Advances in Understanding Inflammation and Tissue Damage: Markers of Persistent Sequelae in COVID-19 Patients

Journal of Clinical Medicine, Journal Year: 2025, Volume and Issue: 14(5), P. 1475 - 1475

Published: Feb. 22, 2025

This review explores the crucial role of established and emerging biomarkers in diagnosis, management, understanding post-COVID-19 conditions. With COVID-19 affecting multiple organ systems, have been instrumental identifying ongoing inflammation tissue damage, facilitating early diagnosis prognostication. Specifically, markers like C-reactive protein (CRP), interleukin-6 (IL-6), novel entities such as soluble urokinase plasminogen activator receptor (suPAR) neutrophil extracellular traps (NETs) provide insights into pathophysiological mechanisms predict long-term outcomes. highlights integration these clinical workflows their implications for personalized medicine, emphasizing potential guiding therapeutic interventions monitoring recovery. Future directions suggest a focus on longitudinal studies to explore biomarker trajectories interaction with outcomes, aiming enhance management conditions refine public health strategies.

Language: Английский

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Immune Cell-Based versus Albumin-Based Ratios as Outcome Predictors in Critically Ill COVID-19 Patients

Journal of Inflammation Research, Journal Year: 2025, Volume and Issue: Volume 18, P. 73 - 90

Published: Jan. 1, 2025

Purpose: The aim of the retrospective, single-center study was to assess prognostic value immune cell-based and albumin-based ratios regarding lethal outcome in critically ill COVID-19 patients. Patients Methods: We analyzed 612 adult patients admitted intensive care unit (ICU) between April 2020 November 2022. Blood measurement on admission ICU encompassed complete blood count (CBC), IL-6, C-reactive protein (CRP), albumin, lactate, lactate dehydrogenase (LDH), serum bicarbonate, arterial base deficit/excess (BD/E), D-dimer. All measured calculated parameters were compared survivors nonsurvivors, with measure being hospital mortality. Results: Immune [NLR - Neutrophil-to-Lymphocyte Ratio, MLR Monocyte-to-Lymphocyte PLR Platelet-to-Lymphocyte MPV Mean Platelet Volume, MPV/PC Volume-to-Platelet Count Derived (d-)NLR ratio neutrophil divided by result white cell (WBC) – count), N/LP Neutrophil x 100/Lymphocyte count, CLR (CRP)-to-Lymphocyte CPR CRP-to-Platelet LLR Lactate (LDH)-to-Lymphocyte Systemic Inflammation Index (SII) platelet neutrophil/lymphocyte Response (SIRI) monocyte/lymphocyte count] investigated. White counts significantly higher, while lymphocyte lower nonsurvivors. MPV, MPV/PC, NLR, d-NLR, MLR, N/LP, CRP, LDH, CPR, CLR, LLR, SII, SIRI values higher Monocyte did not differ groups. Albumin-based included CRP-to-Albumin Ratio (CAR), Lactate-to-Albumin (LAR) LDH-to-Albumin (LDH/ALB). Conclusion: only independent predictor outcomes at is LDH/ALB ratio. Most other moderate, although highly significant predictors mortality Keywords: LDH/albumin ratio, ill, COVID-19,

Language: Английский

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Development and validation of a clinical prediction model for in-hospital mortality of severe pneumonia based on machine learning

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 7, 2025

Objective: We aimed to develop an interpretable model predict the mortality risk for patients with severe pneumonia. Methods: The study retrospectively employed data from pneumonia hospitalized at First Affiliated Hospital of Henan University Chinese Medicine and Provincial between January 2008 November 2021 as training set development. Patients admitted same two hospitals December 2024 were prospectively included test evaluation. The demographic characteristics, clinical manifestations upon admission, factors comorbidities, complications, laboratory results, treatment during hospitalization, other features, fatal outcomes collected. In set, all analyzed in comparison survivors non-survivors. least absolute shrinkage selection operator (LASSO) regression was applied select features establishment five models: logistic (LR), support vector machine (SVM), decision tree (DT), random forest (RF), extreme gradient boosting (XGBoost). performance models assessed discrimination, calibration practicability. optimal screened out, SHapley Additive exPlanation (SHAP) method used explain. Results: A total 323 eligible enrolled, including 226 97 set. four models, XGBoost demonstrated third highest AUROC (0.853), along SHAP value indicated that retention catheterization applicationhad strongest predictive prediction horizons, closely followed by variables oral herbal decoction, BUN level, age, tracheotomy application, complication septic shock, TCM syndrome (pathogenic qi falling into prostration syndrome). Conclusions: Older increased BNU syndrome) may be potential affect pneumonia, among which application decoction are protective factors. exhibits superior overall predicting hospital greater than traditional scoring systems such PSI, SOFA, APACHE II, assists clinicians prognostic assessment, resulting improved therapeutic strategies resource allocation patients.

