Analysis of potential risk factors associated with COVID-19 and hospitalization

Lymphocyte B Subtypes in Peripheral Blood: A Prognostic Biomarker for COVID-19 Patients

BACKGROUND

In view of the scientific gap in knowledge of the involvement of the B-cell compartment and clinical prognostic in SARS-CoV-2 infection, this work aims to evaluate the B-cell subsets and the presence of specific IgM and IgG, as well as neutralizing antibodies against SARS-CoV-2, in unvaccinated patients diagnosed with COVID-19.

METHODS

This study included 133 patients with COVID-19. Cellular components were assessed by flow cytometry, and immunoglobulin levels and reactivity were measured by indirect enzyme-linked immunosorbent assay.

RESULTS

Our results showed no changes in less differentiated B cells. However, non-switched memory B cells (NS-MBCs) and class-switched memory B cells (CS-MBCs) were reduced in the patients with moderate disease. Also, plasmablasts and double-negative (DN) or "atypical" memory B cells were increased in groups of patients with moderate to critical conditions. In addition, the production of IgM, IgG, and neutralizing antibodies against SARS-CoV-2 demonstrated a positive correlation between the positivity of antibodies against SARS-CoV-2 and disease severity. Besides being related to the development of a more severe course of the disease, the increase in DN B-cell count also contributed to a poorer disease outcome in patients with a higher percentage of these cells. On the other hand, we observed an increase in the absolute number of CS-MBCs in patients with greater chances of survival.

CONCLUSIONS

This study demonstrates that the B-cell compartment may contribute to the development of clinical symptoms of COVID-19, with changes in B-cell subset counts linked to disease course and patient prognosis.

Personalized Assessment of Mortality Risk and Hospital Stay Duration in Hospitalized Patients with COVID-19 Treated with Remdesivir: A Machine Learning Approach

Background: Despite advancements in vaccination, early treatments, and understanding of SARS-CoV-2, its impact remains significant worldwide. Many patients require intensive care due to severe COVID-19. Remdesivir, a key treatment option among viral RNA polymerase inhibitors, lacks comprehensive studies on factors associated with its effectiveness. Methods: We conducted a retrospective study in 2022, analyzing data from 252 hospitalized COVID-19 patients treated with remdesivir. Six machine learning algorithms were compared to predict factors influencing remdesivir's clinical benefits regarding mortality and hospital stay. Results: The extreme gradient boost (XGB) method showed the highest accuracy for both mortality (95.45%) and hospital stay (94.24%). Factors associated with worse outcomes in terms of mortality included limitations in life support, ventilatory support needs, lymphopenia, low albumin and hemoglobin levels, flu and/or coinfection, and cough. For hospital stay, factors included vaccine doses, lung density, pulmonary radiological status, comorbidities, oxygen therapy, troponin, lactate dehydrogenase levels, and asthenia. Conclusions: These findings underscore XGB's effectiveness in accurately categorizing COVID-19 patients undergoing remdesivir treatment.

Integration of individualized and population-level molecular epidemiology data to model COVID-19 outcomes

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with enhanced transmissibility and immune escape have emerged periodically throughout the coronavirus disease 2019 (COVID-19) pandemic, but the impact of these variants on disease severity has remained unclear. In this single-center, retrospective cohort study, we examined the association between SARS-CoV-2 clade and patient outcome over a two-year period in Chicago, Illinois. Between March 2020 and March 2022, 14,252 residual diagnostic specimens were collected from SARS-CoV-2-positive inpatients and outpatients alongside linked clinical and demographic metadata, of which 2,114 were processed for viral whole-genome sequencing. When controlling for patient demographics and vaccination status, several viral clades were associated with risk for hospitalization, but this association was negated by the inclusion of population-level confounders, including case count, sampling bias, and shifting standards of care. These data highlight the importance of integrating non-virological factors into disease severity and outcome models for the accurate assessment of patient risk.

Temporal trends in 90-day survival of hospitalised individuals during two years of the COVID-19 pandemic in Denmark

BACKGROUND

Mortality rates peaked early in the COVID-19 pandemic and then declined. Possible explanations are pharmacological and non-pharmacological treatments, vaccines and changing demographics. We sought to evaluate temporal trends in clinical characteristics and survival of patients hospitalised with COVID-19 during the first two years of the pandemic in Denmark.

METHODS

In this observational study, we included all adults with COVID-19 consecutively admitted to three hospitals in Copenhagen, Denmark, from March 2020 through March 2022. The primary outcome was overall survival up to day 90 from admission. We used multivariable Cox proportional hazards models to estimate the association of survival within five consecutive time-periods, based on admission date, adjusted for baseline characteristics, vaccination status, remdesivir and dexamethasone treatment.

RESULTS

In 1630 included patients, the median age [IQR] was 68 [52, 79] years, 56.6% were men and 86.2% had comorbidity. Clinical characteristics changed over time. The crude 90-day mortality rate peaked in March-June 2020 with 28.9%, decreased from July 2020 to 17.5%, and increased again in January-March 2022 to 28.6%. Lower hazard ratios for death were observed in individuals admitted from July 2020 and persisted after adjusting for baseline characteristics. Adjusting for vaccination, remdesivir treatment and dexamethasone treatment attenuated the association in patients requiring low-flow oxygen.

CONCLUSIONS

Our study suggests lower hazard rates for mortality in patients hospitalised with COVID-19 from July 2020 compared to March-June 2020, mainly driven by lower mortality in patients with a need of oxygen at baseline.

