AIR QUALITY ASSESSMENT OF IMMIGRANT RURAL COMMUNITIES BASED ON THE THEORY OF HEALTHY AND SUSTAINABLE DEVELOPMENT - A CASE STUDY OF IMMIGRANT COMMUNITIES IN HUBEI, CHINA

In the context of the global outbreak of COVID-19, health issues have attracted worldwide attention. Building a healthy ecological environment is particularly important for human beings, and among the ecological environmental factors, air quality is particularly prominent. The study takes the air quality of newly-built immigrant relocation communities in Western China as the research object, and adopts a number of technical methods, such as professional laboratory test report, instrument test, calculation test and so on. Obtain the data of regional ambient air quality and building indoor air quality, and comprehensively judge the regional environment and building ventilation efficiency of the experimental point. So as to comprehensively grade the air quality of the experimental point. A number of technologies and methods are studied and integrated to form a comprehensive three-dimensional air quality detection technology integration. From the perspective of air quality inspection, provide technical support for the healthy and sustainable development of relocated new rural communities. It is of great practical significance to supervise and urge the construction of a healthy and sustainable new township village.

Comparison of the clinical and CT features between COVID-19 and H1N1 influenza pneumonia patients in Zhejiang, China.

OBJECTIVE: To explore the different clinical and CT features distinguishing COVID-19 from H1N1 influenza pneumonia. PATIENTS AND METHODS: We compared two independent cohorts of COVID-19 pneumonia (n=405) and H1N1 influenza pneumonia (n=78), retrospectively. All patients were confirmed by RT-PCR. Four hundred and five cases of COVID-19 pneumonia were confirmed in nine hospitals of Zhejiang province, China from January 21 to February 20, 2020. Seventy-eight cases of H1N1 influenza pneumonia were confirmed in our hospital from January 1, 2017 to February 29, 2020. Their clinical manifestations, laboratory test results, and CT imaging characteristics were compared. RESULTS: COVID-19 pneumonia patients showed less proportions of underlying diseases, fever and respiratory symptoms than those of H1N1 pneumonia patients (p<0.01). White blood cell count, neutrophilic granulocyte percentage, C-reactive protein, procalcitonin, D-Dimer, and lactate dehydrogenase in H1N1 pneumonia patients were higher than those of COVID-19 pneumonia patients (p<0.05). H1N1 pneumonia was often symmetrically located in the dorsal part of inferior lung lobes, while COVID-19 pneumonia was unusually showed as a peripheral but non-specific lobe distribution. Ground glass opacity was more common in COVID-19 pneumonia and consolidation lesions were more common in H1N1 pneumonia (p<0.01). COVID-19 pneumonia lesions showed a relatively clear margin compared with H1N1 pneumonia. Crazy-paving pattern, thickening vessels, reversed halo sign and early fibrotic lesions were more common in COVID-19 pneumonia than H1N1 pneumonia (p<0.05). Pleural effusion in COVID-19 pneumonia was significantly less common than H1N1 pneumonia (p<0.01). CONCLUSIONS: Compared with H1N1 pneumonia in Zhejiang, China, the clinical manifestations of COVID-19 pneumonia were more concealed with less underlying diseases and slighter respiratory symptoms. The more common CT manifestations of COVID-19 pneumonia included ground-glass opacity with a relatively clear margin, crazy-paving pattern, thickening vessels, reversed halo sign, and early fibrotic lesions, while the less common CT manifestations of COVID-19 pneumonia included consolidation and pleural effusion.

[Predictive value of neutrophil/lymphocyte ratio on myocardial injury in severe COVID-19 patients].

Objective: To explore the predictive value of neutrophil/lymphocyte ratio (NLR) on myocardial injury in severe COVID-19 patients. Methods: In this single-center retrospective cohort study, we collected and analyzed data form 133 severe COVID-19 patients admitted to Renmin Hospital of Wuhan University (Eastern District) from January 30 to February 18, 2020. Patients were divided into myocardial injury group (n=29) and non-myocardial injury group (n=104) according the presence or absence of myocardial injury. The general information of patients was collected by electronic medical record database system. All patients were followed up for 30 days, the organ injury and/or dysfunction were monitored, the in-hospital death was compared between the two groups, and the disease progression was reevaluated and classified at 14 days after initial hospitalization. Logistic regression analysis was performed to identify risk factors of myocardial injury in severe COVID-19 patients. The ROC of NLR was calculated, and the AUC was determined to estimate the optimal cut-off value of NLR for predicting myocardial injury in severe cases of COVID-19. Results: There was statistical significance in age, respiratory frequency, systolic blood pressure, symptoms of dyspnea, previous chronic obstructive pulmonary disease, coronary heart disease history, white blood cells, neutrophils, lymphocytes, platelets, C-reactive protein, platelet counting, aspartate transaminase, albumin, total bilirubin, direct bilirubin, urea, estimated glomerular filtration rate, total cholesterol, low-density lipoprotein cholesterol, D-dimer, CD3+, CD4+, partial pressure of oxygen, partial pressure of CO2, blood oxygen saturation, other organ injury, clinical outcome and prognosis between patients with myocardial injury and without myocardial injury (all P<0.05). Multivariate logistic regression analysis showed that NLR was a risk factor for myocardial injury (OR=1.066，95%CI 1.021-1.111，P=0.033). ROC curve showed that NLR predicting AUC of myocardial injury in severe COVID-19 patients was 0.774 (95%CI 0.694-0.842), the optimal cut-off value of NLR was 5.768, with a sensitivity of 82.8%, and specificity of 69.5%. Conclusion: NLR may be used to predict myocardial injury in severe COVID-19 patients.