Plasma and Cellular Forms of Fibronectin as Prognostic Markers in Sepsis

Background. There is a pressing need for specific prognostic markers that could be used to monitor the severity of sepsis. The aims of our study were to investigate changes in the expression of different molecular forms of fibronectin in sepsis and to assess their relationship to the clinical severity and mortality of patients. Material and Methods. Forms of fibronectin: plasma (pFN), cellular (EDA-FN), FN-fibrin complexes, and fibronectin fragments were analyzed in 71 sepsis patients (survivors and nonsurvivors) and in the control by ELISA and immunoblotting. Results. The baseline pFN concentration of patients with sepsis was significantly lower than in the control (133.0 mg/L vs. 231.2 mg/L) (P<0.001), and in nonsurvivors, it was lower than in survivors (106.0 mg/L vs. 152.8 mg/L) (P=0.004). The baseline EDA-FN was significantly elevated in both sepsis groups (survivors: 6.7 mg/L; nonsurvivors: 9.4 mg/L) compared to the control (1.4 mg/L) (P<0.001). It should be noted that among patients with more severe sepsis, the EDA-FN level was higher in nonsurvivors than in survivors. Furthermore, molecular FN-fibrin complexes as well as FN fragments occurred much more frequently in nonsurvivors than in survivors. Conclusion. The study showed that in sepsis, changes in plasmatic and cellular form of fibronectin were associated with the severity of sepsis and may be useful predictors of outcome

Porównanie zużycia gazów anestetycznych oraz stabilności znieczulenia przy użyciu automatycznej i ręcznej kontroli przebiegu znieczulenia

BACKGROUND: The automatic control module of end-tidal volatile agents (EtC) was designed to reduce the consumption of anaesthetic gases, increase the stability of general anaesthesia and reduce the need for adjustments in the settings of the anaesthesia machine. The aim of this study was to verify these hypotheses. METHODS: The course of general anaesthesia with the use of the EtC module was analysed for haemodynamic stability, depth of anaesthesia, end-expiratory concentration of anaesthetic, number of ventilator key presses, fentanyl supply, consumption of volatile agents and anaesthesia and operation times. These data were compared with the data obtained during general anaesthesia controlled manually and were processed with statistical tests. RESULTS: Seventy-four patients underwent general anaesthesia for scheduled operations. Group AUTO-ET (n = 35) was anaesthetized with EtC, and group MANUAL-ET (n = 39) was controlled manually. Both populations presented similar anaesthesia stability. No differences were noted in the time of anaesthesia, saturation up to MAC 1.0 or awakening. Data revealed no differences in mean EtAA or the fentanyl dose. The AUTO-ET group exhibited fewer key presses per minute, 0.0603 min-1, whereas the MANUAL-ET exhibited a value of 0.0842 min-1; P = 0.001. The automatic group consumed more anaesthetic and oxygen per minute (sevoflurane 0.1171 mL min-1; IQR: 0.0503; oxygen 1.8286 mL min-1, IQR: 1,3751) than MANUAL-ET (sevoflurane 0.0824 mL min-1, IQR: 0.0305; oxygen 1,288 mL min-1, IQR: 0,6517) (P = 0.0028 and P = 0.0171, respectively). CONCLUSION: Both methods are equally stable and safe for patients. The consumption of volatile agents was significantly increased in the AUTO-ET group. EtC considerably reduces the number of key presses.  BACKGROUND: The automatic control module of end-tidal volatile agents (EtC) was designed to reduce the consumption of anaesthetic gases, increase the stability of general anaesthesia and reduce the need for adjustments in the settings of the anaesthesia machine. The aim of this study was to verify these hypotheses. METHODS: The course of general anaesthesia with the use of the EtC module was analysed for haemodynamic stability, depth of anaesthesia, end-expiratory concentration of anaesthetic, number of ventilator key presses, fentanyl supply, consumption of volatile agents and anaesthesia and operation times. These data were compared with the data obtained during general anaesthesia controlled manually and were processed with statistical tests. RESULTS: Seventy-four patients underwent general anaesthesia for scheduled operations. Group AUTO-ET (n = 35) was anaesthetized with EtC, and group MANUAL-ET (n = 39) was controlled manually. Both populations presented similar anaesthesia stability. No differences were noted in the time of anaesthesia, saturation up to MAC 1.0 or awakening. Data revealed no differences in mean EtAA or the fentanyl dose. The AUTO-ET group exhibited fewer key presses per minute, 0.0603 min-1, whereas the MANUAL-ET exhibited a value of 0.0842 min-1; P = 0.001. The automatic group consumed more anaesthetic and oxygen per minute (sevoflurane 0.1171 mL min-1; IQR: 0.0503; oxygen 1.8286 mL min-1, IQR: 1,3751) than MANUAL-ET (sevoflurane 0.0824 mL min-1, IQR: 0.0305; oxygen 1,288 mL min-1, IQR: 0,6517) (P = 0.0028 and P = 0.0171, respectively). CONCLUSION: Both methods are equally stable and safe for patients. The consumption of volatile agents was significantly increased in the AUTO-ET group. EtC considerably reduces the number of key presses.

