What Risk Factors to Cause Long COVID and Its Impact on Patient Survival Outcomes when Combined with the Effect from Organ Transplantation in the Acute COVID (preprint)

Background Coronavirus disease 2019 (COVID-19) in solid organ transplant (SOT) patients is associated with more severe outcomes than non-immunosuppressed hosts. However, exactly which risk factors cause Long COVID in acute COVID cases remains unknown. More importantly, the impact of Long COVID on patient survival remains understudied, especially when examined alongside the effect of SOT. Methods All patients have been identified with acute COVID in the National COVID Collaborative Cohort registry from July 1, 2020, to June 30, 2022. We compared patient demographics in Long COVID vs. those without Long COVID based on descriptive statistics. Multivariable logistics regressions were used to determine the factors related to the likelihood of developing Long COVID from a case of acute COVID. Multi-variables Cox regression was used to determine the time-to-event outcome of patient survival with Long COVID. Results This study reviewed data from a cohort of 6,416,500 acute COVID patients. Of that group, 31,744 (0.5%) patients developed Long COVID from ICD diagnosis. The mean (q1, q3) age was 39 (22, 57) years old, and 55% of patients were female. From this cohort, a total of 31,744 (1%) developed Long COVID and 43,565 (1%) had SOT, with a total of 698 SOT patients identified with Long COVID. Mean age of those with Long COVID was 52 (39, 64) years old and 64% of patients were female. Most of the SOT patients were kidney transplant recipients. From the Cox regression analysis of patient survival, there were many significant factors related to patient survival (death), with elderly SOT patients having a much higher hazard ratio of 27.8 (26.3, 29.4). Conclusion This study has identified the important risk factors that are more likely to cause Long COVID in an acute COVID cohort. We investigated hazard ratios of patient survival based on multivariable Cox models, which found that Long COVID had a more direct impact on survival in elderly patients and those with SOT.

What Risk Factors to Cause Long COVID and Its Impact on Patient Survival Outcomes when Combined with the Effect from Organ Transplantation in the Acute COVID (preprint)

Coronavirus disease 2019 in solid organ transplant (SOT) patients is associated with more severe outcomes than non-immunosuppressed hosts. However, exactly which risk factors cause Long COVID in acute COVID cases remains unknown. More importantly, the impact of Long COVID on patient survival remains understudied, especially when examined alongside the effect of SOT. All patients have been identified with acute COVID in the National COVID Collaborative Cohort registry. We compared patient demographics in Long COVID vs. those without Long COVID based on descriptive statistics. Multivariable logistics regressions were used to determine the factors related to the likelihood of developing Long COVID from a case of acute COVID. Multi-variables Cox regression was used to determine the time-to-event outcome of patient survival with Long COVID. This study reviewed data from a cohort of 6,416,500 acute COVID patients. Of that group, 31,744 patients developed Long COVID from ICD diagnosis. The mean (q1, q3) age was 39 (22, 57) years old, and 55% of patients were female. From this cohort, a total of 31,744 (1%) developed Long COVID and 43,565 (1%) had SOT, with a total of 698 SOT patients identified with Long COVID. Mean age of those with Long COVID was 52 (39, 64) years old and 64% of patients were female. Most of the SOT patients were kidney transplant recipients. From the Cox regression analysis of patient survival, there were many significant factors related to patient survival, with elderly SOT patients having a much higher hazard ratio of 27.8 (26.3, 29.4). This study has identified the important risk factors that are more likely to cause Long COVID in an acute COVID cohort. We investigated hazard ratios of patient survival based on multivariable Cox models, which found that Long COVID had a more direct impact on survival in elderly patients and those with SOT.

A Validation Study for the Successful Isolation Policy in China: a Meta-Analysis in COVID-19 (preprint)

COVID-19 is quickly spreading around the world and carries along with it a significant threat to public health. This study sought to apply meta-analysis to more precisely and accurately estimate the basic reproduction number (R0) of COVID-19 in order to evaluate the effectiveness of the isolation policy across countries, and the corresponding public health capability to care for patients. Prior estimates of R0 have varied widely and range from 1.95 to 6.49. Utilizing meta-analysis techniques we determined a more robust estimation of 3.05 for R0, which is substantially larger than that provided by the WHO. We also present the infectious rate standardized to per million population, which has proved to be a good index to determine whether the isolation measures in specific countries are effective. Also, this standardized infection rate can be used to determine whether the current infectious severity status is out of range of the national health capacity. Finally, we utilize our robust estimate of R0 and the standardized infectious rate to illustrate that the early and aggressive isolation measures enforced by the Chinese government were substantially more effective in controlling the negative impact COVID-19 than the more permissive measures enacted early in Italy and the United States.

Chest CT Scan of Hospitalized Patients with COVID-19: A Case-Control Study (preprint)

Introduction: This paper sought to investigate the clinical characteristic differences between suspected and confirmed patients with COVID-19 from CT scan to prevent and treat this infectious disease, since the coronavirus outbreak in the world has seriously affected the quality of life. Methods: We proposed to use a retrospective case-control study to give a comparison between suspected patients and confirmed patients in the clinical characteristics. Results: (56%) patients were confirmed for COVID-19 from suspected 167 patients. We find that elder people were more likely to be infected by COVID-19. Among the confirmed 94 patients, 2 (2%) patients were admitted to an intensive care unit, and 0 (0%) patients died during the study period. We find that images of CT scan of patients with a COVID-19 are significantly different from patients without a COVID-19. Conclusions: To our best knowledge, it is the first time to use the case-control design to study the coronavirus disease, since it is particularly appropriate for investigating infectious disease outbreaks. The clinical treatment experience in this study can supply a guideline for treating COVID-19 as the number of the infected patients is increasing in the world. Compared with other studies, we find that the mortality rate and the intensive care unit rate can be reduced if patients can be treated timely in the right identification and detection with nucleic acid testing and chest CT scan. Therefore, we recommend nucleic acid testing and chest CT scan for the clinical treatment practice from this successful clinical treatment study.

Statistical Inference for Coronavirus Infected Patients in Wuhan (preprint)

Importance: The new coronavirus outbreak has seriously affected the quality of life in China. Wuhan is the disaster area, where the number of cases has increased rapidly. However, the current measures of infected patients in Wuhan are still underestimated. Objective: To estimate the overall infected patients in Wuhan from several sampled data. The correct estimated infected patients can be helpful for the government to arrange the needed beds in hospital wards to meet the actual needs. Design: We proposed to use the sampling survey to estimate the overall infected patients in Wuhan. The sampling survey is a kind of non-comprehensive survey. It selected some units from all the survey objects to carry out the survey and made the estimation and inference to all the survey objects. Sampling surveys can obtain information that reflects the overall situation, although it is not a comprehensive survey. Setting: We estimated the overall infection rate in Wenzhou city, which has a better data collection system. Simultaneously, another different samples of Wuhan tourists to Singapore will be used to validate the infection rate in Wenzhou city. Combined these two samples, we give the estimation of the number of infected patients in Wuhan and other prefecture-level cities in Hubei Province. Participants: The number of people who returned from Wuhan to Wenzhou was selected from the daily notification of the pneumonia epidemic caused by a new coronavirus infection in the city. Exposures for observational studies: The daily rate of the pneumonia epidemic caused by the new coronavirus infection in Wenzhou City. The numerator is the number of people diagnosed and whether each person diagnosed had a history of living in Wuhan. The denominator is the total number of people returning to Wenzhou from Wuhan. Based on this rate, it is reasonable to predict the number of the infected patients.