Search Results (407)

Background: This study evaluates whether maximal and mean lactate-to-albumin (LAR), C-reactive protein-to-albumin (CAR), and procalcitonin-to-albumin (PAR) ratios during ICU stay improve mortality prediction beyond admission values in critically ill, cardiovascularly burdened patients, and compares their performance against individual biomarkers. Methods: We conducted a retrospective single-center cohort study of consecutive adult ICU admissions (2024) in a tertiary cardiac center, using temporally aligned (±12 h) albumin-based ratios derived from serial laboratory measurements. Maximal and mean in-ICU values were analysed per admission. The primary endpoint was ICU mortality. Associations and discriminative performance were evaluated using ROC analysis and multivariable logistic regression. Results: Of 212 screened ICU admissions, 137 patients were included. The ICU mortality was 48.9%. Both maximum and mean values of biomarkers and composite ratios were more abnormal in non-survivors, with the strongest independent associations observed for maximum LAR and CAR. In adjusted analyses, maximum LAR and CAR remained independently associated with ICU mortality and showed moderate discrimination (AUC 0.704 and 0.712). Mean CAR and LAR performed numerically slightly better in ROC analysis, whereas PAR showed weaker and less consistent prognostic utility. Conclusions: Maximal and mean LAR and CAR were independently associated with ICU mortality, whereas PAR showed weaker performance. These ratios may serve as simple tools for dynamic risk stratification but require prospective multicenter validation. Full article

Background/Objectives: Acute respiratory failure (ARF) encompasses heterogeneous etiologies, and early bedside prognostication remains challenging. Cytokines and chemokines may capture underlying biological severity and identify high-risk patients. We evaluated whether admission cytokine/chemokine profiles add incremental prognostic value over clinical risk factors in unselected ARF patients. Methods: This prospective, single-center cohort study enrolled adult patients admitted to medical ICUs with ARF requiring high-intensity respiratory support. Plasma samples were collected within 24 h of ARF diagnosis, and 19 cytokines/chemokines were measured using multiplex immunoassays. The primary outcome was ICU mortality. Univariate and multivariable logistic regression models assessed associations between biomarkers and mortality, with discrimination evaluated by the area under the receiver operating characteristic curve (AUC). Results: Among 41 patients, 15 (37%) died in the ICU. Non-survivors had higher rates of immunosuppression (80% vs. 38%, p = 0.010) and hematologic malignancy (67% vs. 31%, p = 0.026). CXCL10 (IP-10), IL-18, and CCL2 (MCP-1) were significantly higher in non-survivors, and IL-1Ra showed a marked numerical increase with a significant univariable association with ICU mortality, despite comparable severity scores and oxygenation indices at admission. A clinical core model (SOFA, immunosuppression, hematologic malignancy) achieved an AUC of 0.74 (95% CI 0.58–0.90); adding cytokines improved discrimination modestly (AUC 0.76–0.80). In highest-quartile survival analyses, IL-1Ra (p = 0.002), CXCL10 (p = 0.005), and CCL2 (p = 0.009) demonstrated significant survival separation. Conclusions: At ICU admission, CXCL10 (IP-10), IL-18, CCL2 (MCP-1), and IL-1Ra showed exploratory associations with ICU mortality and were prioritized as candidate inflammatory biomarkers. These findings require validation in larger multicenter cohorts. Full article

Background/Objectives: Adipokines are candidate biomarkers in critical illness due to their roles in immunity and metabolism, both profoundly altered in sepsis. Omentin-1, vaspin, and chemerin have been studied in selected septic cohorts, but not concurrently in a heterogeneous ICU population including both septic and non-septic patients. Methods: Prospective observational cohort of 200 consecutive ICU patients with 28-day follow-up. Biomarkers were measured by ELISA within 24 h of admission. Analyses included Mann–Whitney U tests, Spearman correlations, ROC curves, and logistic regression with APACHE II and SOFA as comparators. Results: Vaspin was significantly higher in septic versus non-septic patients (406.4 [190.0–799.6] vs. 275.8 [101.8–559.8] pg/mL; p = 0.009). Omentin-1 was elevated in 28-day non-survivors (34.4 [22.5–56.1] vs. 25.1 [15.0–48.4] ng/mL; p = 0.037; AUROC 0.599), but lost significance after APACHE II adjustment (p = 0.295). Chemerin trended lower in non-survivors (p = 0.099); in septic patients, it correlated inversely with SOFA (r = −0.43) and lactate (r = −0.40), both p < 0.001. IL-6 and IL-10 were higher in non-survivors; IL-10 predicted 28-day mortality (AUROC 0.783), comparable to APACHE II (0.785). Conclusions: Vaspin distinguishes sepsis in mixed ICU populations. Omentin-1 shows a severity-driven association with mortality that does not survive APACHE II adjustment (AUROC 0.599, poor standalone discrimination), while chemerin inversely tracks hypoperfusion markers in septic patients, suggesting a potential counter-regulatory role requiring mechanistic confirmation. Individually, these adipokines do not add prognostic value beyond established severity scores, but their biological orthogonality to classical cytokines warrants exploration in multi-marker panel studies. Full article

