Search Results (10,548)

Background: Atrial fibrillation (AF) is common among intensive care unit (ICU) patients and is associated with increased mortality, prolonged length of stay (LOS), and greater resource utilization. Widely used AF risk scores were developed for stable outpatient populations and have limited applicability in critically ill patients. This study aimed to (1) characterize ICU patients with AF, (2) develop and temporally externally validate machine learning models to predict ICU mortality and ICU LOS, and (3) identify early clinical factors associated with these outcomes using interpretable methods. Methods: Adult ICU patients with AF from MIMIC-IV (n = 20,058) were used for model development with grouped cross-validation, and MIMIC-III (n = 11,475) served as a temporal external validation cohort. Predictors included demographics, admission characteristics, vital signs, laboratory values, vasoactive support, and AF-related medications available within the first 24 h of ICU admission. Eight classification algorithms were evaluated for ICU mortality, and six regression algorithms were evaluated for ICU LOS. Discrimination was primarily assessed using the area under the receiver operating characteristic curve (AUC) and average precision (AP), with additional threshold-dependent metrics reported to characterize operating-point behavior under low event prevalence. Probability-threshold optimization using out-of-fold predictions was applied to the primary mortality model. LOS performance was evaluated using mean absolute error (MAE), root mean squared error (RMSE), and the coefficient of determination (R²). Model interpretability was assessed using SHapley Additive exPlanations (SHAP). Results: The median age was 75 years, and ICU mortality was 8.9%. For mortality prediction, the XGBoost model demonstrated preserved discrimination on temporal external validation (MIMIC-III) (AUC = 0.743; AP = 0.226). At the default probability threshold (0.50), recall and F1 scores were low due to low event prevalence; applying a prespecified F1-optimized threshold derived from the development cohort improved sensitivity while maintaining overall discrimination. For ICU LOS, models explained little variance on temporal validation; LightGBM performed best, but the explained variance was low (MAE = 88.9 h; RMSE = 163.9 h; R² = 0.038), indicating that the first 24-h structured data provide an insufficient signal to accurately predict ICU LOS, likely due to downstream clinical and operational factors. SHAP analysis identified clinically plausible predictors of mortality and prolonged ICU stay, including reduced urine output, renal dysfunction, metabolic derangement, hypoxemia, early vasopressor use, advanced age, and admission pathways. Full article

Background/Objectives: The Global Leadership Initiative on Malnutrition (GLIM) recently updated its inflammation criterion through a Delphi consensus to standardize its assessment. This study aimed to assess the impact of these new recommendations on the concurrent and predictive validity of the GLIM criteria in hospitalized medical patients. Methods: This post hoc analysis re-evaluated a previously published cohort of 119 hospitalized patients with acute medical conditions, originally assessed using the GLIM criteria and the Subjective Global Assessment (SGA) as the reference standard. Inflammation was redefined according to the 2024 GLIM Delphi consensus, and the concurrent and predictive validity of the modified GLIM criteria (GLIM-I) were examined. Receiver operating characteristic (ROC) curves were used to compare the discriminative ability of SGA, original GLIM, and GLIM-I to predict prolonged hospital stay. Results: With the updated inflammation definition, all patients met the etiologic criterion, increasing malnutrition prevalence from 41.7% to 52.2%. GLIM-I showed a sensitivity of 78.0% and specificity of 67.7% versus SGA, not reaching the predefined ≥80% threshold for concurrent validity. Predictive validity was maintained (adjusted odds ratio (OR) = 3.40; 95% CI: 1.31–8.83). SGA achieved the highest discriminative ability (area under the curve (AUC) = 0.783; 95% CI: 0.693–0.874), significantly outperforming the original GLIM (AUC = 0.723; 95% CI: 0.616–0.830; p = 0.049). GLIM-I showed similar performance (AUC = 0.731; 95% CI: 0.620–0.843; p = 0.727). Conclusions: SGA should continue to be considered the method of choice for nutritional diagnosis in hospitalized medical patients. Further research is needed to determine how the new inflammation criteria influence the validity of the GLIM framework in other clinical contexts before their widespread implementation. Full article

