Search Results (3,116)

Unlike reactive systems, mechanical ventilation controlled by CO₂ concentration operates at a target efficiency that dynamically increases whenever the target CO₂ level is exceeded. This approach eliminates the typical ‘dead-time’ and prevents air quality degradation by ensuring the system adjusts its performance immediately in response to concentration changes. In this work, the study focuses on the development and evaluation of data-driven predictive models for near-term indoor CO₂ forecasting that can be integrated into pre-occupancy ventilation strategies, rather than designing a complete control scheme. Experimental data were collected over four months in a 48 m² smart laboratory configured as an open-plan office, where a heterogeneous IoT sensing architecture logged synchronized time-series measurements of CO₂ and microclimate variables (temperature, relative humidity, PM_2.5, TVOCs), together with acoustic noise levels and appliance-level energy consumption used as indirect occupancy-related signals. Raw telemetry was transformed into a 22-feature state vector using a structured feature engineering method incorporating z-score standardization, cyclic time encodings, multi-horizon CO₂ lags, rolling statistics, momentum features, and non-linear interactions to represent temporal autocorrelation and daily periodicity. The study benchmarks multiple regression paradigms, including simple baselines and ensemble methods, and found that an automated multi-level stacked ensemble achieved the highest predictive fidelity for short-term forecasting, with an Mean Absolute Error (MAE) of 32.97 ppm across an observed CO₂ range of 403–2305 ppm, representing improvements of approximately 24% and 43% over Linear Regression and K-Nearest Neighbors (KNN), respectively. Temporal diagnostics showed strong phase alignment with observed CO₂ rises during occupancy transitions and statistically reliable prediction intervals. Five-fold walk-forward cross-validation confirmed the temporal stability of these results, with top models achieving consistent R² values of 0.93–0.95 across Folds 2–5. These results demonstrate that, within a single-room university laboratory setting, historical sensor data from low-cost IoT devices can support accurate short-term CO₂ forecasting, providing a predictive layer that could support future proactive ventilation scheduling aimed at reducing CO₂ lag at the start of occupancy while avoiding unnecessary ventilation runtime. Generalization to other building types and occupancy profiles requires further validation. Full article

Introduction: Accurately meeting the energy requirements of patients in intensive care units (ICUs) is crucial to prevent catabolism, muscle loss, and complications. We assessed their energy needs in this study using indirect calorimetry (IC) and predictive formulas, comparing the results with delivered energy intake and evaluating agreement. Materials and Methods: A total of 38 mechanically ventilated patients in seven ICUs at Kayseri City Hospital were included; eligible patients were ≥18 years old and mechanically ventilated for at least 24 h. Disease severity and nutritional risk were evaluated using validated indices (prognostic nutritional index (PNI) and Modified Nutrition Risk in the Critically Ill (mNUTRIC)), and basal energy expenditure (BEE) was measured by IC and calculated using the Harris–Benedict (HB) and ESPEN formulas. IC measurements lasted 15 min under resting conditions in conscious patients and, according to acute phase criteria, in unconscious patients in a quiet, temperature-controlled environment. Nutrition was provided enterally or parenterally based on patient condition and disease severity. Agreement between IC and predictive formulas was assessed using Bland–Altman analysis, a statistical method that evaluates agreement between two measurement techniques. Results: Estimated energy requirements differed significantly from delivered energy intake (p < 0.001). IC-derived values were significantly lower than those estimated by the HB equation and ESPEN recommendations (p < 0.001), suggesting that predictive equations may overestimate energy requirements in this population. By contrast, delivered energy intake was lower than IC-measured values, with a mean difference of approximately 503 kcal, indicating a potential risk of underfeeding in clinical practice. Weak correlations were observed between methods (IC vs. HB: r = 0.35, p = 0.003; IC vs. ESPEN: r = −0.21, p = 0.02), indicating limited agreement between predictive equations and IC measurements, and Passing–Bablok regression analysis further supported this lack of agreement between methods. Conclusions: The energy intake delivered to patients was lower than the calculated values. Indirect calorimetry is important for accurately monitoring and determining energy requirements based on delivered energy intake, and further research in this area is needed. These findings highlight the importance of individualized monitoring of energy expenditure in critically ill patients and suggest that reliance solely on predictive equations may lead to clinically relevant discrepancies in energy delivery. Full article

