Background: COVID-19-associated coagulopathy (CAC) exacerbates the course of coronavirus infection and contributes to increased mortality. Current recommendations for CAC treatment include the use of low-molecular weight heparins (LMWH) at prophylactic or therapeutic doses, as well as the use of unfractionated heparin (UFH). Methods: A randomised, controlled trial enrolled 126 patients hospitalised in the intensive care unit with severe COVID-19 complicated by CAC. The effects of LMWH at preventive and therapeutic doses and UFH at therapeutic doses on mortality and intubation rates were compared. Results: The number of intubations and deaths showed no significant difference depending on the anticoagulant therapy used. However, multivariate logistic regression models revealed an increased risk of intubation (p = 0.026, odds ratio (OR) = 3.33, 95% confidence interval (CI) 1.15–9.59), and an increased risk of death (p = 0.046, OR = 3.01, 95% CI 1.02–8.90), for patients treated with LMWH at a prophylactic dose but not at a therapeutic dose as compared to patients treated with UFH when controlling for other risk factors. Conclusions: The use of unfractionated heparin in the treatment of COVID-19-associated coagulopathy seems to be more effective at reducing the risk of intubation and death than enoxaparin at prophylactic doses.

To investigate the use of oxygen metabolism markers as predictors of mortality in patients with severe coronavirus disease 2019 (COVID-19). A retrospective analysis was undertaken to compare the medical records of patients with severe COVID-19 (53 deceased patients and 50 survivors). The survivors were selected from 222 records using a random number generator. In addition, 28 individuals who considered themselves to be healthy and who had no history of serious illness were included in the study for comparison. Oxygen saturation in arterial blood, oxygen saturation in central venous blood (ScvO2), arterial partial pressure of oxygen (PaO2), respiratory index (PaO2/fraction of inspired oxygen), oxygen delivery, oxygen consumption (VO2) and oxygen extraction (O2ER) were compared in all participants. The optimal cut-off point for each oxygen metabolism marker in the prediction of mortality was determined based on the maximum value of the Youden Index in receiver operating characteristic curve analysis. Significant differences in all studied oxygen metabolism markers were found between survivors compared with deceased patients (p < 0.001). ScvO2, VO2 and O2ER [area under curve (AUC) 1.0] were the strongest predictors of mortality, and PaO2 was the weakest predictor of mortality (AUC 0.81). ScvO2 124.6 ml/min and O2ER >30.2% were identified as predictors of mortality in patients with COVID-19. ScvO2, VO2 and O2ER are good predictors of mortality in critically ill patients with COVID-19.

Tocilizumab (TOC) is presumed to be an effective and safe treatment for severe COVID-19, but its usefulness has not been yet investigated for different SARS-CoV-2 variants. This study aimed to evaluate the influence of TOC on mortality in patients with severe COVID-19 caused by Delta and non-Delta SARS-CoV-2 variants. In a retrospective analysis, we compared the medical records of 78 and 224 patients with severe COVID-19 due to Delta and non-Delta variants, respectively. A total of 30 patients with Delta and 84 with non-Delta variants were treated with TOC in addition to standard therapy. There were no statistically significant differences in mortality rate when comparing Delta vs. non-Delta patients nor when comparing those treated with TOC vs. not treated with TOC in both variants. Using a logistic regression model, in the examined population as a whole, we found an increased (p < 0.05) risk of death as leukocyte and erythrocyte counts decreased and as procalcitonin increased. Increased procalcitonin was significant for mortality in the Delta group, while decreased IL-6, leukocytes, and platelets and increased fibrinogen and procalcitonin were significant in the non-Delta group. Tocilizumab efficacy in severe COVID-19 does not differ between Delta or non-Delta virus variants. The Delta variant of SARS-CoV-2 does not increase mortality when compared to other virus strains.

