Search Results (656)

Sepsis is a systemic disorder in which infection-induced inflammation progressively disrupts vascular homeostasis and drives organ dysfunction. This review reframes septic pathophysiology as a sequential and self-amplifying process centered on endothelial failure. Early activation of innate immune pathways by pathogen- and damage-associated molecular patterns promotes cytokine release, oxidative stress, and enzymatic degradation of the endothelial glycocalyx. Loss of this protective surface layer exposes endothelial cells to unbuffered inflammatory and mechanical injury, impairing mechanotransduction, increasing leukocyte and platelet adhesion, and destabilizing vascular barrier function. Subsequent disruption of intercellular junctions promotes capillary leakage, tissue edema, and impaired oxygen diffusion, while mitochondrial dysfunction and redox imbalance reduce endothelial repair capacity. In parallel, complement activation, neutrophil extracellular trap formation, platelet–leukocyte interactions, and loss of anticoagulant signaling shift the microvasculature toward a prothrombotic and proinflammatory state. These interconnected mechanisms culminate in microvascular incoherence, characterized by heterogeneous capillary flow, regional hypoxia, impaired oxygen extraction, and progressive organ failure despite apparent restoration of systemic hemodynamics. Within this framework, biomarkers such as syndecan-1, soluble thrombomodulin, angiopoietin-2, von Willebrand factor, and plasminogen activator inhibitor-1 are best interpreted as mechanistic readouts of glycocalyx shedding, endothelial injury, permeability imbalance, and thromboinflammatory activation. Understanding sepsis as an evolving endothelial pathophysiological process provides a coherent framework for integrating inflammation, vascular leakage, hypoxia, coagulation, and organ dysfunction while identifying mechanistic biomarkers that reflect distinct stages of microvascular collapse. Full article

Healthcare-associated infections remain a major cause of morbidity and mortality in paediatric patients, particularly among those undergoing surgery or requiring intensive care. Distinguishing postoperative sterile inflammation from early sepsis is clinically challenging because conventional biomarkers such as C-reactive protein (CRP) and procalcitonin lack sufficient specificity. This narrative review aimed to analyse current evidence on pancreatic stone protein (PSP) as an emerging biomarker for the detection and risk stratification of infection in paediatric populations. A structured literature search was performed in PubMed and Web of Science for studies published between 2020 and 2026 using terms related to nosocomial infections, paediatric surgery, and PSP, identifying 147 articles; 54 met the inclusion criteria after screening. The analysed studies show that PSP levels increase significantly in children with sepsis compared with those with non-infectious systemic inflammation and are associated with bacteraemia, organ dysfunction, and mortality. In several paediatric cohorts, PSP demonstrated diagnostic performance comparable to or better than traditional markers, with reported AUROC values up to approximately 0.82 for distinguishing sepsis from non-infectious inflammation. Evidence from neonatal and high-risk populations also suggests strong sensitivity and specificity for early infection detection. Overall, PSP appears to be a promising biomarker for the early identification and prognostic stratification of paediatric sepsis; however, variability among studies highlights the need for larger multicentre prospective investigations and for integrating PSP into multimarker diagnostic algorithms. Full article