Background: Vasoplegic shock (VS) in critically ill patients without microbiological evidence of infection poses a major clinical challenge in intensive care units (ICUs). Extracorporeal cytokine hemadsorption using the oXiris^® membrane—a high-permeability polyacrylonitrile-based (AN69-ST) filter with adsorptive properties against inflammatory mediators—has emerged as a potential adjunct to restore haemodynamic stability. Evidence supporting its use remains limited, particularly regarding timing of initiation and downstream mortality biomarkers. Methods: We conducted a single-centre prospective observational study at the ICU of Istanbul Prof. Dr. Cemil Taşcıoğlu City Hospital between October 2022 and January 2023. Adults aged ≥18 years with VS (CRP ≥ 100 mg/L, procalcitonin [PCT] < 2 μg/L, no positive microbiological culture) requiring continuous renal replacement therapy (CRRT) with the oXiris^® membrane were enrolled (n = 34), of whom 30 completed the study period without microbiological exclusion and comprised the final analysis cohort. Pre- and post-treatment (72 h) clinical and cytokine parameters were compared. The association of VS resolution and 7-day mortality with timing of oXiris^® initiation, cytokine levels, and treatment duration was assessed. This study was conducted and reported in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) statement. Results: Significant changes were observed across all principal haemodynamic and inflammatory parameters at 72 h of oXiris^® treatment, including mean arterial pressure (MAP: 50.8 ± 6.3 to 69.3 ± 17 mmHg, p < 0.001), SOFA score (8.33 ± 2.29 to 4.9 ± 3.22, p < 0.001), IL-6 (767.3 ± 1205.7 to 294.4 ± 686.3 pg/mL, p < 0.001), IL-1β, TNF-α, CRP, lactate, and creatinine. VS resolved in 24/30 patients (80%). Younger age was associated with VS resolution (57.8 ± 19.7 vs. 76.6 ± 13.9 years; p = 0.021). Initiation of oXiris^® within 8 h was associated with significantly shorter VS resolution time (52.5 ± 23.9 vs. 85.9 ± 48.2 h; p = 0.045). Seven-day mortality was 20% (n = 6) and hospital mortality was 50% (n = 15). Post-treatment IL-1β (856.7 ± 548.5 vs. 1086.9 ± 353.6 pg/mL; p = 0.044) and TNF-α (111.0 ± 70.0 vs. 145.4 ± 47.8 pg/mL; p = 0.011) at 72 h were significantly higher in hospital non-survivors, representing exploratory prognostic associations. Conclusions: Changes in haemodynamic and inflammatory parameters were observed during oXiris^®-based CRRT treatment in critically ill patients with non-septic VS. Early initiation (≤8 h) was associated with shorter VS resolution time in this exploratory, uncontrolled analysis. Residual IL-1β and TNF-α at 72 h were associated with hospital mortality in exploratory analyses and may represent hypothesis-generating prognostic signals requiring prospective validation. Randomised controlled trials are warranted to confirm these findings and define optimal timing strategies. Full article

