The Clinical Course and Outcomes of Patients Hospitalized Due to COVID-19 during Three Pandemic Waves in Poland: A Single Center Observational Study

Cardiovascular complications in the course of COVID-19 - lessons learned and implications for the future care of patients with viral respiratory diseases: Data from a single center retrospective observational study

BACKGROUND

Factors associated with cardiovascular complications of COVID-19 remain understudied.

OBJECTIVES

Here we investigate the occurrence and risk factors of arrythmias, myocardial infarction and/or stroke, and thromboembolism in the course of COVID-19.

METHODS

We have performed an observational study with prospectively designed data collection. Data of patients diagnosed with COVID-19 who were admitted from March 6th 2020 to November 30th 2021 in our Hospital were analyzed. Logistic regression was used to identify variables associated with the odds of early hospital death due to COVID-19.

RESULTS

Fourteen-point three percent of 1964 patients had cardiovascular complications, 6.36 % arrhythmias, 5.5 % thromboembolic events and 2.39 % myocardial infarction and/or stroke. Factors independently increasing the odds of arrhythmia were older age (OR=1.49 [95 % CI: 1.17-1.92], p = 0.02), longer time between admission and the first onset of symptoms (1.02 [0.99-1.05], p = 0.049), concomitant atrial fibrillation/flutter (2.84 [1.37-5.70], p = 0.004), nicotinism (2.49 [1.37-4.49], p = 0.002), and eGFR<60 ml/min/1.73m2 (2.44 [1.08-5.59], p = 0.033). Factors independently increasing the odds of myocardial infarction and/or stroke were dementia (4.55 [0.97-19.3], p = 0.044), hemiplegia (12.67 [3.12-46.1], p < 0.001), nicotinism (3.36 [1.30-10.4], p = 0.013) and higher C-reactive protein concentration (1.01 [1.00-1.01], p = 0.040). Factors independently increasing the odds of thromboembolic events were longer hospitalization (1.08 [1.05-1.10], p < 0.001) and higher d-dimers (1.04 [1.02-1.05], <0.001).

CONCLUSIONS

The risk of cardiovascular complications was especially pronounced in patients with older age, pre-existing cardiovascular disease and more sever pneumonia at presentation to care. This underlines the importance of close and careful clinical follow-up in the course of COVID-19 for specific patients' populations, including a pro-active approach in diagnosis.

Immunological and Clinical Responses to Vaccinations among Adults Living with HIV

People living with human immunodeficiency virus (HIV) are at higher risk of morbidity and mortality due to vaccine-preventable diseases. At the same time, they are less likely to respond to vaccinations, and might have a higher rate of vaccine adverse event and faster waning of protective effect. International and national guidelines emphasize the importance of vaccinating people living with HIV against respiratory system disease pathogens including seasonal influenza, Streptococcus pneumoniae, and COVID-19, as well as against sexually transmitted infections, i.e., Hepatitis A and B (HAV, HBV) and human papillomavirus (HPV). This narrative review aims to provide a comprehensive examination of the current knowledge regarding the immune and clinical responses elicited by vaccinations in the older adult population living with HIV.

Evolving Clinical Manifestations and Outcomes in COVID-19 Patients: A Comparative Analysis of SARS-CoV-2 Variant Waves in a Romanian Hospital Setting

The aim of this study was to evaluate differences in the clinical manifestations and outcomes in hospitalized patients with COVID-19 in a single Romanian center during four pandemic waves determined by different SARS-CoV-2 variants of concern (VOCs). A retrospective study on 9049 consecutive hospitalized adult patients was performed between 27 February 2020 and 31 March 2023. The study interval was divided into waves based on national data on SARS-CoV-2 VOCs' circulation. Multivariate logistic regression models were built, predicting death and complications as functions of comorbidities, therapy, wave, severity form, and vaccination status, and adjusted for ages ≥65 years. Pulmonary (pneumothorax/pneumomediastinum, pulmonary embolism) and extrapulmonary complications (liver injury, acute kidney injury, ischemic/hemorrhagic stroke, myocardial infarction, and gastrointestinal bleeding) were present, more frequently in ICU hospitalized patients and with differences between waves. The highest in-hospital mortality was found in patients presenting pneumothorax/pneumomediastinum. All of the evaluated risk factors were significantly associated with death, except for obesity and the Omicron wave. Our study highlights the changing nature of COVID-19 and acknowledges the impacts of viral mutations on disease outcomes. For all four waves, COVID-19 was a severe disease with a high risk of poor outcomes.

