Risk Factors for Pulmonary Embolism in Individuals Infected with SARS-CoV2-A Single-Centre Retrospective Study

The emergence of SARS-CoV2 has presented itself as a significant global health crisis. The prevalence of thrombotic events is known to be high in these patients, affecting various organ systems, sometimes leading to cutaneous thrombosis, pulmonary embolism (PE), stroke, or coronary thrombosis. The available evidence suggests that thromboembolism, hypercoagulability, and the excessive production of proinflammatory cytokines play a significant role in the development of multiorgan failure. Methodology: This retrospective single-centre study was conducted at "Victor Babes" University of Medicine and Pharmacy from Timisoara, Romania, involving a total of 420 patients diagnosed with COVID-19. We separated them into a CONTROL group that included 319 patients, and an intervention group (PE) with 101 patients that, subsequent to infection with the virus, developed pulmonary embolism. The study included the reporting of demographic data, laboratory findings, and comorbidities. Results: Out of a total of 420 patients, 24% experienced pulmonary embolism, while 21.42% died. Arterial thrombotic events were found to be associated with factors such as age, cardiovascular disease, levels of white blood cells, D-dimers, and albumin in the blood. The findings of the study indicate that there is an independent association between pulmonary thrombosis and hypertension (odds ratio (OR): 1.1; 95% confidence interval (CI): 0.7 to 1.7; p = 0.6463), cancer (OR: 1.1; 95% CI: 0.6 to 2.3; p = 0.6014), and COPD (OR: 1.2; 95% CI: 0.6 to 2.3; p = 0.4927). On the other hand, there is a stronger correlation between PE and obesity (OR: 2.8; 95% CI: 1.7 to 4.6; p < 0.0001), diabetes (OR: 3.3; 95% CI: 2 to 5.3; p < 0.0001), and dyslipidemia (OR: 3.6; 95% CI: 2.3 to 5.8; p < 0.0001) in a multivariable regression logistic model. Conclusions: Patients diagnosed with severe forms of COVID-19 display a comparable incidence of arterial thrombotic events, which have been linked to poor survival rates.

Developing Prediction Models for COVID-19 Outcomes: A Valuable Tool for Resource-Limited Hospitals

Purpose

Coronavirus disease is a global pandemic with millions of confirmed cases and hundreds of thousands of deaths worldwide that continues to create a significant burden on the healthcare systems. The aim of this study was to determine the patient clinical and paraclinical profiles that associate with COVID-19 unfavourable outcome and generate a prediction model that could separate between high-risk and low-risk groups.

Patients and Methods

The present study is a multivariate observational retrospective study. A total of 483 patients, residents of the municipality of Timișoara, the biggest city in the Western Region of Romania, were included in the study group that was further divided into 3 sub-groups in accordance with the disease severity form.

Results

Increased age (cOR=1.09, 95% CI: 1.06-1.11, p<0.001), cardiovascular diseases (cOR=3.37, 95% CI: 1.96-6.08, p<0.001), renal disease (cOR=4.26, 95% CI: 2.13-8.52, p<0.001), and neurological disorder (cOR=5.46, 95% CI: 2.71-11.01, p<0.001) were all independently significantly correlated with an unfavourable outcome in the study group. The severe form increases the risk of an unfavourable outcome 19.59 times (95% CI: 11.57-34.10, p<0.001), while older age remains an independent risk factor even when disease severity is included in the statistical model. An unfavourable outcome was positively associated with increased values for the following paraclinical parameters: white blood count (WBC; cOR=1.10, 95% CI: 1.05-1.15, p<0.001), absolute neutrophil count (ANC; cOR=1.15, 95% CI: 1.09-1.21, p<0.001) and C-reactive protein (CRP; cOR=1.007, 95% CI: 1.004-1.009, p<0.001). The best prediction model including age, ANC and CRP achieved a receiver operating characteristic (ROC) curve with the area under the curve (AUC) = 0.845 (95% CI: 0.813-0.877, p<0.001); cut-off value = 0.12; sensitivity = 72.3%; specificity = 83.9%.

Conclusion

This model and risk profiling may contribute to a more precise allocation of limited healthcare resources in a clinical setup and can guide the development of strategies for disease management.

Bacterial and Fungal Superinfections in COVID-19 Patients Hospitalized in an Intensive Care Unit from Timișoara, Romania

PURPOSE

Critically ill patients hospitalized in the intensive care unit (ICU) have an increased infection risk. The aim of this study was to determine the bacterial and fungal superinfections rate in Coronavirus disease 2019 (COVID-19) patients stationed in the ICU, identify risk factors associated with their development and to determine whether superinfection plays a role in patients' outcome in this population.

PATIENTS AND METHODS

In this retrospective, non-interventional, single centre, cohort study, medical records of 302 consecutive patients with SARS-COV-2 pneumonia admitted into the COVID-19 ICU of the largest university hospital from Western Romania between October 2020 and May 2021, were reviewed, of whom 236 patients met the inclusion criteria.

RESULTS

One hundred and nineteen patients developed a superinfection ≥48 h after being admitted to the hospital. Superinfection rate in the ICU was 50.42%. Coagulase-negative Staphylococci (CoNS) and Enterococcus spp. were predominantly isolated from blood cultures, while Acinetobacter baumannii, Staphylococcus aureus and Candida spp. from tracheobronchial aspirates. Significant independent risk factors regarding bacterial/fungal superinfection in COVID-19 patients were obtained for the following variables: number of days of central venous catheter (HR = 1.13 [1.07-1.20], p < 0.001) and prior administration of corticosteroids (HR = 2.80 [1.33-5.93], p = 0.007). Four independent predictive risk factors were associated with unfavorable outcome: age (HR = 1.07 [95% CI 1.03-1.12], p = 0.001); Carmeli Score (HR = 6.09 [1.18-31.50], p = 0.031); body mass index (HR = 1.11 [1.02-1.21], p = 0.011) and the presence of a central venous catheter (HR = 6.49 [1.93-21.89], p = 0.003).

CONCLUSION

The superinfection rate in COVID-19 patients was high in this study group. Exogenous risk factors were associated with superinfection more than endogenous factors. Only a small percentage of uninfected COVID-19 patients were not prescribed antibiotics during their hospitalization, raising serious concerns regarding the judicious prescribing of antibiotics in viral infections.