Background: This study investigated whether lactate dehydrogenase (LDH) levels measured at ICU admission predict early in-hospital mortality among critically ill medical patients in a single-center retrospective cohort study conducted in Turkey. Specifically, we aimed to (i) determine an optimal LDH threshold; (ii) examine the temporal trajectory of discriminatory performance over 72 h; and (iii) assess LDH as an independent predictor beyond established severity scores. Methods: In this single-center retrospective cohort study, 681 adults admitted to a medical ICU between January 2015 and January 2025 were analyzed. Serial LDH measurements were obtained at 0, 24, 48, and 72 h after ICU admission. This study was approved by the Institutional Ethics Committee (Decision No.: 2025/99). ROC analysis was performed under a predefined sensitivity constraint (≥0.70), and time-to-event outcomes were examined using Kaplan–Meier methods and Cox proportional hazards regression. Determinants of maximum LDH were assessed using a GLM with Gamma distribution and log link. Results: The 28-day mortality rate was 39.1%. ROC analysis identified an optimal 24-h LDH cut-off of approximately 275 U/L (AUC = 0.650; sensitivity = 0.70). Discriminatory performance improved progressively over time (AUC of 0.632 at baseline to 0.690 at 72 h), suggesting that serial measurements may capture evolving prognostic information more effectively than single-time-point measurements. Kaplan–Meier analyses demonstrated a stepwise decline in survival with increasing LDH across all categorization approaches (all log-rank p < 0.001). In multivariable Cox models, log-transformed maximum LDH within the first 72 h was the strongest independent predictor of mortality (HR = 2.2–2.6; p < 0.001), demonstrating larger effect sizes than APACHE II, SOFA, and age in fully adjusted models. GLM analysis indicated that male sex was associated with approximately 33% lower expected maximum LDH. Conclusions: Admission LDH is an independently predictive and readily obtainable prognostic biomarker for early in-hospital mortality in critically ill medical patients. LDH may complement established ICU risk assessment tools, and its integration into clinical workflows as a triage adjunct warrants further evaluation in prospective multicenter studies. Full article

(1) Background: Antibiotic co-administration during COVID-19 hospitalization is common, but evidence supporting routine use without confirmed bacterial co-infection is limited, and the impact on post-COVID recovery remains largely uninvestigated; (2) Methods: Single-center prospective observational cohort of 127 hospitalized COVID-19 adults (March 2020–December 2024) across four pandemic waves. Antibiotic exposure was the primary variable. Endpoints were 30-day mortality, ICU admission, and persistent dyspnea at three months. Multivariable logistic regression with Firth’s penalized profile likelihood 95% CI was performed; ROC analysis assessed procalcitonin (PCT) discrimination; (3) Results: Of 127 patients (median age 70.3 years; 63.8% male; 61.4% unvaccinated), 68 (53.5%) received antibiotics. Notably, 61.5% of patients with PCT ≤ 0.25 ng/mL (viral etiology likely) received antibiotics. After adjustment, antibiotic use was not independently associated with 30-day mortality (OR 0.98, 95% CI 0.27–4.05), ICU admission (OR 1.12, 95% CI 0.31–4.05), or persistent dyspnea at three months (OR 1.51, 95% CI 0.62–4.16). COVID-19 severity was the sole independent mortality predictor (OR 3.563, p = 0.018). At three months, 35.6% reported persistent dyspnea and 14.4% had CT pulmonary fibrosis; (4) Conclusions: Antibiotic exposure did not independently predict short- or long-term outcomes after adjustment for severity, while prescribing was misaligned with PCT-based bacterial probability—supporting biomarker-guided stewardship in epidemic respiratory disease. Full article

Background/Objectives: Acute-on-chronic liver failure (ACLF) is characterized by multiple organ failure and short-term mortality, and hepatic encephalopathy (HE) is its frequent complication. We investigated whether the severity of HE upon admission in patients with alcohol-related ACLF at the intensive care unit (ICU) was associated with short-term mortality. Methods: In total, 100 patients with alcohol-related ACLF and HE admitted in ICU were enrolled in the study. Laboratory biomarkers, total hospital length of stay (LOS), ICU length of stay, acute kidney injury (AKI), Acute Physiology and Chronic Health Evaluation II score, CLIF-C organ failure and Sequential Organ Failure Assessment score were tested in relation to the mortality risk. HE was assessed and divided into groups using the West Haven criteria. Results: Total hospital LOS, 7-day and 28-day mortality were significantly higher in the higher-grade HE group (p = 0.035, p = 0.031, p = 0.002, respectively). CLIF-C OF, SOFA, and APACHE II scores were significantly higher in the higher-grade HE group (p < 0.001). Kaplan–Meier survival analysis demonstrated reduced survival in patients with higher-grade HE (log-rank p < 0.001). In Cox regression analyses, AKI was associated with short-term mortality in both HE groups. Total hospital LOS and ICU length of stay were also associated with mortality, but were interpreted as post-baseline markers of clinical trajectory rather than baseline prognostic predictors. Conclusions: In patients with alcohol-related ACLF and HE, higher-grade HE was associated with poorer short-term survival. AKI and higher CLIF-C OF, SOFA and APACHE II scores were associated with poor outcomes, supporting their clinical relevance for mortality risk stratification in this population. LOS-related findings should be interpreted as markers of clinical trajectory rather than baseline prognostic predictors. Full article

