important to reduce the severity of patients with COVID-19.

In-Hospital Use of Statins Is Associated with a Reduced Risk of Mortality among Individuals with COVID-19.

Statins are lipid-lowering therapeutics with favorable anti-inflammatory profiles and have been proposed as an adjunct therapy for COVID-19. However, statins may increase the risk of SARS-CoV-2 viral entry by inducing ACE2 expression. Here, we performed a retrospective study on 13,981 patients with COVID-19 in Hubei Province, China, among which 1,219 received statins. Based on a mixed-effect Cox model after propensity score-matching, we found that the risk for 28-day all-cause mortality was 5.2% and 9.4% in the matched statin and non-statin groups, respectively, with an adjusted hazard ratio of 0.58. The statin use-associated lower risk of mortality was also observed in the Cox time-varying model and marginal structural model analysis. These results give support for the completion of ongoing prospective studies and randomized controlled trials involving statin treatment for COVID-19, which are needed to further validate the utility of this class of drugs to combat the mortality of this pandemic.

The Issue of Recurrently Positive Patients Who Recovered From COVID-19 According to the Current Discharge Criteria: Investigation of Patients from Multiple Medical Institutions in Wuhan, China.

The current discharge criteria for COVID-19 require that patients have 2 consecutive negative results for reverse transcription polymerase chain reaction (RT-PCR) detection. Here, we observed that recurrent positive RT-PCR test results in patients with 3 consecutive negative results (5.4%) were significantly decreased compared with those in patients with 2 consecutive negative results (20.6%); such patients reported positive RT-PCR test results within 1 to 12 days after meeting the discharge criteria. These results confirmed that many recovered patients could show a positive RT-PCR test result, and most of these patients could be identified by an additional RT-PCR test prior to discharge.