Differential Characteristics of Patients for Hospitalized Severe COVID-19 Infected by the Omicron Variants and Wild Type of SARS-CoV-2 in China

Label-Free Quantitative Proteomics Analysis of COVID-19 Vaccines by Nano LC-HRMS

A nanoliter liquid chromatography-high resolution mass spectrometry-based method was developed for quantitative proteomics analysis of COVID-19 vaccines. It can be used for simultaneous qualitative and quantitative analysis of target proteins and host cell proteins (HCPs) in vaccine samples. This approach can directly provide protein information at the molecular level. Based on this, the proteomes of 15 batches of COVID-19 inactivated vaccine samples from two companies and 12 batches of COVID-19 recombinant protein vaccine samples from one company were successfully analyzed, which provided a significant amount of valuable information. Samples produced in different batches or by different companies can be systematically contrasted in this way, offering powerful supplements for existing quality standards. This strategy paves the way for profiling proteomics in complex samples and provides a novel perspective on the quality evaluation of bio-macromolecular drugs.

Difference in the impact of coinfections and secondary infections on antibiotic use in patients hospitalized with COVID-19 between the Omicron-dominant period and the pre-Omicron period

INTRODUCTION

This study evaluated the effect of coinfections and/or secondary infections on antibiotic use in patients hospitalized with coronavirus disease 2019 (COVID-19).

METHOD

Days of therapy per 100 bed days (DOT) in a COVID-19 ward were compared between 2022 (Omicron period) and 2021 (pre-Omicron period). Antibiotics were categorized as antibiotics predominantly used for community-acquired infections (CAIs) and antibiotics predominantly used for health care-associated infections (HAIs). Bacterial and/or fungal infections which were proved or assumed on admission were defined as coinfections. Secondary infections were defined as infections that occurred following COVID-19.

RESULTS

Patients with COVID-19 during the Omicron period were older and had more comorbidities. Coinfections were more common in the Omicron period than in the pre-Omicron period (44.4% [100/225] versus 0.8% [2/257], respectively, p < 0.001), and the mean DOT of antibiotics for CAIs was significantly increased in the Omicron period (from 3.60 to 17.84, p < 0.001). Secondary infection rate tended to be higher in the Omicron period (p = 0.097). Mean DOT of antibiotics for HAIs were appeared to be lower in the COVID-19 ward than in the general ward (pre-Omicron, 3.33 versus 6.37, respectively; Omicron, 3.84 versus 5.22, respectively). No multidrug-resistant gram-negative organisms were isolated in the COVID-19 ward.

CONCLUSION

Antibiotic use for CAIs was limited in the pre-Omicron period but increased in the Omicron period because of a high coinfection rate on admission. With the antimicrobial stewardship, excessive use of antibiotics for HAIs was avoided in the COVID-19 ward during both periods.

Assessing the Diagnostic Values of the Neutrophil-to-Lymphocyte Ratio (NLR) and Systematic Immunoinflammatory Index (SII) as Biomarkers in Predicting COVID-19 Severity: A Multicentre Comparative Study

COVID-19 has been notoriously unpredictable in its clinical course. Such unpredictability poses a challenge to clinicians in predicting patients who will develop severe cases and possibly die from the infection. This study aims to assess and compare the diagnostic value of the NLR and SII as biomarkers in predicting COVID-19 severity, represented by mortality, with a multicentre comparative study including 855 patients in Saudi Arabia. Descriptive and analytical statistics were used to compare haematological indices between survivors and non-survivors. The median age of patients included was 41 years old, with an almost equal ratio of men to women. Most participants were Saudis, and the mortality rate in the study cohort was 13.22%. Non-survivors, as compared to survivors, were significantly older, had lower RBC counts, haemoglobin and haematocrit levels, as well as significantly higher WBC and neutrophil counts. Both the NLR and SII were capable of differentiating between survivors and non-survivors, with the latter having significantly higher values. However, the NLR was superior to the SII in such differentiation, as it had a larger area under the curve. This study further confirms the diagnostic values of the NLR and SII as biomarkers in predicting COVID-19 severity and mortality, with the NLR being more sensitive and specific. Clinical guidelines on managing COVID-19 cases should benefit from these findings by harnessing the value of the NLR in COVID-19 management.

The Role of Neutrophil in COVID-19: Positive or Negative

BACKGROUND

Neutrophils are the first line of defense against pathogens. They are divided into multiple subpopulations during development and kill pathogens through various mechanisms. Neutrophils are considered one of the markers of severe COVID-19.

SUMMARY

In-depth research has revealed that neutrophil subpopulations have multiple complex functions. Different subsets of neutrophils play an important role in the progression of COVID-19.

KEY MESSAGES

In this review, we provide a detailed overview of the developmental processes of neutrophils at different stages and their recruitment and activation after SARS-CoV-2 infection, aiming to elucidate the changes in neutrophil subpopulations, characteristics, and functions after infection and provide a reference for mechanistic research on neutrophil subpopulations in the context of SARS-CoV-2 infection. In addition, we have also summarized research progress on potential targeted drugs for neutrophil immunotherapy, hoping to provide information that aids the development of therapeutic drugs for the clinical treatment of critically ill COVID-19 patients.

Developing a COVID-19 Mortality Prediction (CoMPred) Indicator for ICU Diabetic Patients Treated with Tocilizumab in Saudi Arabia: A Proof-of-Concept Study

Since the beginning of the COVID-19 pandemic, efforts have been made to underline its discourse and identify factors contributing to its severe forms. Clinically, many physicians depended on subjective criteria to determine its severe forms, which varied significantly between practices. However, they did not rely on objective laboratory findings. This study aimed to present a novel and objective laboratory-based indicator to predict mortality among COVID-19 patients. The study included 249 COVID-19 patients who were admitted to the ICU, of which 80 did not survive. The COVID-19 Mortality Prediction (CoMPred) indicator was developed by including the age and the following lab investigations: neutrophil-to-lymphocyte ratio (NLR), D-Dimer, PT, aPTT, ESR, CRP, and urea levels. A CoMPred score of 7.5 or higher carries a sensitivity of 81.10% in predicting mortality, i.e., a patient with a CoMPred score of 7.5 or higher has an 81.10% chance of dying. The CoMPred indicator score directly correlates with mortality, i.e., the higher the score, the higher the possibility of the patient dying. In conclusion, the CoMPred indicator is an objective tool that is affordable and widely available, will assist physicians, and limit the burden on clinical decisions on an unpredicted course of COVID-19 in patients.