Background and Objectives: The diagnostic accuracy of an artificial intelligence (AI)-derived initial 12-lead electrocardiogram (ECG) analysis was evaluated for early carbon monoxide-induced cardiomyopathy (CO-CMP) risk detection. Materials and Methods: Retrospective medical data of carbon monoxide poisoning (COP) cases between 1 January 2015 and 31 December 2024 were screened for the primary outcome: odds ratio (OR) for echocardiographically confirmed CO-CMP among those with high-risk probability score per the AI-derived model. Secondary outcomes included left ventricular ejection fraction (LVEF) and AI-derived probability score, critical care requirements, including intubation and intensive care unit (ICU) admission, and cardiac arrest events. Results: A total of 51 patients with acute COP were included in the final analysis, with 13 (25.5%) being diagnosed with CO-CMP. The LVEF in the CO-CMP group was lower than that in the non-CO-CMP group (40.00 ± 13.80% vs. 63.76 ± 6.24%, p < 0.001). The AI-derived probability score was higher in the CO-CMP group (11.3 [3.8–32.7] vs. 0.5 [0.2–2.2], p < 0.001). Among cardiac biomarkers, troponin I (2.37 [0.32–7.88] vs. 0.06 [0.06–0.95] ng/mL, p = 0.002) was higher in the CO-CMP group. Patients with CO-CMP required recurrent ventilator support (76.9% vs. 21.1%, p < 0.001) and ICU admission (92.3% vs. 42.1%, p = 0.003). In multivariable regression analysis, the AI-derived prediction model was independently associated with CO-CMP (OR 1.14; 95% confidence interval (CI) 1.02–1.27; p = 0.017; Firth-penalized OR 1.11; 95% CI 1.03–1.25; p < 0.001). Receiver operating characteristic analysis of the AI-derived model showed an area under the curve of 0.85 (95% CI 0.70–0.96) for the AI score alone and 0.92 (95% CI 0.83–0.99) for the Combined AI–cardiac marker model, with a sensitivity of 92.3% and specificity of 81.6%. Pairwise DeLong comparisons between the Combined AI model and comparator models did not reach statistical significance (Combined vs. AI-only, p = 0.092; Combined vs. cardiac markers, p = 0.052); however, the likelihood-ratio test for adding the AI probability score to the cardiac marker-only model demonstrated significant incremental information (χ² = 13.68, p < 0.001). Conclusions: AI-based ECG analysis showed exploratory diagnostic association with LV systolic dysfunction observed in suspected CO-CMP patients. Given the limited sample size, low events-per-variable ratio, and lack of external validation, these findings suggest that AI-ECG analysis may provide incremental information for early cardiac risk stratification in selected patients. Full article

Background/Objectives: Postoperative complications following adult cardiac surgery are biologically interrelated, yet most machine learning models predict single outcomes. We developed an explainable multi-output model integrating routinely collected clinical variables and patient blood management (PBM) biomarkers to predict multiple postoperative outcomes simultaneously, with complementary mono-output analyses for selected endpoints. Methods: This retrospective single-center cohort included 1414 adults undergoing cardiac surgery. In total, 513 complete cases were analyzed. Thirteen outcomes were modeled, including major binary complications and ICU/ward length of stay. An initial 80:20 train–test split was used only for algorithm screening across six candidate multi-output regressors and training-set-defined feature subsets. The selected regressor was then evaluated across five random states, and global permutation feature importance was used for multi-output explainability. Mono-output binary analyses using the selected regressor and the same training-set-only feature-selection workflow were evaluated along with accuracy, precision, recall/sensitivity, and F1-scores. Results: The Decision Tree Regressor was selected. Across five random states, global multi-output performance was R² = 0.83, MSE = 1.296, RMSE = 1.132, MAE = 0.298, and MAPE = 0.128. Based on global multi-output permutation importance, creatinine, ferritin, platelet count, estimated glomerular filtration rate, preoperative red blood cell units, and EuroSCORE II were ranked the highest. Atrial fibrillation had the lowest mono-output F1-score (0.719), whereas acute kidney injury, postoperative bleeding, infection, and 1-year hospital readmission yielded F1-scores of 0.928, 0.970, 0.963, and 0.975, respectively. Conclusions: This proof-of-concept study shows the feasibility of explainable multi-output modeling for postoperative outcomes after adult cardiac surgery using clinical and PBM variables. However, external validation is required prior to clinical use. Full article

