Effects of the COVID-19 Lockdown on Air Pollutant Levels and Associated Reductions in Ischemic Stroke Incidence in Shandong Province, China.

Background: Local governments in China took restrictive measures after the outbreak of COVID-19 to control its spread, which unintentionally resulted in reduced anthropogenic emission sources of air pollutants. In this study, we intended to examine the effects of the COVID-19 lockdown policy on the concentration levels of particulate matter with aerodynamic diameters of ≤1 µm (PM1), ≤2.5 µm (PM2.5), and ≤10 µm (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO) and the potential subsequent reductions in the incidence of ischemic and hemorrhagic stroke in Shandong Province, China. Methods: A difference-in-difference model combining the daily incidence data for ischemic and hemorrhagic stroke and air pollutant data in 126 counties was used to estimate the effect of the COVID-19 lockdown on the air pollutant levels and ischemic and hemorrhagic stroke incident counts. The avoided ischemic stroke cases related to the changes in air pollutant exposure levels were further estimated using concentration-response functions from previous studies. Results: The PM1, PM2.5, PM10, NO2, and CO levels significantly decreased by -30.2, -20.9, -13.5, -46.3, and -13.1%, respectively. The O3 level increased by 11.5% during the lockdown compared with that in the counterfactual lockdown phase of the past 2 years. There was a significant reduction in population-weighted ischemic stroke cases (-15,315, 95% confidence interval [CI]: -27,689, -2,942), representing a reduction of 27.6% (95% CI: -49.9%, -5.3%). The change in the number of hemorrhagic stroke cases was not statistically significant. The total avoided PM1-, PM2.5-, PM10-, NO2-, and CO-related ischemic stroke cases were 739 (95% CI: 641, 833), 509 (95% CI: 440, 575), 355 (95% CI: 304, 405), 1,132 (95% CI: 1,024, 1,240), and 289 (95% CI: 236, 340), respectively. Conclusion: The COVID-19 lockdown indirectly reduced the concentration levels of PM1, PM2.5, PM10, NO2, and CO and subsequently reduced the associated ischemic stroke incidence. The health benefits due to the lockdown are temporary, and long-term measures should be implemented to increase air quality and related health benefits in the post-COVID-19 period.

Nomogram for Predicting COVID-19 Disease Progression Based on Single-Center Data: Observational Study and Model Development.

BACKGROUND: In late December 2019, a pneumonia caused by SARS-CoV-2 was first reported in Wuhan and spread worldwide rapidly. Currently, no specific medicine is available to treat infection with COVID-19. OBJECTIVE: The aims of this study were to summarize the epidemiological and clinical characteristics of 175 patients with SARS-CoV-2 infection who were hospitalized in Renmin Hospital of Wuhan University from January 1 to January 31, 2020, and to establish a tool to identify potential critical patients with COVID-19 and help clinical physicians prevent progression of this disease. METHODS: In this retrospective study, clinical characteristics of 175 confirmed COVID-19 cases were collected and analyzed. Univariate analysis and least absolute shrinkage and selection operator (LASSO) regression were used to select variables. Multivariate analysis was applied to identify independent risk factors in COVID-19 progression. We established a nomogram to evaluate the probability of progression of the condition of a patient with COVID-19 to severe within three weeks of disease onset. The nomogram was verified using calibration curves and receiver operating characteristic curves. RESULTS: A total of 18 variables were considered to be risk factors after the univariate regression analysis of the laboratory parameters (P<.05), and LASSO regression analysis screened out 10 risk factors for further study. The six independent risk factors revealed by multivariate Cox regression were age (OR 1.035, 95% CI 1.017-1.054; P<.001), CK level (OR 1.002, 95% CI 1.0003-1.0039; P=.02), CD4 count (OR 0.995, 95% CI 0.992-0.998; P=.002), CD8 % (OR 1.007, 95% CI 1.004-1.012, P<.001), CD8 count (OR 0.881, 95% CI 0.835-0.931; P<.001), and C3 count (OR 6.93, 95% CI 1.945-24.691; P=.003). The areas under the curve of the prediction model for 0.5-week, 1-week, 2-week and 3-week nonsevere probability were 0.721, 0.742, 0.87, and 0.832, respectively. The calibration curves showed that the model had good prediction ability within three weeks of disease onset. CONCLUSIONS: This study presents a predictive nomogram of critical patients with COVID-19 based on LASSO and Cox regression analysis. Clinical use of the nomogram may enable timely detection of potential critical patients with COVID-19 and instruct clinicians to administer early intervention to these patients to prevent the disease from worsening.