Background: Sepsis remains a leading cause of mortality in emergency and intensive care settings, with early diagnosis representing a critical determinant of patient outcomes. Despite advances in biomarker discovery, integrating platelet-derived metabolic signatures with explainable machine learning frameworks for sepsis prediction remains underexplored. The clinical adoption of predictive models has been hindered by the “black box” nature of conventional algorithms, limiting clinician trust and understanding. Objective: This study aimed to evaluate and validate an interpretable machine learning model utilizing platelet metabolomics data for accurate sepsis prediction while providing clinically meaningful explanations of the underlying metabolic disturbances that could inform therapeutic decision-making. Methods: We analyzed metabolomics data, comprising 25 sepsis patients diagnosed according to Sepsis-3 criteria and 14 age- and gender-matched non-sepsis from the emergency department. Platelet metabolite profiles were obtained via quantitative ¹H-NMR spectroscopy. Five machine learning algorithms were evaluated: Explainable Boosting Machine (EBM), Support Vector Machine (SVM), Logistic Regression (LR), Gradient Boosting Machine (GBM), and AdaBoost. Three biologically motivated metabolite ratios (adenosine triphosphate/adenosine diphosphate (ATP/ADP), ATP/adenosine monophosphate (AMP), Glutamine/Glutamate) were derived as additional features, yielding 22 candidate variables. Models were evaluated using a fully nested leave-one-out cross-validation (LOOCV) framework in which log transformation, KNN imputation, BorderlineSMOTE class balancing, and hyperparameter optimisation were performed exclusively within each training fold. Global and local interpretability analyses were performed to identify discriminative metabolites. Results: EBM achieved the highest ROC-AUC (0.864; 95% CI: 0.736–1.000), the highest PR-AUC (0.902; 95% CI: 0.783–0.997), and the best Brier score (0.189; 95% CI: 0.130–0.258) among all evaluated models, with sensitivity 0.880 (95% CI: 0.640–1.000; TP = 22/25) and specificity 0.714 (95% CI: 0.357–1.000; TN = 10/14). Global feature importance identified Carnitine, myo-Inositol, ADP, and O-Phosphoethanolamine as the leading single-feature predictors, alongside three pairwise interaction terms reflecting non-additive energy–amino acid metabolic relationships. Local explanations demonstrated that the ADP–Creatine interaction, Glutamine, and myo-Inositol drove correct sepsis classification in a representative true positive case. Conclusions: The EBM model demonstrated the highest discriminative performance and best calibration among all evaluated models, providing transparent mechanistic insights through global feature importance, and patient-level local explanations. These findings position the proposed framework as a proof-of-concept warranting external validation in larger, multi-centre cohorts before any clinical application is considered. Full article

Background: Sepsis and septic shock are associated with high mortality in intensive care units (ICUs), with a substantial risk persisting after ICU discharge. However, it remains unclear whether inflammatory biomarkers retain their prognostic value at the time of ICU discharge. This study aimed to evaluate whether discharge inflammatory biomarkers—including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), platelet-to-mean platelet volume ratio (PLT/MPV), and C-reactive protein-to-albumin ratio (CAR)—remain predictive of short- and long-term mortality in patients with sepsis and septic shock. Methods: In this single-center, retrospective cohort study, adult patients with sepsis or septic shock discharged from a tertiary ICU specializing in chest diseases between January 2013 and January 2015 were included. Sepsis and septic shock were retrospectively re-classified according to Sepsis-3 criteria. Inflammatory biomarkers measured at ICU admission and discharge, along with clinical variables and disease severity scores (APACHE II and SOFA), were recorded. Patients were followed for 28-day, 6-month, and 2-year mortality. The prognostic performance of biomarkers was assessed using receiver operating characteristic (ROC) analysis, and optimal cut-off values were determined. Independent predictors of mortality were evaluated using Cox proportional hazards regression analysis. Results: A total of 461 patients were included. In total, 291 (63.1%) had sepsis without shock and 170 (36.9%) had septic shock. The overall male proportion was 62%, with a median age of 65 (IQR 54–74) years in the sepsis group and 70 (63–79) years in the septic shock group. Mortality rates were significantly higher in patients with septic shock compared to those with sepsis at 28 days (24% vs. 10%, p < 0.001), 6 months (44% vs. 27%, p < 0.001), and 2 years (71% vs. 57%, p = 0.003). In unadjusted survivor/non-survivor comparisons, elevated discharge NLR and CAR were associated with early post-ICU mortality. However, in multivariable Cox regression, discharge NLR, but not discharge CAR, remained independently associated with 28-day and 6-month mortality. On ROC analysis, discharge NLR showed moderate discriminative performance for 28-day mortality (AUC 0.67, 95% CI 0.60–0.74), as did discharge CAR (AUC 0.68, 95% CI 0.60–0.76), although CAR did not retain independent prognostic significance after adjustment. An NLR value ≥ 5 was identified as an independent predictor of 28-day mortality (HR 2.44; 95% CI 1.24–4.80; p = 0.010) and was also significantly associated with 6-month mortality (HR 2.02; 95% CI 1.18–3.45; p = 0.011), although its predictive value decreased over longer follow-up periods (HR 1.37; 95% CI 0.93–2.01; p = 0.11 at 2 years). Conclusions: Inflammatory biomarkers measured at ICU discharge, particularly NLR, remain predictive of short-term mortality in patients with sepsis and septic shock, but their prognostic value diminishes over time. Assessment of inflammatory status at ICU discharge may provide a practical tool for early post-ICU risk stratification and may support clinical decisions regarding intensified outpatient surveillance and follow-up scheduling in this vulnerable population. Full article