Background: Pediatric heart transplantation (HTx) is the standard therapy for end-stage heart failure in children, and the use of durable left ventricular assist devices (LVADs) as a bridge to transplant is increasing. However, comparative long-term data for LVAD-bridged versus directly transplanted pediatric recipients remain limited. In this study, we aimed to compare the early and long-term outcomes of pediatric heart transplantation with and without LVAD bridging. Methods: We retrospectively reviewed all pediatric patients who underwent orthotopic HTx at our institution between 2004 and 2024. 34 recipients were included, 17 bridged with durable LVAD support, and 17 transplanted without mechanical circulatory support. Perioperative characteristics, early postoperative complications, and long-term outcomes were compared between groups. Results: LVAD recipients had more advanced ventricular dysfunction, longer cardiopulmonary bypass and aortic cross-clamp times, and more frequent red blood cell transfusion requirements. Despite this higher-risk profile, early postoperative complications, early mortality, and ICU and hospital length of stay were similar between groups. Ten-year survival was 70.6% in the LVAD group, and 82.4% in the non-LVAD group (log-rank p = 0.365), and freedom from CAV and treated rejection did not differ significantly. Conclusions: In this single-center, two-decade experience, durable LVAD support enabled successful transplantation of high-risk pediatric candidates without compromising early or long-term post-transplant outcomes. LVAD bridging appears to be a safe and effective strategy in pediatric HTx. Full article

Background/Objectives: Globally, type 2 diabetes mellitus (T2DM) accounts for about 90% of diabetes cases and contributes to hospital admissions and mortality in Malaysia. Identifying the determinants of in-hospital mortality is crucial for improving clinical management and resource allocation. This study aims to determine the clinical and disease-related determinants of in-hospital mortality among T2DM-related admissions in a tertiary teaching hospital. Methods: A cross-sectional study at Hospital Canselor Tuanku Muhriz (HCTM) in Kuala Lumpur involving 2838 T2DM-related admissions from the hospital casemix database. Demographic data, complications, disease group, length of stay, and number of diagnoses were analyzed. Logistic regression assessed factors associated with in-hospital mortality among T2DM-related admissions. Results: The in-hospital mortality rate among T2DM-related admissions was 4.2%. T2DM-related admissions resulting in in-hospital death involved individuals with a higher mean age (67.72 years, SD 12.06) compared to admissions that did not result in death (65.11 years, SD 11.03). Significant determinants of mortality included infections and parasitic diseases (aOR = 8.042; 95% CI: 2.999, 21.569; p < 0.001), respiratory system (aOR = 3.004; 95% CI: 1.192, 7.571; p = 0.020), hepatobiliary/pancreatic (aOR = 3.674; 95% CI: 1.143, 11.871; p = 0.029), and central nervous system (aOR = 3.484; 95% CI: 1.236, 9.826; p =0.018) conditions, and severity level 3 (aOR = 2.994; 95% CI: 1.464, 6.221; p = 0.003). Each additional diagnosis increased the mortality risk (aOR = 1.107; 95% CI: 1.032, 1.189; p = 0.005). Conclusions: Mortality among hospitalized T2DM-related admissions is driven by severe infections, respiratory, hepatobiliary, and neurological conditions, together with overall disease burden. Early identification of high-risk clinical presentations and a timely multidisciplinary approach may reduce preventable deaths among T2DM patients. Full article

Background/Objectives: Family Integrated Care (FICare) is a model of care for preterm or critically ill infants in which families are considered equal partners with clinical teams and are fully integrated into all aspects of care and decision-making. In this study, we conducted a health economics study of FICare implementation in the UK, as part of the EU-funded international, interdisciplinary, and intersectoral project RISEinFamily. Methods: An economic evaluation of healthcare services and an audit of clinical outcomes for infants admitted to the Royal Sussex County Hospital and the Princess Royal Hospital neonatal units in 2021 (at the start of FICare) and 2024 (when FICare was fully integrated into clinical practice) were conducted. Anonymized data on hospital admissions were downloaded from the hospital database. Infants with a duration of stay in the NICU of more than 20 days were included in the analysis. The cost of NICU stay was estimated using the Health Resource Group codes. Results: The average duration of infants’ stay in NICU was similar before and after the implementation of FICare (47 days (SD 29) in 2021 and 47 days (SD 31) in 2024). However, the infants who received FICare spent fewer days in high-dependency care; on average, 10 days in 2024 and 13 days in 2021. The duration of invasive ventilation fell by 12% and the duration of CPAP by 26% after introducing FICare. The total cost per baby stay in NICU was GBP 63,279 (USD 87,021) in 2021 and GBP 59,284 (USD 75,777) in 2024. Conclusions: Although the changes did not reach statistical significance, the study suggests that FICare may be resource- and cost-saving due to reducing infants’ stays in high-dependency care. Full article