Explainable Artificial Intelligence Helps in Understanding the Effect of Fibronectin on Survival of Sepsis

Fibronectin (FN) plays an essential role in the host&rsquo;s response to infection. In previous studies, a significant decrease in the FN level was observed in sepsis; however, it has not been clearly elucidated how this parameter affects the patient&rsquo;s survival. To better understand the relationship between FN and survival, we utilized innovative approaches from the field of explainable machine learning, including local explanations (Break Down, Shapley Additive Values, Ceteris Paribus), to understand the contribution of FN to predicting individual patient survival. The methodology provides new opportunities to personalize informative predictions for patients. The results showed that the most important indicators for predicting survival in sepsis were INR, FN, age, and the APACHE II score. ROC curve analysis showed that the model&rsquo;s successful classification rate was 0.92, its sensitivity was 0.92, its positive predictive value was 0.76, and its accuracy was 0.79. To illustrate these possibilities, we have developed and shared a web-based risk calculator for exploring individual patient risk. The web application can be continuously updated with new data in order to further improve the model

Immunosuppression as a Hallmark of Critical COVID-19: Prospective Study

The dysregulation of both the innate and adaptive responses to SARS-CoV-2 have an impact on the course of COVID-19, and play a role in the clinical outcome of the disease. Here, we performed a comprehensive analysis of peripheral blood lymphocyte subpopulations in 82 patients with COVID-19, including 31 patients with a critical course of the disease. In COVID-19 patients who required hospitalization we analyzed T cell subsets, including Treg cells, as well as TCRα/β and γ/δ, NK cells, and B cells, during the first two weeks after admission to hospital due to the SARS-CoV-2 infection, with marked reductions in leukocytes subpopulations, especially in critically ill COVID-19 patients. We showed decreased levels of Th, Ts cells, Treg cells (both naïve and induced), TCRα/β and γ/δ cells, as well as CD16+CD56+NK cells in ICU compared to non-ICU COVID-19 patients. We observed impaired function of T and NK cells in critically ill COVID-19 patients with extremely low levels of secreted cytokines. We found that the IL-2/INFγ ratio was the strongest indicator of a critical course of COVID-19, and was associated with fatal outcomes. Our findings showed markedly impaired innate and adaptive responses in critically ill COVID-19 patients, and suggest that the immunosuppressive state in the case of a critical course of SARS-CoV-2 infection might reflect subsequent clinical deterioration and predict a fatal outcome

Usefulness of C2HEST Score in Predicting Clinical Outcomes of COVID-19 in Heart Failure and Non-Heart-Failure Cohorts

Background: Patients with heart failure represent a vulnerable population for COVID-19 and are prone to having worse prognoses and higher fatality rates. Still, the clinical course of the infection is dynamic, and complication occurrence in particular in patients with heart failure is fairly unpredictable. Considering that individual components of the C2HEST (C2: Coronary Artery Diseases (CAD)/Chronic obstructive pulmonary disease (COPD); H: Hypertension; E: Elderly (Age &ge; 75); S: Systolic HF; T: Thyroid disease) are parallel to COVID-19 mortality risk factors, we evaluate the predictive value of C2HEST score in patients with heart failure (HF) Material and Methods: The retrospective medical data analysis of 2184 COVID-19 patients hospitalized in the University Hospital in Wroclaw between February 2020 and June 2021 was the basis of the study. The measured outcomes included: in-hospital mortality, 3-month and 6-month all-cause-mortality, non-fatal end of hospitalization, and adverse in-hospital clinical events. Results: The heart failure cohort consists of 255 patients, while 1929 patients were assigned to the non-HF cohort. The in-hospital, 3-month, and 6-month mortality rates were highest in the HF cohort high-risk C2HEST stratum, reaching 38.61%, 53.96%, and 65.36%, respectively. In the non-HF cohort, in-hospital, 3-month, and 6-month mortalities were also highest in the high-risk C2HEST stratum and came to 26.39%, 52.78%, and 65.0%, respectively. An additional point in the C2HEST score increased the total death intensity in 10% of HF subjects (HR 1.100, 95% CI 0.968&ndash;1.250 p = 0.143) while in the non-HF cohort, the same value increased by 62.3% (HR 1.623, 95% CI 1.518&ndash;1.734 p &lt; 0.0001). Conclusions: The C2HEST score risk in the HF cohort failed to show discriminatory performance in terms of mortality and other clinical adverse outcomes during hospitalization. C2HEST score in the non-HF cohort showed significantly better performance in terms of predicting in-hospital and 6-month mortality and other non-fatal clinical outcomes such as cardiovascular events (myocardial injury, acute heart failure, myocardial infarction, cardiogenic shock), pneumonia, sepsis, and acute renal injury