Predicting the Outcome of Patients with Severe COVID-19 with Simple Inflammatory Biomarkers: The Utility of Novel Combined Scores-Results from a European Tertiary/Referral Centre

Association of Inflammatory and Metabolic Markers with Mortality in Patients with Postoperative Femur Fractures in the Intensive Care Unit

Background and Objectives: Postoperative femur fracture in elderly patients is associated with high morbidity and mortality, especially in the intensive care unit (ICU). Various factors, including demographic and laboratory parameters, may influence mortality in this population. The aim of this study was to evaluate the association of inflammatory and metabolic markers with mortality in ICU patients with postoperative femur fractures and to identify key predictors to enhance risk stratification and improve patient outcomes. Materials and Methods: In this retrospective single-center study, we analyzed 121 patients aged over 65 years with postoperative femur fractures who were admitted to the ICU between January 2023 and January 2024. Demographic and clinical data, including comorbidities, Charlson Comorbidity Index (CCI), and Acute Physiology and Chronic Health Evaluation (APACHE II) score, were collected. Laboratory parameters such as white blood cell count (WBC), albumin, C-reactive protein (CRP), D-dimer, Pan-Immune-Inflammation Value (PIV), CRP-to-albumin ratio (CAR), neutrophil-to-lymphocyte ratio (NLR), and others were analyzed. Linear regression, logistic regression, and Receiver Operating Characteristic (ROC) analyses were performed to determine the predictive value of these markers for ICU mortality. Results: The mean age of the patients was 76.3 ± 9.6 years, and 52.1% were female. The most common comorbidities were hypertension (67.8%) and diabetes (49.6%). ICU mortality occurred in 24 patients (20%). Significant predictors of mortality included higher CRP (>62.8 mg/L), NLR (>10.0), PIV (>450), and APACHE II scores (>23) (p < 0.001 for all). Lower albumin levels (<2.5 g/dL) were strongly associated with increased mortality (p < 0.001). ROC analysis demonstrated that the APACHE II score had the highest predictive accuracy for mortality (AUC = 0.83), followed by albumin (AUC = 0.79) and PIV (AUC = 0.76). Extended ICU stay (>10 days) was also significantly correlated with increased mortality (p < 0.001). Conclusions: This study successfully demonstrates the utility of combining traditional clinical markers, such as APACHE II score, with novel inflammatory markers, such as PIV, CAR, and NLR, in predicting mortality in ICU patients following femur fracture surgery. The integration of emerging biomarkers with well-established scoring systems offers enhanced predictive accuracy and provides valuable insights into patient management.

Predicting Severe COVID-19 Outcomes in the Elderly: The Role of Systemic Immune Inflammation, Liver Function Tests, and Neutrophil-to-Lymphocyte Ratio

Background: Patients aged 80 years and above are at increased risk for severe COVID-19 outcomes. This study aimed to evaluate the prognostic utility of the derived neutrophil-to-lymphocyte ratio (dNLR), aspartate-aminotransferase-to-lymphocyte ratio index (ALRI), aspartate-aminotransferase-to-platelet ratio index (APRI), and systemic immune inflammation index (SII) in predicting severe disease, intensive care unit (ICU) admission, and mortality among COVID-19 patients aged 80 years and older. Methods: In this retrospective cohort study, 138 elderly patients (≥80 years) and 215 younger controls (<65 years) with confirmed COVID-19 were included. Laboratory data at admission were collected, and the dNLR, ALRI, APRI, and SII scores were calculated. Receiver operating characteristic (ROC) curve analysis was performed to assess the predictive performance of these indices. Results: The SII had the highest area under the ROC curve (AUC) for predicting severe disease in elderly patients (AUC = 0.857, 95% CI: 0.795-0.919, p < 0.001), with an optimal cutoff value of 920 × 10⁹/L (sensitivity 86%, specificity 78%). Elevated SII was significantly associated with increased risk of ICU admission (hazard ratio (HR): 2.9, 95% CI: 1.8-4.6, p < 0.001) and mortality (HR: 3.2, 95% CI: 1.9-5.2, p < 0.001). Similarly, dNLR showed good predictive value (AUC = 0.792, 95% CI: 0.722-0.862, p < 0.001). Conclusions: SII and dNLR are valuable prognostic biomarkers for predicting severe outcomes in COVID-19 patients aged 80 years and above. Early identification using these indices can assist clinicians in risk stratification and management decisions to improve patient outcomes.