Background/Objectives: This pilot study employed a quasi-experimental, single-group, pre-post design to examine the acute effects of single music lessons on executive function and to explore whether affective changes are associated with cognitive improvement in trained musicians. Drawing on Fredrickson’s broaden-and-build theory and Eysenck’s processing efficiency theory, we hypothesized that changes in positive affect and state anxiety would be statistically associated with cognitive outcomes. Methods: Using purposive sampling, 60 musicians (34 female, 26 male; Mage = 26.0, SD = 9.8; range: 16–58 years) completed assessments before and after a 45–60 min instrumental lesson (guitar, n = 20; violin, n = 20; piano, n = 20). Executive function was measured using the Stroop Color-Word Test (Golden version, Greek-validated). Affective states were assessed using the Positive and Negative Affect Schedule (PANAS; 20 items) and State-Trait Anxiety Inventory-State (STAI-S; 20 items). Data were analyzed using paired t-tests, Pearson correlations, path analysis, and bootstrap mediation analysis (5000 resamples). Results: Music lessons were associated with improved executive function (Stroop interference: d = 0.59, p < 0.001), increased positive affect (d = 1.87, p < 0.001), and reduced negative affect (d = −2.34, p < 0.001) and state anxiety (d = −2.64, p < 0.001). Path analysis demonstrated excellent model fit (CFI = 1.00; RMSEA = 0.00), with affective changes associated with 61.3% of the total effect on cognitive improvement. Conclusions: Single music lessons were associated with both cognitive and affective benefits, with affective changes statistically linked to cognitive outcomes. As a pilot study, these exploratory findings require replication using controlled designs before generalization. Future research should incorporate neuroimaging methods and cross-cultural validation. Full article

Location-based services generate a large amount of location and trajectory data, which contain rich spatiotemporal and semantic information. Publishing these data without proper protection can seriously threaten users’ trajectory privacy. Existing trajectory privacy protection schemes generally fail to consider the dependency between a stay point and its preceding location and also overlook the relationship between the semantic information of location and privacy. Moreover, they often suffer from issues such as over-protection. Therefore, this paper proposes a trajectory privacy protection scheme based on the replacement of stay points. First, a stay point extraction algorithm is proposed, which extracts users’ stay points by setting distance and time thresholds based on the principle of the sliding window. Then, this paper proposes a location perturbation algorithm based on the vector indistinguishability mechanism and introduces different protection strategies for ordinary stay points and long-duration stay points, respectively. Finally, the perturbed trajectory is adjusted by generating a certain number of location points near the replacement points to maintain the temporal continuity and integrity of the trajectory. The experimental results indicate that it is necessary to provide more meticulous protection for long-duration stay points. Compared with similar schemes, the proposed scheme in this paper achieves higher data utility while ensuring privacy. Full article

Devices equipped with the Global Positioning System (GPS) generate massive volumes of trajectory data on a daily basis, imposing substantial computational, network, and storage burdens. Online trajectory simplification reduces redundant points in a streaming manner while preserving essential spatial and temporal characteristics. A representative method in this line of research is Directed acyclic graph-based Online Trajectory Simplification (DOTS). However, DOTS does not preserve stay-related information and can incur high computational cost. To address these limitations, we propose Directed acyclic graph-based Online Trajectory Simplification with Stay Areas (DOTSSA), a fast online simplification method that integrates DOTS with an online stay area detection algorithm (SA). In DOTSSA, SA continuously monitors movement patterns to detect stay areas and segments the incoming trajectory accordingly, after which DOTS is applied to the extracted segments. This approach ensures the preservation of stay areas while reducing computational overhead through localized DAG construction. Experimental evaluations on a real-world dataset show that, compared with DOTS, DOTSSA can reduce compression time, while achieving comparable compression ratios and preserving key trajectory features. Full article

How do survivors mourn when violence controls movement, speech, and public grief? This article reads lament as a political–theological practice that keeps the dead publicly addressable under forced (im)mobilities—conditions in which some are deported, disappeared, or killed while others are compelled to remain amid ruins, surveillance, and stigma. Through a comparative reading of Lamentations and Han Kang’s Human Acts, this study develops “fourth-person lament” to name a ruin-saturated address (“you”) that is relayed through multiple voices and across the boundary of death, refusing to resolve responsibility into a single speaker or a finished story. The analysis shows how lament is mediated through bodies that remain—hunger, wounds, exhaustion, unburied dead—and through spaces turned into archives of violence, so that catastrophe cannot be sealed into closure or denial. By tracing struggles over memory and affect—over who may move, who must stay, and whose deaths can appear as grievable—this article argues that lament operates as resistant passage within enforced (im)mobility: a communal and public insistence that memory, mourning, and responsibility remain open to contestation. Full article