Association of Serum Potassium Variability With 60-day Mortality and Cardiovascular Events after COVID-19 Infection in Maintenance Hemodialysis Patients

Objective: This study aimed to investigate the association between serum potassium variability and 60-day mortality and cardiovascular disease (CVD) in maintenance hemodialysis (MHD) patients following the coronavirus disease 2019 (COVID-19) infection. Methods: We conducted a retrospective study on MHD patients treated at the affiliated hospital of Qingdao University hemodialysis center who were infected with the novel coronavirus between December 1, 2022, and January 31, 2023. Baseline characteristics of patients were collected from electronic medical records. Kaplan-Meier survival analysis was used to obtain patient survival probabilities, and multivariate Cox hazard regression models and binary Logistic regression models were used to obtain hazard ratios (HR), odds ratios (OR), and 95% confidence intervals (95% CI) between exposure and outcomes. Results: A total of 296 patients were included in this study, with a mean age of 57.2±16.3 years, and 59.8% were male. The 60-day mortality rate was 10.8%, and the incidence of CVD was 32.8%. Kaplan-Meier curves showed that a higher potassium variability coefficient was associated with higher all-cause mortality (P = 0.024). After adjusting for potential confounders, multivariate Cox regression analysis showed that the HR for 60-day mortality in the Q4 group compared to the Q1 group was 2.06 (95% CI = 1.03-4.09, P = 0.040), and binary Logistic regression analysis showed that the OR for 60-day CVD in the Q4 group compared to the Q1 group was 4.09 (95% CI = 1.52-10.97, P = 0.005). Conclusion: Increased serum potassium variability in MHD patients after COVID-19 infection significantly increased the likelihood of 60-day mortality and CVD.

COVID-19 vaccination for children with pulmonary hypertension: efficacy, safety and reasons for opting against vaccination

Objective

To determine the reasons why pulmonary hypertension (PH) children refused vaccination against COVID-19, evaluate the safety and efficacy of COVID-19 vaccine in PH children.

Study design

This retrospective cohort study included congenital heart disease-associated pulmonary arterial hypertension (CHD-PAH) and bronchopulmonary dysplasia associated PH (BPD-PH) children who were divided into vaccinated group and non-vaccinated group. Univariate logistic regression analysis and multivariate logistic regression analysis were conducted to explore the reasons why PH children refused COVID-19 vaccine. Then, the prevalence, the number of symptoms, and the severity of COVID-19 disease were compared between the vaccinated and unvaccinated groups.

Result

We included 73 children and 61 children (83.6%) were unvaccinated. The main reasons for not being vaccinated were fear of worsening of existing diseases (31%). Age < 36 months (RR: 0.012; P < 0.001) and the presence of comorbidities (RR = 0.06; P = 0.023) were risk factors influencing willingness to vaccinate. The most common adverse events (AEs) were injection site pain (29.6%). COVID-19 vaccines are safe for PH children. The prevalence of COVID-19 disease decreased in PH children after vaccination (RR = 0.51; P = 0.009). 1 month after negative nucleic acid test or negative antigen test, PH children in the vaccinated group had fewer symptoms (P = 0.049).

Conclusions

The vaccination rate of COVID-19 vaccine is low in CHD-PAH and BPD-PH children while COVID-19 vaccines are safe. Vaccination can reduce the prevalence of COVID-19 disease and the number of symptoms 1 month after negative nucleic acid or antigen tests.

Were metabolic and other chronic diseases the driven onset epidemic forces of COVID-19 in Mexico?

The underline hypothesis of this study was that SARS-CoV-2 can infect individuals regardless of health condition, sex, and age in opposition to the classical epidemiological assumption of an identifiable susceptible subpopulation for epidemic development. To address this issue, a population cohort with 24.4 million metadata associated with 226,089 official RT-qPCR positive and 283,450 negative cases, including 27,769 deceased, linked putatively to B.1. and B.1.1. SARS-CoV-2 lineages were analyzed. The analysis baseline was to determine the infection and mortality structure of the diseased cohort at the onset-exponential phase of the first epidemic wave in Mexico under the assumption of limited herd immunity. Individuals with nonchronic diseases (NOCDs) were compared with those exhibiting at least one of 10 chronic diseases (CDs) adjusted by age and sex. Risk factors for infection and mortality were estimated with classification and regression tree (CART) and cluster analysis based on Spearman's matrix of rho-values in RStudio®, complemented with two proposed mortality indices. SARS-CoV-2 infection was independent of health condition (52.8% NOCD vs. 47.2% CDs; p = 0.001-0.009) but influenced by age >46 in one risk analysis scenario (p < 0.001). Sex contributed 9.7% to the overall risk. The independent effect was supported by the health structure of negative cases with a similar tendency but a higher proportion of NOCDs (61.4%, p = 0.007). The infection probability in individuals with one CD was determined by the disease type and age, which was higher in those older individuals (≥56 years) exhibiting diabetes (12.3%, cp = 0.0006), hypertension (10.1%, cp < 0.0001), and obesity (7.8%, cp = 0.001). In contrast, the mortality risk was heavily influenced by CD conditioned by sex and age, accounting for 72.3% of total deaths (p = 0.001-0.008). Significant mortality risk (48%) was comprised of women and men (w, m) aged ≥56 years with diabetes (19% w and 27.9% m, cp < 0.0004), hypertension (11.5% w, cp = 0.0001), and CKD (3.5% w and 5.3% m, cp = 0.0009). Older people with diabetes and hypertension comorbidity increased the risk to 60.5% (p = 0.001). Based on a mortality-weighted index, women were more vulnerable to preexisting metabolic or cardiovascular diseases. These findings support our hypothesis and justify the need for surveillance systems at a communitarian level. This is the first study addressing this fundamental epidemiological question.