Effect of tocilizumab treatment in mildly-obese patients with coronavirus disease 2019: a case series

Changes in Clinical Features and Severity of COVID-19 with the Emergence of Omicron Variants: A Shift Towards a Common Disease

Background

The emergence of the Omicron variant of severe acute respiratory syndrome coronavirus-2 has significantly altered the clinical features and severity of coronavirus disease 2019 (COVID-19).

Objective

This study aims to evaluate whether the clinical factors that previously predicted COVID-19 remain valid following the emergence of the Omicron variant.

Methods

This cross-sectional study was conducted at Showa University Fujigaoka Hospital from April 2022 to March 2023. A total of 576 patients with suspected COVID-19 were included, of which 258 (44.8%) were diagnosed with COVID-19 based on real-time reverse-transcription polymerase chain reaction tests. Clinical data were collected retrospectively, and multivariate logistic regression was used to analyze factors associated with a COVID-19 diagnosis.

Results

Of the 258 patients diagnosed with COVID-19, 60% had mild disease, and the overall severity was lower than in previous reports prior to the emergence of the Omicron variant. In the multivariate analysis, only C-reactive protein (CRP) levels were significantly associated with COVID-19 (odds ratio, 0.3164; 95% confidence interval, 0.2077-0.4819), while factors such as age, sex, body mass index, lactate dehydrogenase, and comorbidities were not significantly associated. Non-COVID-19 cases were primarily bacterial infections, accounting for 57.2% of the non-COVID-19 diagnoses. Mortality rates did not differ significantly between the COVID-19 and non-COVID-19 groups.

Conclusion

The clinical characteristics of COVID-19 have become less distinct since the emergence of the Omicron variant, with CRP being the primary marker associated with a COVID-19 diagnosis. As COVID-19 continues to transition towards a more common infectious disease, distinguishing it will become increasingly challenging.

Combination of rRT-PCR and Clinical Features to Predict Coronavirus Disease 2019 for Nosocomial Infection Control

Background

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), immediately became a pandemic. Therefore, nosocomial infection control is necessary to screen for patients with possible COVID-19.

Objective

This study aimed to investigate commonly measured clinical variables to predict COVID-19.

Methods

This cross-sectional study enrolled 1087 patients in the isolation ward of a university hospital. Conferences were organized to differentiate COVID-19 from non-COVID-19 cases, and multiple nucleic acid tests were mandatory when COVID-19 could not be excluded. Multivariate logistic regression models were employed to determine the clinical factors associated with COVID-19 at the time of hospitalization.

Results

Overall, 352 (32.4%) patients were diagnosed with COVID-19. The majority of the non-COVID-19 cases were predominantly caused by bacterial infections. Multivariate analysis indicated that COVID-19 was significantly associated with age, sex, body mass index, lactate dehydrogenase, C-reactive protein, and malignancy.

Conclusion

Some clinical factors are useful to predict patients with COVID-19 among those with symptoms similar to COVID-19. This study suggests that at least two real-time reverse-transcription polymerase chain reactions of SARS-CoV-2 are recommended to exclude COVID-19.