Body composition, specifically the quantification of skeletal muscle and adipose tissue using preoperative computed tomography (CT) imaging, is a clinically significant predictor of postoperative complications after lung cancer surgery. The main features of CT-derived body composition analysis are: skeletal muscle index, muscle density, adipose tissue quantification and automated or semi-automated segmentation. Low skeletal muscle mass (sarcopenia) independently increases the risk of perioperative complications, including respiratory complications, and is associated with longer hospital length of stay and worse long-term survival. Sarcopenic obesity—characterized by low muscle mass in the context of high adiposity—further elevates complication risk and prolongs recovery. CT-derived measures such as muscle cross-sectional area, muscle density, and adipose tissue distribution (visceral, subcutaneous, and intramuscular) provide more precise risk stratification than BMI alone. Skeletal muscle area and density are inversely correlated with postoperative complications and recurrence risk; patients with lower muscle mass and density experience more adverse outcomes. In men, age and reduced skeletal muscle area are particularly strong predictors of complications after pneumonectomy. Obesity, when not accompanied by sarcopenia or myosteatosis, may confer a survival advantage—the so-called “obesity paradox”—but this protective effect is lost in patients with low muscle mass or poor muscle quality. Systemic inflammation and nutritional status further modulate the impact of body composition on surgical risk. This review highlights the critical role of CT-derived body composition analysis in predicting postoperative outcomes following lung cancer surgery. Full article

Background: Traumatic brain injury (TBI) is a global healthcare problem, and post-traumatic amnesia (PTA) is a known predictor of long-term and societal outcomes. However, factors influencing PTA recovery during the inpatient rehabilitation phase remain underexplored, particularly in Asian populations. Objective: To identify factors associated with PTA duration and emergence during inpatient rehabilitation and examine their impact on functional outcomes. Materials and Methods: We conducted a retrospective, single-center cohort study over a 7-year period among patients with acute TBI who were admitted to an inpatient rehabilitation hospital. Outcomes included PTA emergence and duration, discharge Functional Independence Measure (FIM), rehabilitation length of stay, and Glasgow Outcome Scale (GOS) at ≥1 year. Results: A total of 100 patients were analyzed. In an adjusted Cox regression, age ≥ 55 years (Hazard Ratio [HR] 0.47) and non-infective medical complications during rehabilitation (HR 0.31) were associated with reduced likelihood of PTA emergence, while mild admission GCS (13–15; HR 4.80) and epidural hemorrhage (EDH) (HR 2.00) were associated with PTA emergence. PTA non-emergence was associated with approximately a 20-point lower discharge FIM total score (adjusted model, p < 0.001). A PTA duration of ≥90 days was associated with a lower total discharge FIM score by approximately 45 points compared with those with a PTA duration of <28 days (p < 0.001). PTA emergence was associated with better GOS at ≥1 year (odds ratio [OR] 3.92, p = 0.02). Conclusion: Both acute injury characteristics and intra-rehabilitation factors were associated with PTA recovery functional outcomes. PTA emergence, beyond PTA duration, was strongly associated with discharge functional status and long-term global outcome, supporting the clinical value of PTA in prognostication, rehabilitation planning, and goal setting. Full article

The continuous handling of the large amount of raw data generated by implantable brain–computer interface (BCI) devices requires a large amount of hardware resources and is becoming a bottleneck for implantable BCI systems, particularly for power-constrained wireless systems. To overcome this bottleneck, we present NeuroGator, an asynchronous gating system using Local Field Potential (LFP) for the implantable BCI system. Unlike a conventional continuous data decoding approach, NeuroGator uses hierarchical state classification to efficiently allocate hardware resources to reduce the data size before handling or transmission. The proposed NeuroGator operates in two stages: Firstly, a low-power hardware silence detector filters out background noise and non-active signals, effectively reducing the data size by approximately $69.4\%$. Secondly, a Dual-Resolution Gate Recurrent Unit (GRU) model controls the main data processing procedure on the edge side, using a first-level model to scan low-precision LFP data for potential activity and a second-level model to analyze high-precision LFP data for confirmation of an active state. The experiment shows that NeuroGator reduces overall data throughput by 82% while maintaining an F1-Score of 0.95. This architecture allows the Implantable BCI system to stay in an ultra-low-power state for over 85% of its entire operation period. The proposed NeuroGator has been implemented in an Application-Specific Integrated Circuit (ASIC) with a standard 180 nm Complementary Metal Oxide Semiconductor (CMOS) process, occupying a silicon area of $0.006{\mathrm{mm}}^2$ and consuming 51 nW power. NeuroGator effectively resolves the resource efficiency dilemma for implantable BCI devices, offering a robust paradigm for next-generation asynchronous implantable BCI systems. Full article