Background/Objective: Prehabilitation aims to improve physiological reserve before surgery to enhance postoperative outcomes. Multiple systematic reviews have evaluated preoperative interventions in adult cardiac surgery; however, variability in scope, methodological quality, and overlap of primary trials complicates interpretation. The aim of this study is to synthesise and critically appraise evidence from systematic reviews and meta-analyses evaluating prehabilitation interventions in adults undergoing cardiac surgery. No funding was received for this study. Methods: We conducted an umbrella systematic review following a prospectively registered protocol (PROSPERO: CRD420261292354) and PRISMA 2020 guidance. PubMed, Web of Science, and Scopus were searched from inception to 31 December 2025. Eligible reviews included adults (≥18 years) undergoing cardiac surgery, evaluated and compared preoperative inspiratory muscle training (IMT), respiratory muscle training, and exercise-based, educational, or multimodal prehabilitation with usual care or sham intervention. Reviews focused solely on postoperative interventions or non-cardiac surgery were excluded. Methodological quality was assessed using AMSTAR-2. Certainty of evidence was evaluated using GRADE. Overlap of primary studies was quantified using the Corrected Covered Area (CCA). A structured narrative synthesis with a direction-of-effect framework was applied. Results: Eighteen systematic reviews (published 2012–2025) were included, comprising 46 unique primary studies and more than 6674 participants (exact totals unavailable due to incomplete reporting in at least one review). Overall overlap was high (CCA 12.5%). Respiratory-focused prehabilitation, particularly IMT, demonstrated consistent reductions in postoperative pulmonary complications (PPCs) (risk ratios approximately 0.42–0.53), pneumonia (RR ~0.44–0.45), and atelectasis (RR ~0.49–0.59), favouring prehabilitation over usual care. Hospital length of stay was reduced by approximately 1.5–3 days across multiple reviews. Inspiratory muscle strength improved consistently (mean difference ~+12 to +17 cmH₂O). Effects on ICU length of stay and mechanical ventilation duration were inconsistent or non-significant. Exercise-based programmes improved functional capacity (6 min walk distance increase ~50–75 m) and showed modest reductions in hospital stay, but heterogeneity was substantial. No intervention demonstrated a consistent reduction in postoperative mortality. Evidence was limited by clinical heterogeneity, performance bias in primary trials, inconsistent outcome definitions, and high overlap of key IMT trials across reviews. Mortality outcomes were underpowered. Conclusions: Preoperative IMT provides evidence for reducing pulmonary complications and shortening hospital stays in adult cardiac surgery. Exercise-based prehabilitation improves functional capacity but requires further high-quality, standardised trials. Integration of respiratory prehabilitation into cardiac surgical pathways appears supported by the current evidence. Full article

In intensive care units, large-scale clinical time-series data are continuously accumulated through electronic medical records and bedside monitoring systems. However, direct utilization of such data for clinical decision-making remains challenging due to irregular sampling, pervasive missingness, unstructured diagnostic information, and incomplete ICD labeling. Automated ICD coding constitutes an extreme multi-class classification problem with thousands of long-tailed categories, while intervention prediction tasks, such as mechanical ventilation management, involve rare transition events and severe class imbalance. To address these challenges, we propose CAGE, a hierarchical Clinical Decision Support System framework that integrates diagnosis, time-series signals, and intervention prediction. The framework first infers admission-level diagnostic context using a partial-label Automated ICD Coding module that combines DCNv2 with an Adaptive CLPL loss, producing probability-weighted diagnostic embeddings. These embeddings are subsequently fused with ICU time-series tensors and processed by a multi-branch Temporal Convolutional Network equipped with an ICD-conditioned gating mechanism to predict future ventilation state transitions. The experimental results demonstrate that DCNv2 achieves consistent superiority across all hit@k and probability concentration metrics for ICD coding. For intervention prediction, the proposed method substantially outperforms existing baselines, achieving a Macro-AUC of 98.2, Macro-AUPRC of 77.4, and F1-score of 79.4. These findings indicate that reinjecting diagnostic context as a conditioning variable, together with imbalance-aware loss design, effectively enhances rare-event detection and improves the practical applicability of clinical decision support systems. Full article

