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The clinical spectrum of COVID-19 pneumonia is varied. Thus, it is important to identify risk factors at an early stage for predicting deterioration that require transferring the patients to ICU. A retrospective multicenter study was conducted on COVID-19 patients admitted to designated hospitals in China from Jan 17, 2020, to Feb 17, 2020. Clinical presentation, laboratory data, and quantitative CT parameters were also collected. The result showed that increasing risks of ICU admission were associated with age > 60 years (odds ratio [OR], 12.72; 95% confidence interval [CI], 2.42–24.61; P = 0.032), coexisting conditions (OR, 5.55; 95% CI, 1.59–19.38; P = 0.007) and CT derived total opacity percentage (TOP) (OR, 8.0; 95% CI, 1.45–39.29; P = 0.016). In conclusion, older age, coexisting conditions, larger TOP at the time of hospital admission are associated with ICU admission in patients with COVID-19 pneumonia. Early monitoring the progression of the disease and implementing appropriate therapies are warranted.

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and key terms 18 Abstract: 19 Computer Fluid Dynamics (CFD) is a popular method for studying airflow of nasal 20 cavities. However, the data of CFD studies has rarely been validated through Experimental Validation of the CFD of Normal Nasal Flow 2 21 experiments. To test the accuracy of CFD computation, we studied the consistency of 22 the air pressure of nasal cavities in the CFD and the experiment. A proportional resin 23 model of a normal human subject's nasal cavities was created by a 3-d printer with a 24 precision value of 0.1mm. The pressure of 63 check points in the nasal cavities in 25 different breathing states was measured. The experimental data was compared with the 26 data obtained by CFD simulation. At the flow rates of 180 ml s -1 and 560 ml s -1 , the 27 pressure in all check points remained highly consistent with the CFD data. At 1100 ml s -28 1 flow rate, there was a significant deviation in the posterior segment of the nasal cavity 29 during exhalation. The method used in this study to measure the pressure in the nasal 30 cavities can be used in experimental validation of CFD data. The computational 31 methods and the boundary conditions used in this study resulted in a high agreement 32between the results of the CFD simulation and the experiment. 33In the contemporary era, Computer fluid dynamics (CFD) is the mainstream 36 method for studying air flow. Due to the complex anatomical structure of the nasal 37 cavity, the CFD results of the nasal flow have rarely been experimentally verified. This 38 study provides a method to verify the methods and results of nasal CFD. We printed an 39 accurate model of a normal person's nasal cavity with a high-precision 3D printer. In this 40 nasal cavity model, we set 63 small holes to detect the air pressure of the places we 41 concerned. Three different nasal flow quantity are used to represent different breathing 42 conditions: high (1100 ml s-1), medium (560 ml s-1), and low (180 ml s-1). In medium 43 and low nasal flow quantities, our CFD results are in good agreement with the Experimental Validation of the CFD of Normal Nasal Flow 3 44 experimental pressure values. On this basis, we analyzed the characteristics of nasal 45 airflow in normal people. The method used in this study to measure the pressure in the 46 nasal cavities can be used in experimental measurements of the partial resistance of 47 the nasal cavity. With proper modification, it can be applied to the clinical practice for 48 nasal resistance, giving more help for the design of the operation plan. 49 50 59 rhinometry) can be taken, and correlation between these measurements and clinical 60 practice is questionable[2]. 61 Due to the complex internal structure of the nasal cavity, it is difficulty to study its 62 internal flow directly. The internal flow in the nasal cavity can only be estimated 63 indirectly by studying the flow outside the nasal cavity[3]. Previous researchers Hahn et 64 al. made a valuable study by constructing an enlarged scale (20x) model of a human 65 nasal cavity[...