Validity of prognostic models of critical COVID-19 is variable. A systematic review with external validation

OBJECTIVES

To identify prognostic models which estimate the risk of critical COVID-19 in hospitalized patients and to assess their validation properties.

STUDY DESIGN AND SETTING

We conducted a systematic review in Medline (up to January 2021) of studies developing or updating a model that estimated the risk of critical COVID-19, defined as death, admission to intensive care unit, and/or use of mechanical ventilation during admission. Models were validated in two datasets with different backgrounds (HM [private Spanish hospital network], n = 1,753, and ICS [public Catalan health system], n = 1,104), by assessing discrimination (area under the curve [AUC]) and calibration (plots).

RESULTS

We validated 18 prognostic models. Discrimination was good in nine of them (AUCs ≥ 80%) and higher in those predicting mortality (AUCs 65%-87%) than those predicting intensive care unit admission or a composite outcome (AUCs 53%-78%). Calibration was poor in all models providing outcome's probabilities and good in four models providing a point-based score. These four models used mortality as outcome and included age, oxygen saturation, and C-reactive protein among their predictors.

CONCLUSION

The validity of models predicting critical COVID-19 by using only routinely collected predictors is variable. Four models showed good discrimination and calibration when externally validated and are recommended for their use.

Identifying key genes related to inflammasome in severe COVID-19 patients based on a joint model with random forest and artificial neural network

Background

The coronavirus disease 2019 (COVID-19) has been spreading astonishingly and caused catastrophic losses worldwide. The high mortality of severe COVID-19 patients is an serious problem that needs to be solved urgently. However, the biomarkers and fundamental pathological mechanisms of severe COVID-19 are poorly understood. The aims of this study was to explore key genes related to inflammasome in severe COVID-19 and their potential molecular mechanisms using random forest and artificial neural network modeling.

Methods

Differentially expressed genes (DEGs) in severe COVID-19 were screened from GSE151764 and GSE183533 via comprehensive transcriptome Meta-analysis. Protein-protein interaction (PPI) networks and functional analyses were conducted to identify molecular mechanisms related to DEGs or DEGs associated with inflammasome (IADEGs), respectively. Five the most important IADEGs in severe COVID-19 were explored using random forest. Then, we put these five IADEGs into an artificial neural network to construct a novel diagnostic model for severe COVID-19 and verified its diagnostic efficacy in GSE205099.

Results

Using combining P value < 0.05, we obtained 192 DEGs, 40 of which are IADEGs. The GO enrichment analysis results indicated that 192 DEGs were mainly involved in T cell activation, MHC protein complex and immune receptor activity. The KEGG enrichment analysis results indicated that 192 GEGs were mainly involved in Th17 cell differentiation, IL-17 signaling pathway, mTOR signaling pathway and NOD-like receptor signaling pathway. In addition, the top GO terms of 40 IADEGs were involved in T cell activation, immune response-activating signal transduction, external side of plasma membrane and phosphatase binding. The KEGG enrichment analysis results indicated that IADEGs were mainly involved in FoxO signaling pathway, Toll-like receptor, JAK-STAT signaling pathway and Apoptosis. Then, five important IADEGs (AXL, MKI67, CDKN3, BCL2 and PTGS2) for severe COVID-19 were screened by random forest analysis. By building an artificial neural network model, we found that the AUC values of 5 important IADEGs were 0.972 and 0.844 in the train group (GSE151764 and GSE183533) and test group (GSE205099), respectively.

Conclusion

The five genes related to inflammasome, including AXL, MKI67, CDKN3, BCL2 and PTGS2, are important for severe COVID-19 patients, and these molecules are related to the activation of NLRP3 inflammasome. Furthermore, AXL, MKI67, CDKN3, BCL2 and PTGS2 as a marker combination could be used as potential markers to identify severe COVID-19 patients.