Background: Critically ill cardiac patients who require invasive mechanical ventilation represent a high-risk population with persistently elevated in-hospital mortality, despite advances in cardiovascular and critical care management. Real-world data describing clinical profiles and prognostic patterns in this population remain limited. Objectives: The aim of this study was to characterize clinical profiles and prognostic patterns among critically ill cardiac patients requiring invasive mechanical ventilation and to identify variables associated with in-hospital mortality. Methods: We conducted a five-year retrospective observational cohort study, including 492 adult patients admitted to a tertiary cardiovascular intensive care unit who required invasive mechanical ventilation. The demographic characteristics, cardiovascular risk factors, primary cardiac diagnoses, major in-hospital complications, duration of mechanical ventilation, length of hospital stay, and in-hospital mortality were analyzed. Results: The overall in-hospital mortality was 53.9%. Acute myocardial infarction was the most frequent primary diagnosis. Advanced age, diabetes mellitus, cardiogenic shock, acute renal dysfunction, hepatic dysfunction and prolonged hospitalization were significantly associated with increased mortality (p < 0.05 for all comparisons). Cardiogenic shock showed the strongest association (p < 0.001). Ventilator-associated respiratory infections occurred in 16.9% of patients, and were associated with a prolonged hospital stay (p < 0.05), without a statistically significant association with mortality. Conclusions: Critically ill cardiac patients requiring invasive mechanical ventilation exhibit distinct high-risk clinical profiles characterized by advanced age, cardiogenic shock, metabolic comorbidities, and the development of multi-organ dysfunction. These findings highlight prognostic patterns that may support risk stratification and generate hypotheses for future prospective studies in cardiac intensive care. Full article

Background: Sepsis remains a major global health challenge, associated with high mortality, prolonged intensive care unit (ICU) stays, and disproportionate healthcare costs. CytoSorb hemoadsorption offers a potential adjunct in septic shock, but real-world cost-effectiveness data in Diagnosis-Related Group (DRG)-based systems are limited. This study aimed to evaluate the clinical and economic impact of CytoSorb therapy in ICU patients with septic shock at a high-volume Swiss tertiary care center. Methods: A retrospective observational cohort study (2020–2023) was conducted at Kantonsspital Münsterlingen. Among 246 septic shock patients, 142 received CytoSorb therapy and 104 standard care. Patients were grouped according to treatment exposure. Baseline characteristics as well as ICU course variables, including sepsis origin, Simplified Acute Physiology Score (SAPS) II, and the Nine Equivalents of Nursing Manpower Use Score (NEMS), were compared between groups. Clinical outcomes included ICU/hospital length of stay (LOS) and duration of mechanical ventilation. Economic analysis included DRG-based revenue, direct case-related hospital costs, and net financial results. Results: CytoSorb-treated patients had significantly higher SAPS II scores at baseline. Despite higher initial acuity, this group showed a significantly shorter ICU LOS (median 408.5 vs. 554.5 h; p = 0.001), reduced hospital LOS (23.5 vs. 30.0 days; p = 0.008), and lower nursing workload (>20% NEMS point reduction; p = 0.015). Survivors treated with CytoSorb had significantly shorter ventilation durations (164.0 vs. 336.0 h; p = 0.014). Total hospital costs were not significantly different between groups; however, CytoSorb patients achieved a significantly better net financial result (CHF 17,125 vs. –1930; p = 0.025), particularly in the abdominal and pneumogenic sepsis subgroups. Conclusions: This study provides the first real-world evidence for the cost-effectiveness of CytoSorb hemoadsorption in septic shock, showing reduced ICU length of stay and improved financial outcomes, without increasing treatment costs or nursing workload. These findings challenge the perception of hemoadsorption as a cost driver and highlight its potential to optimize resource use in critical care. Further multicenter studies are needed to inform reimbursement strategies and integration into sepsis treatment protocols. Full article

