Time series analysis revealed prognostic value of continuous nasopharyngeal SARS-CoV-2 nucleic acid quantification for COVID-19: A retrospective study of >3000 COVID-19 patients from 2 centers.

BACKGROUND: Early stratification of disease progression remains one of the major challenges towards the post-coronavirus disease 2019 (COVID-19) era. The clinical relevance of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid load is debated due to the heterogeneity in patients' underlying health conditions. We determined the prognostic value of nasopharyngeal viral load dynamic conversion for COVID-19. METHODS: The cycling threshold (Ct) values of 28,937 nasopharyngeal SARS-CoV-2 RT-PCRs were retrospectively collected from 3,364 COVID-19 patients during hospitalization and coordinated to the onset of disease progression. The ROC curve was utilized to determine the predictive performance of the rate of Ct value alteration between two consecutive RT-PCR runs within 48 h (ΔCt%) for disease transformation across patients with different COVID-19 severity and immune backgrounds, and further validated with 1,860 SARS-CoV-2 RT-PCR results from an independent validation cohort of 262 patients. For the 67 patients with severe COVID-19, Kaplan-Meier analysis was performed to evaluate the difference in survival between patients stratified by the magnitude of Ct value alteration between the late and early stages of hospitalization. RESULTS: The kinetics of viral nucleic acid conversion diversified across COVID-19 patients with different clinical characteristics and disease severities. The ΔCt% is a clinical characteristic- and host immune status-independent indicator for COVID-19 progression prediction (AUC = 0.79, 95 % CI = 0.76 to 0.81), which outperformed the canonical blood test markers, including c-reactive protein (AUC = 0.57, 95 % CI = 0.53 to 0.61), serum amyloid A (AUC = 0.61, 95 % CI = 0.54 to 0.68), lactate dehydrogenase (AUC = 0.61, 95 % CI = 0.56 to 0.67), d-dimer (AUC = 0.56, 95 % CI = 0.46 to 0.66), and lymphocyte count (AUC = 0.62, 95 % CI = 0.58 to 0.66). Patients with persistent high SARS-CoV-2 viral load (an increase of mean Ct value < 50 %) during the first 3 days of hospitalization demonstrated a significantly unfavorable survival (HR = 0.16, 95 % CI = 0.04 to 0.65, P = 2.41 × 10-3). CONCLUSIONS: Viral nucleic acid dynamics of SARS-CoV-2 eliminates the inter-patient variance of basic health conditions and therefore, can serve as a prognostic marker for COVID-19.

Impact of the Digital Transformation of Small- and Medium-Sized Listed Companies on Performance: Based on a Cost-Benefit Analysis Framework

The ultimate goals of digital transformation, which is the only means of realizing the sustainable development of current enterprises, are to achieve cost reduction, efficiency improvement, and innovation for enterprises. However, there are limited empirical quantitative studies on the investment costs and impact of organizational performance related to the digital transformation of small- and medium-sized listed companies. This study first uses Excel VBA to sort the digital transformation panel data of 319 small- and medium-sized listed companies in China’s Shanghai and Shenzhen A-share markets from 2007 to 2020. Thereafter, Stata, a general-purpose statistical software package, is used to analyze the impact of digital transformation on the performance of small- and medium-sized listed companies. The results show that the digital transformation of small- and medium-sized listed companies has a positive correlation with operational performance, and an inverted U-shaped relationship with innovation performance;however, the U-shaped relationship with financial performance is not significant. For small- and medium-sized listed companies to promote digital transformation, first, it must help the organization to improve its internal operational efficiency;second, it can optimize and improve the organization’s financial efficiency;and finally, through innovative efficiency, the organization can continue to develop steadily and improve its organizational resilience.

Research on the Relationship between Digital Transformation and Performance of SMEs

Objective: Through an empirical analysis of the performance of SMEs undergoing digital transformation, this study attempts to identify the influencing factors that determine their sustainable development to provide reference for academic researchers and industrial decision makers. Method: This study first uses an interview method to investigate the impact of SMEs’ three main resources on digital transformation: digital technology, employee digital skills, and digital transformation strategy. Second, we assess the impact of digital transformation on financial performance. Using the structural equation model, 335 valid questionnaires were recovered through the questionnaire method, and the key factors were identified using SPSS and SPSSAU tools. Results: In the Chinese context, digital transformation affects SME performance, and the three resources mentioned above are positively correlated with SMEs’ digital transformation. Digital transformation is positively correlated with performance, and it is the mediator of the impact of digital transformation strategies on performance. Conclusion: For SMEs, focusing on investing in digital technologies, employee digital skills, and digital transformation strategies are three key factors that are beneficial for digital transformation, thus helping to improve performance and maintain their sustainable development.