Background/Objectives: Early risk stratification in non-shock sepsis remains challenging, as patients may appear clinically stable despite ongoing deterioration. We used key variables across seven pathophysiological domains (cardiovascular, hematological, metabolic, hepatic, renal, immune, and comorbidity burden) to identify admission-based predictors of in-hospital mortality for these patients and derive a simple, clinically applicable triage score. Methods: This prospective pilot study included 182 adult non-shock sepsis patients transferred from the Emergency Department to the internal medicine ward in a tertiary hospital in Arad (Romania). Markers of cardiovascular (atrial fibrillation), renal (creatinine, urea), immune–inflammatory (IL-6, CRP, ESR, procalcitonin, presepsin), metabolic (FBG), hepatic (AST, ALT), and comorbidity burden (CCI) domains were analyzed using logistic and LASSO regression with bootstrap validation. Results: Non-survivors exhibited a significantly higher prevalence of atrial fibrillation (p = 0.012), as well as significantly higher creatinine, urea, IL-6, CRP, ESR, CCI, and presepsin (p ≤ 0.042). Although most variables, (except IL-6) were significant in univariate analysis (p ≤ 0.047), only atrial fibrillation (AOR = 2.31, 95% CI: 1.09–2.84, p = 0.021) and creatinine (AOR = 1.40, 95% CI: 1.00–1.95, p = 0.048) remained independent predictors in the multivariate model. LASSO regression (1000 bootstrap iterations, selection frequency ≥ 80%) confirmed their robustness. Three-parameter models combining atrial fibrillation, creatinine, and inflammatory biomarkers showed good discrimination, with the presepsin-based model achieving an AUC of 0.843, 80.0% sensitivity, 82.9% specificity, and NPV > 95% at the optimal cut-offs (creatinine > 1.49 mg/dL; presepsin > 1446 pg/mL). The Sepsis CORE score demonstrated progressive risk stratification, with mortality rising from 0% to 60.0% across score categories. Conclusions: The proposed score integrates cardiovascular, renal, and immune domains into a simple admission-based tool with high negative predictive value. It may support early triage and risk stratification in non-shock sepsis patients admitted to general wards, although external validation is required. Full article

Background: Early identification of bacteremia in immunosuppressed cancer patients remains difficult, especially in neutropenia. This study evaluated the diagnostic accuracy of NLR, PLR, and NLPR for identifying bacteremia and sepsis in patients undergoing blood culture episode. Methods: We conducted a retrospective diagnostic accuracy study at a tertiary oncology center between January 2023 and December 2024. All bacteremia identified were included as cases. Culture-negative episodes were subsequently sampled as controls using a frequency-matching strategy. Hematological parameters were obtained within ±24 h of first blood culture episode. Diagnostic performance was assessed using ROC curve analysis and multivariable logistic regression. Results: Of 369 screened episodes, 337 from 323 unique patients were included after excluding 31 records. NLPR showed the highest accuracy for bacteremia (AUC 0.730; 95% CI 0.671–0.788). The optimal cut-off was 0.038 (sensitivity 69.2%, specificity 72.3%) and remained consistent after excluding episodes with antibiotic therapy (AUC 0.768), corticosteroids (AUC 0.708), or growth factor use (AUC 0.718). In severe neutropenia, NLPR showed the highest accuracy (AUC 0.887; 95% CI 0.797–0.978). In multivariable analysis (n = 304), NLPR remained independently associated with bacteremia (p < 0.001), with good model discrimination (AUC 0.815; 95% CI 0.763–0.866). Diagnostic performance for sepsis was lower and not statistically significant. Conclusions: These findings suggest that NLPR may represent a simple, inexpensive, widely accessible adjunctive biomarker to support early bacteremia risk stratification in immunosuppressed cancer patients, particularly in patients with severe neutropenia. Although its overall discrimination was comparable to isolated lymphocyte count, NLPR may provide clinically relevant contextual information by integrating multiple dimensions of immune dysregulation. Further prospective multicenter validation is warranted. Full article