Background: Length of stay (LOS) reflects healthcare utilization but may also capture patient clinical trajectories. We investigated the relationship between LOS categories, organ support requirements, and in-hospital mortality. Methods: This retrospective observational study included 1332 consecutive adult ICU patients in a tertiary-care center. ICU LOS patterns were categorized using median-based and predefined cutoffs. Multivariable logistic regression was used to identify independent predictors of in-hospital mortality. Results: Prolonged ICU LOS was associated with higher crude mortality (61.0% vs. 43.5%, p < 0.001). However, in LOS-adjusted models, mortality was independently associated with mechanical ventilation (aOR 29.89, 95% CI 17.92–49.86), inotropic support (aOR 4.94, 95% CI 3.50–6.97), hemodialysis (aOR 5.43, 95% CI 2.52–11.72), older age, and diabetes mellitus. Prolonged LOS was not independently associated with mortality (aOR 0.93, p = 0.630). Conclusions: LOS reflects underlying disease severity rather than acting as an independent driver of mortality. Integrating LOS pattern assessment with markers of organ dysfunction may improve risk stratification and resource planning in hospitalized populations. Full article

Background: Thoracentesis is pivotal in managing pleural effusion (PE), particularly in invasive mechanical ventilation (IMV), with documented improvements in respiratory mechanics, oxygenation, and hemodynamic parameters. However, its efficacy may vary based on effusion type and drained volume. Methods: A retrospective longitudinal study was conducted at a high-complexity care center in Cali, Colombia (2019–2024), including 93 (IMV) patients who underwent therapeutic thoracentesis (TT). Respiratory and hemodynamic parameters were assessed before and up to 24 h post-procedure. Stratified analysis was performed by drained volume, fluid type, and left ventricular ejection fraction (LVEF). Results: TT yielded significant improvements in fraction of inspired oxygen (FiO₂) (−4%), positive end expiratory pressure (PEEP) (−0.5 cmH₂O), and Oxygen arterial Pressure Index/Inspired Oxygen Fraction (PaO₂/FiO₂-ratio) (+27.1), with greater impact for volumes ≥500 mL and transudative PE. Patients with LVEF ≤ 40% showed increased mean arterial pressure (MAP) and PaO₂. Complication rates were low (<4%). Conclusions: TT is safe and effective in critically ill IMV patients, particularly for transudative PE and drained volumes ≥500 mL, as well as in subjects with LVEF ≤ 40%. Its positive impact on oxygenation and ventilation supports its therapeutic utility in critical care. Full article

Background/Objectives: Patients with adrenal insufficiency (AI) are at an increased risk of adverse events (AEs) during cardiovascular hospitalization. However, the association between AI and takotsubo cardiomyopathy (TCM) remains unclear. We investigated the association between AI and cardiovascular outcomes in patients with TCM. Methods: We analyzed data on patients with TCM included in the 2019 Nationwide Readmissions Database to compare in-hospital outcomes between patients with and without AI. The primary outcome measure was inpatient mortality. Secondary outcomes included the odds of all-cause 90-day readmission, acute kidney injury (AKI), mechanical ventilation use, vasopressor use, cardiogenic shock, length of stay (LOS), and total hospitalization charges (THC). Multivariate regression models were used to adjust for confounding variables. Results: Among 30,987 cases, 0.59% (n = 183) had concomitant AI. AI was associated with higher odds of in-hospital mortality (adjusted odds ratio [aOR] 3.32, 95% confidence interval [CI] 1.43–7.74, p = 0.005), cardiogenic shock (aOR 5.28, 95% CI 3.16–8.82, p < 0.001), mechanical ventilation use (aOR 3.20, 95% CI 1.78–5.74, p < 0.001), AKI (aOR 1.96, 95% CI 1.11–3.48, p = 0.021), vasopressor use (aOR 4.59, 95% CI 1.56–13.47, p = 0.006), longer LOS (6.84 vs. 3.67 days, p < 0.001), and higher THC ($97,419 vs. $54,574, p < 0.001). Additionally, AI was associated with lower odds of all-cause 90-day readmissions (aOR 0.44, 95% CI 0.25–0.79, p = 0.006). Conclusions: Among patients with TCM, AI was associated with higher odds of fatal and non-fatal adverse events. Further studies are required to confirm these findings and better understand how to improve outcomes in this high-risk population. Full article