Background: Respiratory syncytial virus (RSV) is a serious disease in older adults and is associated with various comorbidities; however, comparative data across epidemic waves, both clinically and in terms of inflammatory profiles and their diagnostic and prognostic utility, remain limited. Methods: We conducted a retrospective study of adults hospitalized with RSV infection across two epidemic waves (2022–2023 and 2024–2025). Data on clinical characteristics, comorbidities, severity scores, and outcomes were collected, and serum interleukin-6 (IL-6), C-reactive protein (CRP), and hematological parameters were analyzed and compared with those in healthy controls. Results: A total of 152 patients were included in this study (81 in wave 1 and 71 in wave 2). Patients in wave 2 were older and had a higher burden of comorbidities, although ICU admission and in-hospital mortality were similar across waves. RSV induced a consistent systemic inflammatory response in both waves, characterized by elevated IL-6 and CRP levels, neutrophilia, lymphopenia, and increased neutrophil-to-lymphocyte ratios, with no relevant inter-wave differences. All biomarkers demonstrated good diagnostic performance. The neutrophil-to-lymphocyte ratio showed the highest accuracy, while IL-6 exhibited high rule-in capacity. However, none of the evaluated biomarkers were associated with disease severity or mortality. Conclusions: RSV infection in older adults is associated with a similar inflammatory profile across waves. Although biomarkers showed strong diagnostic utility, they did not show any significant prognostic discrimination in this cohort. We suggest that disease severity is primarily associated with host-related factors, particularly comorbidities, rather than with differences in the inflammatory response, highlighting the need for improved preventive and risk-stratification strategies in this population. 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: Chronic critical illness (CCI) following acute brain injury involves persistent immune dysfunction, yet its genetic determinants remain unclear. We investigated whether the rate of T-cell receptor excision circle (TREC) depletion—a proposed marker of adaptive homeostatic resilience—is associated with the burden of rare damaging genetic variants. Methods: Whole-exome sequencing (WES) was performed on a cohort of 84 patients (64 with traumatic brain injury, 20 with stroke). In a longitudinal sub-cohort (n = 27), patients were stratified into quartiles (Q1–Q4) based on the slope of their TREC trajectories. “Qualifying variants” (QVs) were defined using strict rarity (gnomAD allele frequency ≤ 0.001) and pathogenicity criteria. Gene-level burden (collapsing) analysis and permutation-based statistical testing (10,000 iterations) were employed to evaluate genetic enrichment in the extreme quartiles. Results: While baseline TREC levels were strictly age dependent (p < 0.0001), the rate of change (TREC slope) was age independent. Rapid TREC decline (Q1) correlated with significantly higher final SOFA scores (p = 0.001) and neutrophil-to-lymphocyte ratios (p = 0.020). Rare variant burden analysis revealed that Q1 patients were significantly more likely to harbor QVs in immune-related genes compared to the Q4 recovery group (odds ratio = 8.25; permutation p = 0.016). Patients with rapid decline were enriched for QVs in putative core “housekeeping” pathways essential for T-cell maintenance and DNA repair (e.g., ERCC3, FANCM), whereas variants in recovering patients were restricted to peripheral effector or structural pathways. Conclusions: Our findings suggest, as a conceptual framework, that an individual’s ability to maintain T-cell homeostasis during critical illness is influenced by their underlying genetic buffering capacity. We propose a hypothetical “two-hit” framework where physiological stress unmasks pre-existing fragilities in core homeostatic pathways—potentially reflecting a state of functional haploinsufficiency under extreme proliferative demand—leading to accelerated immune exhaustion. These results position the TREC slope as a dynamic, age-independent biomarker of genomic resilience in the ICU. All findings are exploratory and hypothesis generating. Full article