Notable correlation between serum epidermal growth factor values and inflammatory status in patients with COVID-19

INTRODUCTION

Despite its crucial role in Epidermal Growth Factor Receptor (EGFR) activation, and the resulting impact on the health-disease process, epidermal growth factor (EGF) is an underexplored molecule in relation to how its serum concentrations relate to other analytes and clinical variables in pathological contexts.

OBJECTIVE

To clarify the possible correlation between EGF and clinical and analytical variables in the context of COVID-19.

METHODS

Cross-sectional observational and analytical study, in patients with virological and clinical diagnosis of COVID-19, selected by simple random sampling, admitted between August and September 2021. UMELISA-EGF commercial kits were used.

RESULTS

Differences in overall EGF values were observed between groups (566.04 vs. 910.53 pg/ml, p = .0430). In COVID-19 patients, no notable correlations were observed for neutrophil, platelet, triglyceride or liver enzyme values (p > .05). Significant correlations were observed with the neutrophil-lymphocyte indicator (r = 0.4711, p = .0128) as well as with the platelet-lymphocyte index (r = 0.4553, p = .0155). Statistical results of multivariate regression analysis suggest NLR (β = .2232, p = .0353) and PLR (β = .2117, p = .0411) are predictors of inflammation in patients with COVID-19.

CONCLUSIONS

Serum EGF concentrations in COVID-19 correlate positively with prognostic inflammatory markers of severity and could presumably act as an independent risk factor for the development of inflammation in response to new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Neutrophil-to-Lymphocyte Ratio and Cytokine Profiling as Predictors of Disease Severity and Survival in Unvaccinated COVID-19 Patients

BACKGROUND

During the COVID-19 pandemic, identifying reliable biomarkers for predicting disease severity and patient outcomes in unvaccinated individuals is essential. This study evaluates the efficacy of key hematological markers, including leukocyte and neutrophil counts, Neutrophil-to-Lymphocyte Ratio (NLR), and cytokine profiles (IL-6, INF-γ, TNF-α, IL-17A, CCL2, and CXCL10) for predicting the necessity for mechanical ventilation and assessing survival probabilities.

METHODS

We conducted an in-depth analysis on a cohort of COVID-19 patients, emphasizing the relationship between NLR, cytokine profiles, and clinical outcomes, utilizing routine leukocyte counting and cytokine quantification by flow cytometry.

RESULTS

Elevated leukocyte and neutrophil counts, increased NLR, and significant cytokine elevations such as IL-6 and IL-10 were strongly associated with the need for mechanical ventilation, reflecting a pronounced systemic inflammatory response indicative of severe disease outcomes.

CONCLUSION

Integrating hematological markers, particularly NLR and cytokine profiles, is crucial in predicting mechanical ventilation needs and survival in non-vaccinated COVID-19 patients. Our findings provide critical insights into the pathophysiology of COVID-19, supporting the development of more targeted clinical interventions and potentially informing future strategies for managing infectious disease outbreaks.

Assessment of COVID-19 risk factors of early and long-term mortality with prediction models of clinical and laboratory variables

BACKGROUND

Coronavirus disease (COVID-19) may lead to serious complications and increased mortality. The outcomes of patients who survive the early disease period are burdened with persistent long-term symptoms and increased long-term morbidity and mortality. The aim of our study was to determine which baseline parameters may provide the best prediction of early and long-term outcomes.

METHODS

The study group comprised 141 patients hospitalized for COVID-19. Demographic data, clinical data and laboratory parameters were collected. The main study endpoints were defined as in-hospital mortality and 1-year mortality. The associations between the baseline data and the study endpoints were evaluated. Prediction models were created.