Objectives: This study aimed to explore the relationship between emotion dysregulation (ED), impulsivity, and symptom severity in emerging adults (16–25 years) diagnosed with Borderline Personality Disorder (BPD). Specifically, it sought to determine which ED dimensions differentiate BPD from non-clinical, independently of anxiety and depression, and how these relate to clinical features of BPD. Methods: A total of 184 participants (BPD = 44, non-clinical group = 140) completed standardized assessments, including the DERS (ED), UPPS-P (impulsivity), DIB-R (BPD), BDI-II (depression), and STAI-T (trait anxiety). Analyses included Mann–Whitney tests, quantile and logistic regressions, and Spearman correlations, adjusting for clinical covariates. Results: BPD participants scored significantly higher on all DERS subscales (p < 0.001). Adjusted regressions identified Impulse, Awareness, and Clarity as key discriminators (ORs: 5.91, 3.56, 2.90), and a total DERS score >129 increased BPD likelihood twelvefold. ED dimensions were associated with DIB-R symptom severity, especially Impulse and Strategies. Only Clarity showed a negative correlation with suicide attempts, suggesting greater emotional confusion was linked to fewer reported attempts. ED also correlated with urgency traits on the UPPS-P. Conclusions: ED—particularly emotional impulsivity, poor awareness, and low clarity—emerges as a core marker of BPD in emerging adulthood. These findings underscore the importance of early intervention strategies targeting emotional identification, modulation, and impulsivity control to mitigate clinical severity and long-term risk. Full article

The increasing use of nuclear energy, a reliable baseload power with minimal greenhouse gas emissions, makes managing the heat of dry storage for spent nuclear fuel (SNF) a key engineering issue. Our research indicates that strong heat layers form in standard setups, with over 40% of the vault exceeding 85 °C when airflow stops. A staggered cask setup with outlets on both sides and a 0° inlet yielded the best results, exhibiting the lowest standardized temperature (θave = 0.23) and maintaining wall temperatures below 65 °C. Input speed (4.0–6.0 m/s) is the most significant factor, dropping output temperature from 80 °C to 38 °C. While convection is the primary method of heat transfer (over 90%), radiation becomes significant in low-flow areas, although its effect diminishes as surface temperatures increase. Pressure loss stays low (about 3.2 Pa), which is suitable for mechanics. To improve the system’s practicality and sustainability, it is advised to use both active and passive cooling and to reuse low-grade heat. This work provides reliable guidance for HVAC design under full-load conditions, enhancing the safety, energy efficiency, and cost-effectiveness of SNF storage. Full article

Cable-stayed suspension hybrid bridges (CSSHBs) integrate the advantages of cable-stayed bridges and suspension bridges into a highly rigid structure. However, due to their hybrid nature, the static performance of CSSHBs is highly sensitive to various factors, presenting significant challenges for parameter analysis and scheme comparison during design. This study presents a new live load effects analysis strategy for the hybrid bridge with varied structural parameters. The methodology expands the application scenarios of variable parameter influence line (IL) analysis. It solves structural live load responses based on the area of influence lines with the same sign and constructs a “parameter variation-structural response” diagram. Simultaneously, it extracts critical live load cases, enabling designers to adjust parameters during the conceptual design phase based on calculation results from a limited number of load cases. The 690 m Tuwan Bridge is used as the benchmark model for the case study. The study first investigates the characteristics of its influence lines, followed by parametric studies. Results indicate that when the main girder stiffness is increased by a factor of 100, the deflection at the mid-span section and the cable force amplitude of the side hanger are reduced by 53% and 81%, respectively. And increasing the sag-to-span ratio proves effective in mitigating live load effects. Finally, the structural static responses under three critical load cases are analyzed to comprehensively validate the proposed analytical strategy. Full article