Objective: The primary objective was to evaluate whether admission serum albumin predicts six-month all-cause mortality in older adult patients admitted to the intensive care unit (ICU) after simple fracture surgery, and to compare its predictive performance with the modified Nutrition Risk in the Critically Ill (mNUTRIC) score and the Nutrition Risk Screening 2002 (NRS-2002). The secondary objectives were to identify baseline predictors of six-month mortality and high-risk mNUTRIC classification. Methods: This retrospective cohort study included patients aged ≥65 years admitted to the ICU of a tertiary care hospital after surgery for a simple fracture between July and December 2024. Demographic data, comorbidities, admission laboratory values (including albumin, prealbumin, and 25-hydroxy vitamin D, the latter included as an adjunctive nutritional biomarker), APACHE II, SOFA, mNUTRIC, and NRS-2002 scores were recorded. Postoperative complications and admission durations were evaluated. Binomial logistic regression models were constructed for six-month all-cause mortality and nutritional risk group classification. Receiver operating characteristic (ROC) analysis with the Youden Index was performed to determine cutoff values. Results: A total of 172 patients (mean age 80.84 ± 7.72 years; 67.4% female) were analyzed. Six-month all-cause mortality was 22.7%. Serum albumin (OR 0.823, 95% CI 0.729–0.928, p = 0.002) and ICU admission duration (OR 1.413, 95% CI 1.101–1.812, p = 0.007) were independent predictors of six-month all-cause mortality, whereas mNUTRIC, NRS-2002, and vitamin D were not. Neither mNUTRIC nor NRS-2002 scores differed significantly between survivors and non-survivors. In nutritional risk group analysis, age (OR 1.117, p = 0.001) and APACHE II (OR 1.694, p = 0.001) were independent predictors of high mNUTRIC risk. Head-to-head ROC analysis for the primary outcome of six-month all-cause mortality showed that admission serum albumin (AUC 0.698, 95% CI 0.604–0.793) provided significantly better discrimination than mNUTRIC (AUC 0.570, DeLong p = 0.046) and NRS-2002 (AUC 0.550, DeLong p = 0.039). In a sensitivity model restricted to admission-time variables (albumin, age, APACHE II, vitamin D, Charlson Comorbidity Index), admission albumin remained an independent predictor (OR 0.830, 95% CI 0.747–0.923, p < 0.001) and age emerged as a further independent predictor (OR 1.062, p = 0.034). Conclusions: Serum albumin outperformed mNUTRIC and NRS-2002 in predicting six-month all-cause mortality among older adult post-fracture ICU patients. Because neither mNUTRIC nor NRS-2002 discriminated between survivors and non-survivors, these scores alone cannot be recommended as mortality-prediction tools in this orthogeriatric ICU population. Whether admission albumin adds incremental value to existing nutritional scoring in this setting requires prospective, adequately powered validation. 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: Pneumonia remains a leading cause of emergency department visits worldwide, requiring rapid and objective risk stratification. While traditional scoring systems like CURB-65 and the Pneumonia Severity Index (PSI) are well-established, there is a constant need for dynamic biomarkers reflecting the underlying pathophysiology. This study aims to investigate the prognostic value of the hemoglobin-to-lactate ratio (HLR) in predicting mortality among pneumonia patients. Methods: This retrospective cohort study included 183 adult patients diagnosed with pneumonia at a tertiary training and research hospital between October 2024 and November 2025. Demographic data, clinical findings, laboratory parameters, and prognostic scores (CURB-65, PSI) were recorded. The impact of HLR on mortality was evaluated using univariate and multivariate logistic regression, while its predictive performance was assessed via Receiver Operating Characteristic (ROC) analysis and compared with clinical scores using DeLong’s method. Results: The overall mortality rate was 32.8%. HLR values were significantly lower in the exitus group compared to survivors (4.68 vs. 6.92, p < 0.001). Multivariate analysis revealed that an HLR ≤ 5.65 was an independent predictor of mortality, associated with a 10-fold increase in risk (OR: 10.0; 95% CI: 4.15–24.19; p < 0.001). HLR demonstrated high predictive power (AUC = 0.802), comparable to CURB-65 (AUC = 0.807) and PSI (AUC = 0.829). Notably, the combined HLR + CURB-65 model provided the highest diagnostic accuracy (AUC = 0.857, p = 0.037). Conclusions: HLR is a low-cost and easily accessible biomarker for predicting mortality in pneumonia. It effectively reflects the physiological balance between tissue oxygenation and metabolic failure. Integrating HLR into clinical practice, particularly when combined with traditional scores, can enhance risk (decision of discharge, admission unit [ward, ICU], evaluation of prognosis) in the emergency department. Full article