Background: Anemia is a pervasive public health issue that is both a risk factor and a consequence of infection. This study aims to determine the prevalence and correlates of anemia in adults receiving vancomycin (VAN). Methods: A retrospective cross-sectional analysis of clinical data was undertaken for 299 patients treated with VAN at a tertiary care hospital from January 2024 to February 2025. Subjects were stratified by anemia severity into non-anemic, mild, moderate, and severe groups. Frequency was examined using the chi-squared test, medians by Kruskal–Wallis test, monotonic relations by Spearman’s correlation, and independent predictors using regression models. Results: Anemia was extremely prevalent in 90% of patients, mostly at a moderate level, and a weak positive correlation was observed between anemia severity and VAN trough levels, ICU admission, kidney disease, abnormal liver markers, and inflammatory indices. Microbial isolates were differentially enriched across anemia categories with K. pneumoniae, E. coli, and MRSA peaking in mild anemia and sharply declining in moderate and severe cases. Anemia severity was differentially correlated with P. aeruginosa, creatinine, hypertension, liver disease, albumin, platelets, and derived indices. In adjusted analysis, albumin, age, gender, platelet–neutrophil ratio, kidney disease, ICU admission, and MATH-1SD were independent predictors of anemia. A diagnostic model for anemia based on multiple markers was developed with an accuracy of 77%. Conclusions: Anemia is alarmingly very common in VAN-treated patients with distinct microbial and inflammatory signatures across severity groups, which highlights the need for experimental and longitudinal studies elucidating its pathophysiological mechanisms and clinical implications. Full article

Background/Objectives: Sepsis is clinically dynamic, and isolated admission biomarker values may insufficiently capture early biological evolution after treatment initiation. This study evaluated whether routine biomarker reassessment at approximately 48 h provides incremental prognostic information beyond admission Sequential Organ Failure Assessment (SOFA) score for 28-day mortality in sepsis. The analysis was framed as an exploratory 48 h landmark prognostic assessment among patients who were alive and had complete biomarker reassessment data at 48 ± 6 h. Methods: We conducted a prospective single-center observational cohort study including adult patients with sepsis. Clinical and laboratory data were collected at baseline (M1) and repeated 48 ± 6 h later (M2). The primary outcome was 28-day mortality. Candidate biomarkers included C-reactive protein (CRP), procalcitonin (PCT), lactate (LAC), and neutrophil-to-lymphocyte ratio (NLR). PCT clearance and NLR change were calculated as relative changes between M1 and M2, whereas 48 h CRP and 48 h lactate were evaluated as early reassessment values. Exploratory logistic regression models were constructed using admission SOFA as the clinical reference model. Model discrimination and fit were summarized using receiver operating characteristic analysis, likelihood-ratio testing, and Nagelkerke R²; the models were not intended as validated individual-level risk calculators. Results: The 48 h landmark analytical cohort included 126 patients, of whom 44 (34.9%) died within 28 days. Admission biomarker values showed limited prognostic signal. SOFA alone showed fair discrimination (AUC 0.740). Among the primary SOFA-augmented models, SOFA plus PCT clearance showed the highest discrimination and explanatory performance (AUC 0.810; Nagelkerke R² 0.332) and significantly improved model fit compared with SOFA alone. SOFA plus NLR change and SOFA plus 48 h lactate also provided incremental prognostic information, although their gains were more modest. In exploratory combined modeling, SOFA plus PCT clearance and NLR change provided the most coherent additional signal, with all predictors retaining independent associations with 28-day mortality. Conclusions: In this exploratory single-center 48 h landmark analysis, selected routine biomarker reassessment measures were associated with 28-day mortality beyond admission SOFA. PCT clearance provided the clearest incremental prognostic signal, while NLR change offered complementary information. Persistent 48 h lactate elevation was also informative, whereas lactate clearance was not. These findings should be interpreted as hypothesis-generating and require validation in larger cohorts, ideally including serial organ dysfunction measures such as 48 h SOFA or SOFA change. Full article