Background and Objectives: To identify predictors of pulmonary infection in critically ill patients after abdominal surgery and to develop an early postoperative risk stratification model. Materials and Methods: Medical records of ICU patients after abdominal surgery (January 2016–June 2024) with Acute Physiology and Chronic Health Evaluation II (APACHE II) scores ≥10 were retrospectively analyzed. Patients were categorized according to the presence or absence of pulmonary infection. Candidate variables were screened using LASSO regression, followed by multivariate logistic regression to identify independent predictors. A nomogram-based prediction model was constructed and internally validated. Results: Among 4852 patients, 390 (8.0%) developed pulmonary infections. Overall, 8 independent predictors were identified: Male sex (vs. female) (OR 1.509, 95% CI: 1.091–2.087, p = 0.013), chronic obstructive pulmonary disease (OR 4.139, 95% CI: 2.872–5.966, p < 0.001), atrial fibrillation (OR 2.320, 95% CI: 1.366–3.939, p = 0.002), hypertension (OR 1.869, 95% CI: 1.372–2.539, p < 0.001), chronic renal insufficiency (OR 2.412, 95% CI: 1.143–5.091, p = 0.021), preoperative total bilirubin (OR 1.003, 95% CI: 1.001–1.004, p = 0.002), rectal surgery (OR 0.354, 95% CI: 0.151–0.830, p = 0.017), and invasive mechanical ventilation duration > 6 h (OR 2.206, 95% CI: 1.628–2.990, p < 0.001). The nomogram demonstrated good discrimination (AUC: 0.734 95% CI: 0.698–0.770) and calibration. Conclusions: This study identified 8 independent predictors of pulmonary infection and developed an internally validated early postoperative risk stratification model with satisfactory performance. The model may assist clinicians in identifying high-risk patients and guiding timely preventive strategies in ICU practice. Full article

This study experimentally investigates the combustion behavior of RP-3 aviation kerosene pool fires (300~800 mm) within a confined space, specifically focusing on the complex interaction between buoyancy-driven plumes and mechanical negative pressure ventilation. By integrating high-precision mass loss measurements with multiple characteristic parameters, this research uniquely characterizes the transition of energy feedback mechanisms under confined suction flow. Results show that ventilation enhances combustion intensity and compresses the fire cycle. For an 800 mm pool, the peak mass loss rate rose by 57.1%, from 16.71 g/s to 26.25 g/s. This enhancement stems from boundary layer thinning, which transitions the combustion from diffusion-controlled to kinetics-controlled. Ventilation also induces severe flame tilt with a non-monotonic trend. The tilt angle peaks at 84° for 600 mm pools but drops to 64° at 800 mm as buoyancy momentum increases. Additionally, an energy contrast of vertical cooling and horizontal heating was observed. Axial peak temperatures decreased by 20%, while downwind thermal radiation flux increased by up to 125%. The ventilation system essentially acts as a directional energy projector, shifting heat loads toward the downwind region. These findings support the optimization of fire safety and detection designs for industrial ventilation systems. This study experimentally investigates the combustion behavior of RP-3 aviation kerosene pool fires (300–800 mm) within a confined space, specifically focusing on the complex interaction between buoyancy-driven plumes and mechanical negative pressure ventilation. By integrating high-precision mass loss measurements with multi-point thermal and imaging diagnostics, this research uniquely characterizes the transition of energy feedback mechanisms under confined suction flow. Full article