RESULTS

The in-hospital mortality rate was 20.5% (n = 29). Compared with survivors, nonsurvivors were significantly older (p = 0.001) and presented comorbidities, including diabetes (0.027) and atrial fibrillation (p = 0.006). Assessment of baseline laboratory markers and time to early death revealed negative correlations between time to early death and higher IL-6 levels (p = 0.032; Spearman rho - 0.398) and lower lymphocyte counts (p = 0.018; Pearson r -0.438). The one-year mortality rate was 35.5% (n = 50). The 1-year nonsurvivor subgroup was older (p < 0.001) and had more patients with arterial hypertension (p = 0.009), diabetes (p = 0.023), atrial fibrillation (p = 0.046) and active malignancy (p = 0.024) than did the survivor subgroup. The model composed of diabetes and atrial fibrillation and IL-6 with lymphocyte count revealed the highest value for 1-year mortality risk prediction.

CONCLUSIONS

Diabetes and atrial fibrillation, as clinical factors, and LDH, IL-6 and lymphocyte count, as laboratory determinants, are the best predictors of COVID-19 mortality risk.

Evaluating the diagnostic and prognostic ability of ischemia modified albumin in COVID-19

BACKGROUND

Patients with COVID-19 can rapidly deteriorate and develop acute hypoxic respiratory failure. Prominent features of the disease include severe inflammation, endotheliitis, and thrombosis.

OBJECTIVES

The aim of the study was to evaluate the diagnostic and prognostic effectiveness of ischemia modified albumin (ΙΜΑ) in a cohort of COVID-19 patients.

METHODS

This prospective observational study included adults with SARS-CoV-2 infection confirmed by reverse transcription polymerase chain reaction test, who were hospitalized specifically for COVID-19. The outcomes of interest were progression to severe acute respiratory failure during the index hospitalization defined as partial pressure of oxygen/fraction of inspired oxygen lower or equal to 150, admission to the intensive care unit (ICU) and in-hospital mortality. Admission IMA levels were determined using the commercially available "IMA Assay Kit" method (Abbexa LTD, Cambridge, UK). Adults without SARS-CoV-2 infection were used as controls.

RESULTS

135 COVID-19 patients and 64 controls were included. Admission IMA levels were significantly higher in COVID-19 patients compared to controls [[24.38 (11.94) ng/ml vs. 14.69 (3.52) ng/ml, p < 0.01]. Receiver operating characteristic analysis of admission IMA showed an area under the curve (AUC) of 94% (p < 0.0001) for COVID-19 diagnosis (cut-off value: 17.5 ng/ml; sensitivity: 90.37%; specificity: 87.5%). Admission IMA was also associated with mortality (AUC: 68%, p = 0.01). However, it was not associated with severe acute respiratory failure (AUC: 47%, p = 0.53) or ICU admission (AUC: 58%, p = 0.41).

CONCLUSION

Admission IMA was significantly increased in COVID-19 patients and was associated with in-hospital mortality.

Inflammatory Biomarkers for Assessing In-Hospital Mortality Risk in Severe COVID-19-A Retrospective Study

(1) Background: Our study aims to investigate the utility of inflammatory factors as prognostic indicators for disease severity and mortality in COVID-19 patients admitted to the Intensive Care Unit (ICU) Department of Pelican Clinical Hospital Oradea Romania. While elevated white blood cell (WBC) levels are associated with COVID-19 severity and mortality, they may not effectively predict the risk of death; (2) Methods: In our ICU department, we conducted assessments on the 10th and 14th days of COVID-19 patients' hospitalization, measuring the following markers: C-reactive protein (CRP) levels, procalcitonin (PCT) levels, granulocytes/lymphocytes (G/L) ratios, ferritin levels, age, and obesity status. We included a total of 209 eligible COVID-19 patients in the final analysis. Our goal was to identify biomarkers that could quickly identify high-risk patients with a potential for disease progression and mortality; (3) Results: Our study (a retrospective, single-center observational cohort study) demonstrated statistically significant differences in predicting mortality and disease severity based on G/L ratio (p < 0.0001), PCT (p < 0.0002), CRP (p < 0.0001), ferritin (p < 0.0001), age (p < 0.0001), and obesity (p < 0.0001); (4) Conclusions: Having a G/L ratio exceeding 20 units, along with elevated levels of PCR, PCT, and ferritin in older and obese patients on the 3rd day of ICU admission, represents significant risk factors for in-hospital mortality in severe COVID-19 patients.