Neutrophil extracellular traps (NETs) contribute to innate immunity in sepsis, but their diagnostic value in neonates is unclear. We evaluated whether circulating NET-associated biomarkers discriminate septic from non-infected neonates. In this prospective observational study 96 neonates (≥34 weeks gestational age) with clinical suspicion of infection were enrolled (36 sepsis, 60 controls). Serum cell-free DNA (cfDNA), myeloperoxidase–DNA complexes (MPO-DNA), neutrophil elastase–DNA complexes (NE-DNA), and citrullinated histone H3 (H3cit) were measured alongside CRP and IL-6 at days 1, 3, and 5. Diagnostic performance was assessed by receiver operating characteristic (ROC) analysis with bootstrap confidence intervals. CRP (AUC 0.75, 95% CI 0.66–0.85) and IL-6 (AUC 0.73, 95% CI 0.61–0.83) showed the best diagnostic performance. cfDNA demonstrated moderate discrimination (AUC 0.72, 95% CI 0.60–0.84) but was only transiently elevated at day 1. MPO-DNA (AUC 0.47), NE-DNA (AUC 0.44), and H3cit (AUC 0.47) performed no better than chance. Within the sepsis group, MPO-DNA and NE-DNA at day 3 strongly correlated with the immature-to-total neutrophil ratio (ρ = 0.76 and 0.72), suggesting these markers reflect neutrophil degranulation rather than NET formation. NET-associated biomarkers do not improve diagnostic accuracy for neonatal sepsis beyond CRP and IL-6. These findings support the concept that neonatal innate immune responses differ fundamentally from adult patterns. Full article

Pediatric sepsis is a life-threatening systemic infectious response syndrome. Its core pathophysiological process involves a systemic imbalance between oxygen delivery and demand, coupled with cellular energy metabolism dysfunction, which collectively contribute to high mortality rates. Parameters of oxygen metabolism serve as critical indicators reflecting tissue perfusion and cellular oxygen utilization. Consequently, these parameters hold significant value for the early identification, severity stratification, therapeutic guidance, and prognostic evaluation of pediatric sepsis. This review systematically elucidates the pathophysiological mechanisms underlying oxygen metabolism disorders in pediatric sepsis. Furthermore, it highlights the current clinical applications and significance of key monitoring indices, including blood lactate, central venous oxygen saturation, oxygen delivery, and oxygen consumption. By integrating recent research advancements, this paper also explores therapeutic strategies aimed at optimizing oxygen metabolism, such as blood purification, microcirculation-targeted therapies, and extracorporeal membrane oxygenation. Finally, we provide future perspectives on emerging biomarkers and metabolomic approaches, aiming to establish a theoretical foundation for the optimized clinical management of pediatric sepsis. Full article

Septic cardiomyopathy is recognized as an acute, transient, and reversible condition. However, septic insult may induce latent changes characteristic of cardiac remodeling, with future consequences. Therefore, the present study aimed to evaluate the morphological and functional cardiac changes in the acute and subacute phases (with 7-day follow-up) in male Wistar rats subjected to experimental sepsis using a cecal ligation and puncture (CLP) model. In the acute phase, the animals underwent echocardiographic assessment at baseline and 48 h after the induction of sepsis. In the subacute 7 days follow-up, animals were allocated in control and sepsis groups. After this period, the animals underwent echocardiographic assessment, followed by euthanasia, papillary muscle testing, and subsequent morphometric and biochemical analyses. Fecal samples from six animals per group were collected at baseline and after 7 days for microbiota analysis. In the acute phase, echocardiographic assessment revealed that, following sepsis, animals exhibited reduced systolic function. In the subacute 7 days follow-up, both echocardiogram and papillary muscles revealed cardiac dysfunction in the sepsis group. Cardiomyocyte cross-sectional area and collagen content were significantly greater in the sepsis group compared with that in the control group. Analysis of maximal enzymatic activities involved in cardiac energy metabolism and oxidative stress biomarkers revealed no significant differences between groups. Considering microbiota assessment, beta diversity analysis revealed significant differences between septic animals and controls. In conclusion, sepsis was associated with persistent systolic/diastolic dysfunction, cardiomyocyte hypertrophy, and fibrosis after 7 days. These data suggest that septic cardiomyopathy should not be considered merely an acute, transient, and reversible condition in this experimental context. Full article

