Background: Sepsis-induced coagulopathy (SIC) and hypoalbuminemia represent distinct yet interrelated manifestations of endothelial dysfunction in sepsis. While both have been individually associated with increased mortality, their combined prognostic value remains unexplored. This study aimed to assess the relationship between the SIC score and serum albumin levels and to evaluate their integrated role in predicting mortality and bleeding risks in septic patients. Methods: We conducted a prospective observational study enrolling adult patients with community-acquired sepsis admitted to an Intermediate Medical Care Unit between January 2023 and June 2024. The primary outcome was 30-day all-cause mortality. The secondary outcome was the occurrence of ISTH-defined major bleeding. Multivariable logistic regression and Net Reclassification Improvement (NRI) analyses were performed to evaluate the predictive value of albumin when added to the SIC score. Results: A total of 413 patients were enrolled; 18.4% had a positive SIC score. The serum albumin and SIC score were inversely correlated (r = −0.189, p < 0.001). Both variables were independently associated with 30-day mortality and major bleeding. The addition of albumin significantly improved the predictive performance of the SIC score (NRI = 0.276 for mortality; NRI = 0.268 for bleeding; both p = 0.003). The cluster analysis identified distinct phenotypes based on albumin and SIC profiles, with differing clinical trajectories and transfusion needs. Conclusions: The combined assessment of the SIC score and serum albumin enhances early risk stratification in sepsis. This dual-parameter approach may support more accurate prognostication and individualized management in septic patients.

Background: Over the past few decades, emergency departments (EDs) have experienced an increasing workload. However, the variation in the types of patient accesses to these departments remains poorly understood. Objective: To evaluate the 5-year temporal trend in the volume of patients attending EDs based on the urgency of their conditions. Methods: This multicenter observational retrospective study was conducted from 1 January 2019, to 31 December 2023, across seven Italian EDs located within the same province. All patients accessing the EDs during the study period were included, totaling 1,282,735 patients. The triage code was used as an urgency index; non-urgent patients were defined as those who received a code 4 or 5 in triage, while urgent patients were defined as those who received a code 3, 2, or 1 in triage. Temporal analyses of admissions were conducted, also evaluating individual age groups to understand behavior over time. Results: From 2019 to 2023, there was a significant 10% increase in ED attendances by non-urgent patients. This increase was observed during both daytime and nighttime shifts. Notably, all age groups showed an increase in non-urgent patients, except for pediatric patients aged 0 to 14. Conclusions: Over the past 5 years, there has been a consistent upward trend in ED attendances by non-urgent patients. Healthcare policies should consider implementing strategies to manage or mitigate the overload in EDs, particularly related to non-urgent patient accesses.

Background/Objectives: Healthcare-associated infections (HAIs), including sepsis, represent a major challenge in clinical practice owing to their impact on patient outcomes and healthcare systems. Large language models (LLMs) offer a potential solution by analyzing clinical documentation and providing guideline-based recommendations for infection management. This study aimed to evaluate the performance of LLMs in extracting and assessing clinical data for appropriateness in infection prevention and management practices of patients admitted to an infectious disease ward. Methods: This retrospective proof-of-concept study analyzed the clinical documentation of seven patients diagnosed with sepsis and admitted to the Infectious Disease Unit of San Bortolo Hospital, ULSS 8, in the Veneto region (Italy). The following five domains were assessed: antibiotic therapy, isolation measures, urinary catheter management, infusion line management, and pressure ulcer care. The records, written in Italian, were anonymized and paired with international guidelines to evaluate the ability of LLMs (ChatGPT-4o) to extract relevant data and determine appropriateness. Results: The model demonstrated strengths in antibiotic therapy, urinary catheter management, the accurate identification of indications, de-escalation timing, and removal protocols. However, errors occurred in isolation measures, with incorrect recommendations for contact precautions, and in pressure ulcer management, where non-existent lesions were identified. Conclusions: The findings underscore the potential of LLMs not merely as computational tools but also as valuable allies in advancing evidence-based practice and supporting healthcare professionals in delivering high-quality care.