Language: Английский

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Risk factors for thrombocytopenia associated with intravenous valproic acid therapy in pediatric patients undergoing neurosurgical operations

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 21, 2025

Thrombocytopenia is one of the side effects VPA. This study aimed to evaluate incidence and risk factors thrombocytopenia after intravenous VPA treatment in children with neurosurgical operations. Pediatric patients undergoing operations treated were enrolled this retrospective study. According platelet count injection VPA, pediatric divided into group non-thrombocytopenia group. Binary logistic regression analysis was used explore for thrombocytopenia. A total 252 included study, 12.3% (31/252). Univariate showed that baseline count, duration therapy, blood loss associated occurrence administration revealed (OR 0.995, 95% CI 0.991-0.999) independent Our data show common an factor Regular monitoring important whether short-term prophylactic use

Language: Английский

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Predictive Models of Patient Severity in Intensive Care Units Based on Serum Cytokine Profiles: Advancing Rapid Analysis

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(9), P. 4823 - 4823

Published: April 26, 2025

Predicting disease states and outcomes—and anticipating the need for specific procedures—enhances efficiency of patient management, particularly in dynamic heterogenous environments intensive care units (ICUs). This study aimed to develop robust predictive models using small sets blood analytes predict severity mortality ICUs, as fewer are advantageous future rapid analyses biosensors, enabling fast clinical decision-making. Given substantial impact inflammatory processes, this research examined serum profiles 25 cytokines, either association with or independent nine routine analyses. Serum samples from 24 male COVID-19 patients admitted an ICU were divided into three groups: Group A, including less severe patients, Groups B C, that needed invasive mechanical ventilation (IMV). Patients C died within seven days after current analysis. Naïve Bayes developed full dataset feature subsets selected through information gain algorithm univariate data Strong achieved IMV (AUC = 0.891) homogeneous 0.774) more heterogeneous 0.887) populations utilizing two features. Despite sample, these findings underscore potential effective prediction based on a limited number analytes.

Language: Английский

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Comparative analysis of neutrophil dynamics and disease in SARS-CoV-2 Delta and Omicron variants utilizing an in vivo feline model for COVID-19

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: May 22, 2025

The emergence of SARS-CoV-2 variants, particularly Delta (B.1.617.2) and Omicron (XBB.1.5) has substantially influenced the clinical immunological landscape COVID-19. This study investigates differential pathogenicity immune responses in a feline model infected with these focusing on neutrophil activation, extracellular trap (NET) formation, cytokine profiles. Eight pathogen-free cats were inoculated B.1.617.2 (Delta) (n=3), XBB.1.5 (Omicron) or vehicle (n=2), assessments, histopathological examinations, analyses performed post-infection. Results demonstrate that Delta-infected exhibit more severe manifestations characterized by significant elevation respiratory effort, wheezing, systemic inflammation compared to Omicron-infected cats, which show milder symptoms, primarily confined upper tract. Histopathological findings suggest pronounced lung damage whereas infection resulted localized pathology. Cytokine profiling demonstrates heightened proinflammatory responses, elevated levels IL-6, IFN-γ TNF-α while results less inflammatory responses. Moreover, neutrophil-related parameters, including total counts banded neutrophils, significantly correlating enhanced NET formation as evidenced increased NETs-related markers MPO, NE, citrullinated H3, NET-specific MPO-DNA complexes cell-free DNA. underscores importance variant-specific highlights need for targeted therapeutic strategies mitigate injury associated infection, also considering distinct dynamics observed variant. Furthermore, support delineating concerning future variants. These provide valuable insights into pathogenesis companion animals inform public health new variants continue emerge.

Language: Английский

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