Background: Immune effector cell-associated hemophagocytic lymphohistiocytosis-like syndrome (IEC-HS) is a rare, life-threatening complication following CAR T-cell therapy. Diagnosis is challenging due to overlap with severe CRS, sepsis and lack of standardized criteria. Clinical data remain limited. Methods: We retrospectively analyzed 301 patients treated with CD19- or BCMA-directed CAR T-cells for hematologic malignancies at a single center from January 2019 to January 2026. IEC-HS was defined according to American Society for Transplantation and Cellular Therapy criteria. Results: Median follow-up was 31 months. IEC-HS was diagnosed in 14 patients (4.7%), median age 67 years. Underlying diseases included diffuse large B-cell lymphoma (n = 4), multiple myeloma (n = 7), mantle cell lymphoma, Burkitt lymphoma and B-lymphoblastic leukemia (n = 1 each). All patients had hyperferritinemia and cytopenias at baseline; most had high tumor burden (9/14) and elevated LDH (10/14). CRS occurred in all patients and ICANS in 6/14. IEC-HS occurred at median 10 days and was characterized by hyperferritinemia (median 15,321 µg/L), neutropenia, thrombocytopenia, hepatic dysfunction and high CAR-T-cell expansion in peripheral blood. Treatment included corticosteroids and anakinra (12/14). Refractory patients received IVIG (5/14), tocilizumab (3/14), siltuximab, ruxolitinib, emapalumab or etoposide (each n = 1). Infections occurred in 11/14; 4/14 had mixed infections. IEC-HS resolved in 7/14 (median 7 days). Mortality was 79% (11/14), mainly due to IEC-HS (7/14). Three patients were alive at last follow-up. One-year OS was lower vs. the whole cohort (31% vs. 69%, p < 0.0001). Conclusions: IEC-HS was associated with severe cytopenias, hyperferritinemia, hepatic dysfunction and high infection risk. Despite intensive immunosuppressive therapy, outcomes remain poor. Early biomarker-driven identification and multicenter studies are needed. Full article

Mesenchymal stem/stromal cells (MSCs) are multipotent progenitor cells with potent immunomodulatory properties, making them attractive candidates for treating inflammatory and autoimmune diseases. A key mediator of MSC-induced immunosuppression is programmed death-ligand 1 (PD-L1), a checkpoint molecule that interacts with PD-1 on immune cells to regulate immune responses and promote tolerance. This review synthesizes current evidence on the role of PD-L1 expression in MSCs, emphasizing its effects on both the innate and adaptive immune systems, its therapeutic potential, and its utility as a biomarker for MSC potency and clinical efficacy. We examine how PD-L1 modulates T cell activation, dendritic cell maturation, macrophage polarization, and cytokine profiles, including its role in exosomal contexts. Additionally, we highlight its synergistic interactions with other immune checkpoints and discuss its dual function as both a therapeutic effector and a dynamic biomarker. Finally, we explore its relevance in clinical contexts such as autoimmune diseases, graft-versus-host disease, sepsis, and transplantation and conclude with a discussion of challenges and future directions in harnessing PD-L1 for MSC-based therapies. Full article