OBJECTIVES: Evaluate the predictive and prognostic performance of the Phoenix Sepsis Criteria (PSC) and Phoenix Sepsis Score (PSS) compared with International Pediatric Sepsis Consensus Conference (IPSCC) criteria and other organ dysfunction scores in children admitted to the PICU with suspected infection. DESIGN: Multicenter, prospective cohort study. SETTING: Eight PICUs within the Italian Network of PICU Study Group (TIPNet). PATIENTS: Patients younger than 18 years admitted with suspected infection (from February 2022 to April 2024). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Vital signs, organ dysfunction markers, and organ support requirements were collected during day 1 and day 2 of PICU admission. Sepsis was assessed using IPSCC criteria and PSC. IPSCC Severe Sepsis, PSS, Phoenix-8, Pediatric Logistic Organ Dysfunction-2 (PELOD-2), pediatric Sequential Organ Failure Assessment, and Pediatric Multiple Organ Dysfunction Score were calculated as organ dysfunction scores. Sepsis criteria predictive performance was assessed using sensitivity and positive predictive value (PPV). Organ dysfunction scores prognostic performance was assessed using the area under the precision-recall curve (AUPRC). Primary outcome was PICU mortality. Among 687 patients, PSC showed higher predictive performance than IPSCC sepsis criteria, with improved sensitivity and PPV for mortality on day 1 (PSC: sensitivity, 96.4%; 95% CI, 95.0–97.8%; PPV, 7.6%; 95% CI, 5.6–9.6% and IPSCC: sensitivity, 82.1%; 95% CI, 79.3–85.0%; PPV, 6.2%; 95% CI, 4.4–8.0%) and day 2 (PSC: sensitivity, 100.0%; 95% CI, 100.0–100.0%; PPV, 10.0%; 95% CI, 7.6–12.5% and IPSCC: sensitivity, 75.0%; 95% CI, 71.5–78.5%; PPV, 9.0%; 95% CI, 6.7–11.3%). PELOD-2 exhibited the highest AUPRC for mortality (day 1, 0.45; 95% CI, 0.26–0.63 and day 2, 0.59; 95% CI, 0.38–0.77). IPSCC Severe Sepsis score was outperformed by all other organ dysfunction scores, including PSS and Phoenix-8. All prognostic performances improved from day 1 to day 2. CONCLUSIONS: PSC and PSS performed superior to IPSCC criteria in diagnosing and prognosticating pediatric sepsis, with improved performance at day 2 of PICU admission. This study first validated PSC and PSS in a European cohort.

Background: Emergency department (ED) triage systems aim to prioritize patients based on clinical severity, ensuring timely intervention for high-risk cases. Recently, the National Early Warning Score (NEWS) has been proposed as an alternative to traditional triage systems, but its efficacy across multiple clinical outcomes remains unclear. This study aimed to compare the predictive performance of the NEWS and the Manchester Triage System (MTS) across multiple clinical outcomes. Methods: We conducted a retrospective, single-center study at Merano Hospital, Italy, from 1 June 2022 to 30 June 2023, comparing the performance of the NEWS and the Manchester Triage System (MTS). All adult ED patients (≥18 years) were included, while exclusions applied to those on fast-track pathways, non-residents, and pregnant patients. Primary outcomes included 30-day mortality, hospitalization, and ICU admission. A random 5% subgroup was analyzed for secondary outcomes, including the need for life-saving interventions (LSIs), physician-defined clinical priority, and severity. Predictive performance was assessed using Receiver Operating Characteristic (ROC) curves, area under the ROC curve (AUROC) comparisons, and Decision Curve Analysis (DCA). Results: Among 27,238 patients, the NEWS predicted 30-day mortality more accurately than the MTS (AUROC 0.745 vs. 0.701, p < 0.001). However, the MTS outperformed the NEWS for hospitalization (AUROC 0.733 vs. 0.609, p < 0.001), ICU admission (AUROC 0.862 vs. 0.672, p < 0.001), and all secondary outcomes. DCA further confirmed MTS’s superiority across clinically relevant ED probability thresholds (20–40%). Conclusions: The NEWS, while effective for predicting mortality, it is inadequate in comprehensive triage decision-making. The MTS remains the superior system for prioritizing high-risk patients based on clinical severity. Rather than replacing triage with the NEWS, efforts should focus on refining existing systems to improve risk stratification. Future multi-center prospective studies are necessary to validate these findings.