Comparison of clinical characteristics of COVID-19 between elderly patients and young patients: a study based on a 28-day follow-up.

The number of corona virus disease 2019 cases is increasing rapidly. However, the comparison of clinical characteristics between patients ≥ 70 and those < 70 has not been implemented yet. To achieve that, we collected clinical data of consecutive 222 patients in Renmin Hospital of Wuhan University diagnosed between January 13, 2020 and February 4, 2020. We divided them into an under-70 group and an over-70 group according to their ages, comparing their clinical characteristics. Meanwhile, univariate and multivariate Cox regression analyses were performed to identify the prognostic factors. Among the patients enrolled, 37 (16.67%) were 70 or older and 185 (83.33%) were younger than 70. Higher proportions of dyspnoea, expectoration, chronic cardiovascular disease, diabetes, organ complications, severe-to-critical cases, a higher death rate, a longer hospital stay and decreased immune status were observed in the over-70 group patients compared with their younger counterparts. The risk factors for death included dyspnoea, muscle ache, elevated myocardial enzymes, elevated C3 in over-70 patients and dyspnoea, pharyngalgia, chronic cardiac disease, increased C-reactive protein, IgA, decreased platelets in under-70 patients. Overall, our research compared the clinical characteristics of the two populations with different immune status and illustrated differentiated risk factors for death in them.

The clinical course and its correlated immune status in COVID-19 pneumonia.

OBJECTIVES: To explore the clinical course and its dynamic features of immune status in COVID-19 patients and find predictors correlated with severity and prognosis of COVID-19. METHODS: The electronic medical records of 204 patients with COVID-19 pneumonia confirmed by nucleic acid testing were retrospectively collected and analyzed. RESULTS: All patients were divided into severe (69) and non-severe group (135). Lymphocyte subsets count, including CD3+ T cell, CD4+ T cell, CD8+ T cell, B cell (CD19+) and NK cell (CD16+ 56+), were significantly lower in severe group (P＜0.001). The dynamic levels of T lymphocyte in severe group were significantly lower from disease onset, but in the improved subgroup the value of T lymphocyte began to increase after about 15-day treatment and finally returned to the normal level. The cut-off value of the counts of CD3+ (576), CD4+ (391) and CD8+ (214) T cell were calculated and indicated significantly high sensitivity and specificity for severity of COVID-19. CONCLUSION: Our results shown that the decrease of CD3+, CD4+ and CD8+ T lymphocyte correlated with the course of patients with COVID-19 pneumonia, especially in severe cases. The level of T lymphocyte could be used as an indicator for prediction of severity and prognosis of patients with COVID-19 pneumonia. The application of glucocorticoid should be cautious in severe cases.

CT imaging and clinical course of asymptomatic cases with COVID-19 pneumonia at admission in Wuhan, China.

PURPOSE: Aimed to characterize the CT imaging and clinical course of asymptomatic cases with COVID-19 pneumonia. METHODS: Asymptomatic cases with COVID-19 pneumonia confirmed by SARS-COV-2 nucleic acid testing in Renmin Hospital of Wuhan University were retrospectively enrolled. The characteristics of CT imaging and clinical feature were collected and analyzed. RESULTS: 58 asymptomatic cases with COVID-19 pneumonia admitted to our hospital between Jan 1, 2020 and Feb 23, 2020 were enrolled. All patients had history of exposure to SARS-CoV-2. On admission, patients had no symptoms and laboratory findings were normal. The predominant feature of CT findings in this cohort was ground glass opacity (GGO) (55, 94.8%) with peripheral (44, 75.9%) distribution, unilateral location (34, 58.6%) and mostly involving one or two lobes (38, 65.5%), often accompanied by characteristic signs. After short-term follow-up, 16 patients (27.6%) presented symptoms with lower lymphocyte count and higher CRP, mainly including fever, cough and fatigue. The evolution of lesions on CT imaging were observed in 10 patients (17.2%). The average days of hospitalization was19.80±10.82 days, and was significantly longer in progression patients (28.60±7.55 day). CONCLUSION: CT imaging of asymptomatic cases with COVID-19 pneumonia has definite characteristics. Since asymptomatic infections as "covert transmitter", and some patients can progress rapidly in the short term. It is essential to pay attention to the surveillance of asymptomatic patients with COVID-19. CT scan has great value in screening and detecting patients with COVID-19 pneumonia, especially in the highly suspicious, asymptomatic cases with negative nucleic acid testing.