Background/Objectives: Sepsis is a dynamic clinical syndrome characterized by a rapidly evolving inflammatory response, where early identification of patients at risk for adverse outcomes remains a major challenge. While inflammatory biomarkers are widely used, their prognostic value at baseline is limited. This study aimed to evaluate whether early changes in inflammatory biomarkers, particularly the neutrophil-to-lymphocyte ratio (ΔNLR), provide additional prognostic value in predicting short-term outcomes in patients with sepsis. Methods: A retrospective longitudinal observational study was conducted, including 168 adult patients admitted with sepsis at a tertiary infectious diseases hospital. Inflammatory biomarkers (CRP, procalcitonin, leukocyte subpopulations, and NLR) were assessed at admission and at 48–72 h. Early changes (Δ values) were calculated and analyzed in relation to a composite adverse outcome, including ICU admission, vasopressor requirement, mechanical ventilation, or in-hospital mortality. Logistic regression and ROC curve analyses were used to evaluate predictive performance. Results: Patients with adverse outcomes had significantly higher baseline inflammatory markers and severity scores. Early reductions in CRP and NLR were more pronounced in survivors, whereas non-survivors showed persistently elevated or minimally decreasing values. In multivariate analysis, ΔNLR remained independently associated with in-hospital mortality (OR 0.91, 95% CI 0.84–0.98, p = 0.015), alongside Sequential Organ Failure Assessment (SOFA) score and septic shock. ΔNLR demonstrated better discriminative performance (AUC 0.74) compared to baseline markers and improved predictive accuracy when combined with SOFA score (AUC 0.81). Higher baseline NLR quartiles were associated with a stepwise increase in adverse outcomes. Conclusions: Early changes in inflammatory biomarkers, particularly ΔNLR, provide clinically relevant prognostic information beyond baseline measurements and severity scores in sepsis. Dynamic assessment of immune response may improve early risk stratification and support more individualized clinical decision-making. Full article

Background and Objectives: Urosepsis is a common cause of sepsis in adults and is associated with substantial morbidity and mortality, particularly when urinary obstruction delays timely source control. The roles of diagnostic uncertainty at presentation, microbiological phenotypes (including multidrug resistance), and biomarkers in shaping management pathways and outcomes warrant further evaluation. Materials and Methods: This retrospective, single-center, observational study included 154 consecutive adult patients hospitalized for urosepsis. Sepsis was defined according to the Sepsis-3 criteria. Baseline clinical modifiers at admission were encoded as binary variables (e.g., malignancy, urinary tract obstruction/altered anatomy, immunocompromised status, acute kidney injury [AKI], and diagnostic uncertainty). Microbiology was standardized into pathogen groups (Gram-negative, Gram-positive, or no isolate), infection complexity (mono- vs. polymicrobial), and multidrug-resistant organism (MDRO) status. Procedures were categorized as no procedure, urinary tract decompression, or other source controls. Biomarkers (C-reactive protein [CRP], procalcitonin [PCT], and creatinine) were analyzed at admission and, when available, during hospitalization. The primary outcomes were in-hospital mortality, ICU admission, and absence/delay of source control. Results: The median age was 68 years, and 60.4% of patients were male. The in-hospital mortality and ICU admission rates were 7.1% and 3.9%, respectively. Diagnostic uncertainty was present in 9.8% and was associated with a higher likelihood of no invasive intervention (86.7% vs. 43.9%, p = 0.002) and a lower rate of urinary tract decompression (13.3% vs. 45.3%, p = 0.01). Gram-negative pathogens predominated (50.0%), and MDROs were identified in 18.2% and were associated with prior urological interventions (53.6% vs. 24.6%, p = 0.003) and higher admission PCT levels (8.6 vs. 3.2 ng/mL, p = 0.04). Bacteremia was associated with mortality (14.5% vs. 2.2%, odds ratio [OR] 7.64, p = 0.007). Mortality was higher in Gram-positive infections (21.7% vs. 4.6%, OR 5.79, p = 0.012) and in patients with AKI at admission (25.0% vs. 5.7%; OR, 5.54; p = 0.043). Conclusions: Urosepsis exhibits distinct clinical and microbiological phenotypes that influence its management and outcomes. Diagnostic uncertainty at presentation was associated with reduced early source control measures, whereas MDRO infections were clustered with prior urological interventions and higher systemic inflammatory burdens. Bacteremia, Gram-positive pathogens, and AKI at admission were associated with an increased in-hospital mortality risk. These findings support a multidimensional early assessment strategy integrating clinical presentation, microbiological risk, biomarkers, and rapid evaluation of obstruction to facilitate timely source control. Full article