Background/Objectives: Nutrition is essential to outcomes in critically ill children; however, optimal timing, route, and composition of feeding remain uncertain. Prior studies demonstrate considerable variability in study design, patient populations, and outcome measures, limiting comparability. This review synthesizes international pediatric intensive care unit (PICU) nutrition studies evaluating timing, route, and content of nutritional interventions and summarizes associated clinical outcomes and nutritional adequacy. Methods: A comprehensive scoping review was conducted using the PICOS framework. PubMed and Embase databases were searched for studies published between 2015 and 2025 enrolling critically ill children ≤21 years old admitted to PICUs. Eligible studies assessed timing (early vs. late enteral nutrition), nutritional composition, or feeding route (enteral vs. parenteral). Screening and full-text review were performed independently by two reviewers using Covidence, with discrepancies resolved by a third reviewer. Quality assessment used STROBE. The protocol was registered with PROSPERO. Results: Of 652 identified records, 30 studies met inclusion criteria. Studies were conducted primarily in the United States (27%), with additional contributions from Spain and Brazil (10% each) and several other countries. Study designs included randomized controlled trials (27%) and observational studies (73%). Interventions examined feeding route (14%), nutritional content (38%), and timing (48%). Frequently reported outcomes included feeding intolerance or adverse events, duration of mechanical ventilation, time to nutrition goals, PICU length of stay, mortality, and nutritional adequacy. Conclusions: The contemporary PICU nutrition literature demonstrates persistent heterogeneity in practice and outcomes. This review identifies ongoing gaps in timing, delivery, and adequacy of nutritional support. Full article

Gas concentration series in coal mining faces are jointly affected by multiple coupled factors, including geological conditions, mining disturbances, ventilation organization, and gas drainage intensity, and therefore exhibit pronounced nonstationarity, strong fluctuations, spatiotemporal correlations across multiple monitoring points, and occasional abrupt spikes. To address these challenges, this study proposes a gas concentration prediction and early-warning method that integrates CEEMDAN–SST with GraphPINN-TimesFM (Graph Physics-Informed Neural Network–Time Series Foundation Model). First, based on multi-source monitoring data such as wind speed, gas concentrations at multiple monitoring points, and equipment operating status, anomaly removal, operating-condition segmentation, and change-point detection are performed to construct stable operating-state labels. Feature selection is then conducted by combining optimal time-lag correlation, Shapley value contribution, and dynamic time warping. Second, WGAN-GP is employed to augment samples from minority operating conditions, while CEEMDAN–SST is used to decompose and reconstruct the target series so as to reduce the interference of nonstationary noise and enhance sequence predictability. On this basis, TimesFM is adopted as the backbone for long-sequence forecasting to capture long-term dependency features in gas concentration evolution. Furthermore, GraphPINN is introduced to embed the topological associations among monitoring points, airflow transmission delays, and convection–diffusion mechanisms into the training process, thereby enabling collaborative modeling that integrates data-driven learning with physical constraints. Finally, the predictive performance, early-warning capability, and interpretability of the proposed model are systematically evaluated through regression forecasting, warning discrimination, and Shapley-based interpretability analysis. The results demonstrate that the proposed method can effectively improve the accuracy, robustness, and physical consistency of gas concentration prediction under complex operating conditions, thereby providing a new technical pathway for gas over-limit early warning and safety regulation in coal mining faces. Full article