Pulmonary arterial hypertension (PAH) is common in severe coronavirus disease 2019 (COVID-19) and worsens the prognosis. Sildenafil, a phosphodiesterase-5 inhibitor, is approved for PAH treatment but little is known about its efficacy in cases of severe COVID-19 with PAH. This study aimed to investigate the clinical efficacy of sildenafil in patients with severe COVID-19 and PAH. Intensive care unit (ICU) patients were randomly assigned to receive sildenafil or a placebo, with 75 participants in each group. Sildenafil was administered orally at 0.25 mg/kg t.i.d. for one week in a placebo-controlled, double-blind manner as an add-on therapy alongside the patient’s routine treatment. The primary endpoint was one-week mortality, and the secondary endpoints were the one-week intubation rate and duration of ICU stay. The mortality rate was 4% vs. 13.3% (p = 0.078), the intubation rate was 8% and 18.7% (p = 0.09), and the length of ICU stay was 15 vs. 19 days (p < 0.001) for the sildenafil and placebo groups, respectively. If adjusted for PAH, sildenafil treatment significantly reduced mortality and intubation risks: OR = 0.21 (95% CI: 0.05–0.89) and OR = 0.26 (95% CI: 0.08–0.86), respectively. Sildenafil demonstrated some clinical efficacy in patients with severe COVID-19 and PAH and should be considered as an add-on therapy in these patients.

Background: Severe traumatic brain injury (sTBI) in adults remains a leading cause of mortality and disability worldwide. Early identification of reliable predictors of outcome is crucial for risk stratification and ICU management. Disturbances of hemostasis and metabolic factors such as body mass index (BMI) have been proposed as potential prognostic markers, but evidence remains limited. Methods: We conducted a retrospective, multicenter study including 307 adult patients with sTBI (Glasgow Coma Scale ≤ 8) admitted to three tertiary intensive care units in Ukraine between September 2023 and July 2024. All patients underwent surgical evacuation of hematomas and decompressive craniotomy. Laboratory parameters (APTT, INR, fibrinogen, platelets, D-dimer) were collected within 12 h of admission. BMI was calculated from measured height and weight. Predictive modeling was performed using L1-regularized logistic regression and Random Forest algorithms. Class imbalance was addressed with SMOTE. Model performance was assessed by AUC, accuracy, calibration, and feature importance. Results: The 28-day all-cause mortality was 32.9%. Compared with survivors, non-survivors had significantly lower GCS scores and higher INR, D-dimer, and APTT values. Very high VIF values indicated severe multicollinearity between predictors. Classical logistic regression was not estimable due to perfect separation; therefore, regularized logistic regression and Random Forest were applied. Random Forest demonstrated higher performance (AUC 0.95, accuracy ≈ 90%) than logistic regression (AUC 0.77, accuracy 70.1%), although results must be interpreted cautiously given the small sample size and potential overfitting. Feature importance analysis identified increased BMI, prolonged APTT, and elevated D-dimer as leading predictors of mortality. Sensitivity analysis excluding BMI still yielded strong performance (AUC 0.91), confirming the prognostic value of coagulation markers and GCS. Conclusions: Mortality in adult sTBI patients was strongly associated with impaired hemostasis, obesity, and low neurological status at admission. Machine learning-based modeling demonstrated promising predictive accuracy but is exploratory in nature. Findings should be interpreted with caution due to retrospective design, severe multicollinearity, potential overfitting, and absence of external validation. Larger, prospective, multicenter studies are needed to confirm these results and improve early risk stratification in severe TBI.

Background: Cytokine storm in COVID-19 is heterogenous. There are at least three subtypes: cytokine release syndrome (CRS), macrophage activation syndrome (MAS), and sepsis. Methods: A retrospective study comprising 276 patients with SARS-CoV-2 pneumonia. All patients were tested for ferritin, interleukin-6, D-Dimer, fibrinogen, calcitonin, and C-reactive protein. According to the diagnostic criteria, three groups of patients with different subtypes of cytokine storm syndrome were identified: MAS, CRS or sepsis. In the MAS and CRS groups, treatment results were assessed depending on whether or not tocilizumab was used. Results: MAS was diagnosed in 9.1% of the patients examined, CRS in 81.8%, and sepsis in 9.1%. Median serum ferritin in patients with MAS was significantly higher (5894 vs. 984 vs. 957 ng/mL, p < 0.001) than in those with CRS or sepsis. Hypofibrinogenemia and pancytopenia were also observed in MAS patients. In CRS patients, a higher mortality rate was observed among those who received tocilizumab, 21 vs. 10 patients (p = 0.043), RR = 2.1 (95% CI 1.0–4.3). In MAS patients, tocilizumab decreased the mortality, 13 vs. 6 patients (p = 0.013), RR = 0.50 (95% CI 0.25–0.99). Conclusions: Tocilizumab therapy in patients with COVID-19 and CRS was associated with increased mortality, while in MAS patients, it contributed to reduced mortality.