Background/Objectives: Central line-associated bloodstream infections (CLABSIs) remain a leading healthcare-associated infection in intensive care units (ICUs), yet independent risk factors and evidence-based catheter duration thresholds have not been defined through analytical study designs in settings with endemic multidrug-resistant organisms (MDROs). Methods: A retrospective case–control study was conducted in the ICU of a tertiary teaching university hospital in western Türkiye (January 2019–December 2024). Cases (n = 74) were patients with confirmed CLABSIs per CDC/NHSN criteria; controls (n = 148) were randomly selected central venous catheter (CVC)-bearing patients without CLABSIs. A reduced multivariate logistic regression model (seven variables; events-per-variable ratio 10.6) identified independent risk factors. Results: In multivariate analysis, catheter duration (adjusted OR: 1.19 per day; 95% CI: 1.13–1.24; p < 0.001), renal replacement therapy (aOR: 3.66; 95% CI: 1.68–7.95; p = 0.001), vasopressor support (aOR: 3.04; 95% CI: 1.50–6.17; p = 0.002), APACHE-II score (aOR: 1.07 per point; 95% CI: 1.02–1.11; p = 0.002), lower Glasgow Coma Scale (aOR: 0.86 per point; 95% CI: 0.78–0.94; p = 0.002), mechanical ventilation (aOR: 2.48; 95% CI: 1.24–4.95; p = 0.010), and total parenteral nutrition (aOR: 2.33; 95% CI: 1.12–4.86; p = 0.024) were independently associated with CLABSI. The model demonstrated good discrimination (C-statistic: 0.864) and calibration (Hosmer–Lemeshow p = 0.425). Kaplan–Meier analysis showed CLABSI-free survival declining from 98.9% at day 7 to 42.9% at day 21 (log-rank p < 0.001); these within-study estimates reflect relative risk patterns given the artificial 1:2 case-to-control ratio. Receiver operating characteristic (ROC) analysis identified day 13 as an exploratory optimal cutoff (AUC: 0.818; 95% CI: 0.762–0.874; sensitivity: 77.0%; specificity: 74.3%). CLABSI-attributable ICU mortality was 20.3% (47.3% vs. 27.0%; p = 0.004). Late-onset CLABSIs (>10 days) were dominated by Gram-negative pathogens (68.3%) versus 35.7% in early-onset infections (Fisher’s exact p = 0.012), with Acinetobacter baumannii as the predominant organism (27.0%; 83.3% carbapenem-resistant). Conclusions: Each additional catheter-day is independently associated with a 19% increment in CLABSI odds, with an exploratory critical threshold at day 13 beyond which enhanced surveillance measures should be considered, pending external validation. Full article

Background/Objectives: Ventilator weaning imposes profound hemodynamic stress, unmasking cardiopulmonary vulnerability. Since conventional predictors of post-tracheostomy weaning failure remain elusive, biomarker-driven risk stratification offers a translational approach. We evaluated the prognostic utility of admission N-terminal pro-B-type natriuretic peptide (NT-proBNP) as an early triaging tool for weaning failure and explored its therapeutic implications alongside optimal tracheostomy timing. Methods: In this large-scale retrospective cohort study, we analyzed 707 critically ill patients who underwent tracheostomy in a medical intensive care unit. We investigated the association between baseline NT-proBNP levels—measured as a molecular surrogate of cardiovascular stress at ICU admission; echocardiographic parameters; and weaning outcomes. Multivariable logistic regression analysis was utilized to identify independent pathophysiological predictors associated with weaning failure. Results: Patients experiencing weaning failure exhibited significantly elevated admission NT-proBNP levels compared to those successfully weaned (3077.0 vs. 1410.0 pg/mL, p < 0.001). High admission NT-proBNP (>3271 pg/mL) was independently associated with an increased risk of weaning failure (adjusted odds ratio [aOR] 2.86, 95% confidence interval [CI] 1.81–4.53, p < 0.001). Conversely, an early clinical intervention—tracheostomy performed within 10 days of mechanical ventilation initiation—was associated with a significantly lower risk of weaning failure (aOR 0.55, 95% CI 0.35–0.87, p = 0.010). Furthermore, elevated biomarker levels strongly correlated with prolonged intensive care unit stays and higher 90-day mortality. Conclusions: Admission NT-proBNP serves as a powerful biomarker associated with cardiopulmonary vulnerability from the earliest stages of critical illness. Integrating this diagnostic biomarker with interventional strategies like optimal tracheostomy timing has significant prognostic implications. This biomarker-guided approach facilitates personalized risk stratification from ICU admission, potentially optimizing weaning pathways for mechanically ventilated patients. Full article