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Parameter estimation for complex physics-based cardiac models is computationally demanding. Surrogate models can be used to speed up model evaluations and improve the feasibility of estimation and uncertainty quantification. However, the use of surrogates introduces additional sources of error that, if neglected, can cause bias or overconfidence in inferences. Here, we present a general approach to account for such model errors when carrying out surrogate-based parameter estimation and uncertainty quantification. We use the Bayesian approximation error approach to develop a general framework that systematically accounts for modelling errors and uncertainties induced from the use of a surrogate model. We detail and implement this approach for the task of estimating cardiac stiffness from in-silico 3D left ventricle passive deformation data. We use a finite element model of cardiac mechanics with a neural network-based surrogate, and compare the results with those obtained from a simple regression approach. We show that, despite the sophistication of the neural network, neglecting model errors in the estimation stage leads to biased and overconfident estimates. We demonstrate that our proposed framework allows for simple model-error corrections that provide substantially better inferences. We also demonstrate that our approach can decrease the required number of forward simulations and computational cost for training a neural network by augmenting a low-complexity neural network with a Bayesian approximation error model. We have developed a framework for augmenting surrogate models that improves inference and decreases training time. This has potential for use in the clinical estimation of cardiac stiffness as a biomarker of disease, where efficiency is required at the point of care.
Under the "Dual Carbon" goals, reducing carbon emissions from contaminated site remediation is urgent. However, most existing studies have focused on Cd, Pb, and other heavy metals, and research on the remediation of Cr(VI) has long centered primarily on removal efficiency and risk management. There is a relative lack of research specifically addressing carbon emissions accounting and reduction strategies for sites contaminated with Cr(VI). This study, therefore, presents the first comprehensive carbon emissions assessment for Cr(VI) contaminated site remediation and explores emission mitigation pathways based on a project in East China. A life cycle assessment (LCA) was applied to define system boundaries and compile inventories for chemical washing, chemical reduction, and chemical washing combined with reduction. The carbon footprint was calculated using Emission Factor Methods, with key factors identified via contribution and sensitivity analyses. Mitigation potential was assessed through technical and energy system optimization and their integration, resulting in targeted strategies. Results show that treating 1 m3 of Cr(VI)-contaminated soil emits 407.75, 27.52, and 227.27 kg CO2eq, respectively. The remediation stage dominates emissions for washing (63.77%) and combined (57.37%), while wastewater treatment dominates for reduction (57.78%). Technical, energy, and coupled optimizations reduce emissions by 24-30%, 2-24%, and 31-48%, respectively. Key measures include improving reagent efficiency, controlling transport distance, recycling water, and selecting suitable techniques. This study focuses on the application, based on the case studies from the East China region. It considers the soil pollution situation of Cr(VI), calculates the total carbon emissions during the entire life cycle of the remediation process, and conducts a comprehensive analysis of contribution rates, sensitivity, and emission reduction potential. This provides a reference for the formulation of carbon reduction strategies in the remediation process of similar contaminated sites.
Speeding poses a critical risk to urban traffic safety, especially for new energy vehicle taxis, whose capacity of high torque and rapid acceleration may exacerbate this risk. To investigate the speeding risk of new energy vehicle taxis, this study proposes a multistage analytical framework, which combines endogeneity-adjustment methods and machine learning to account for spatial spillovers, endogeneity, and nonlinear effects. The framework employs geographically weighted generalized propensity score matching to capture nearby road segments' spillover effects and balance observable endogeneity, and combines spatial instrumental variables with two-stage residual inclusion method to account for potential unobservable endogeneity. Besides, the study develops a generalized speeding risk index that incorporates speeding frequency, severity, and exposure to comprehensively measure the speeding risk at the road segment level. Further, three Extreme Gradient Boosting models with Shapley Additive Explanations values and Accumulated Local Effects plots are developed to capture the nonlinear relationships between speeding risk and four categories of influencing factors (i.e., traffic conditions, road characteristics, traffic management strategies, and points-of-interest density) and enhance model interpretability. The proposed framework is applied using GPS trajectory data of new energy vehicle taxis in Chengdu, China. Results show that the proposed framework significantly outperforms conventional geographically weighted regression and linear regression models. Medium traffic flow, moderate intersection spacing, 4-5-lane segments, low commercial points-of-interest density, and roads near charging stations are associated with higher speeding risk, whereas no-parking rules, higher residential points-of-interest density, physical separators, and higher speed-limit categories are associated with lower risk. The findings further indicate that traffic management strategies become more influential after accounting for spatial spillover effects and correcting endogeneity, highlighting the importance of structurally aware modeling for urban traffic safety analysis. The study provides theoretical insights and practical implications for urban traffic safety management in the era of vehicle electrification.
Perception of basic spatial properties (e.g., size, separation) varies with visual context, indicating a rescaling process in spatial vision. Previous findings have suggested that this rescaling is supported by an adjustable "mental ruler", an internal metric that can be flexibly changed by context. However, the neural implementation of this putative mental ruler remains unknown. We hypothesized that this mental ruler is represented by multiple spatial frequency (SF) channels with different tunings. In this account, the relative weighting of different SF channels sets the unit length of the mental ruler. Up-weighting of high-SF channels drives the concentration of neuronal receptive fields in early visual cortex, leading to a shorter unit length (a finer division) and perceptual inflation. Conversely, up-weighting of low-SF channels produces a longer unit length (a coarser division) and perceptual compression. Consistent with this account, we found that modulating the relative contribution of the high- and low-SF channels is coupled with a systematic distortion in perceived separation, a fundamental spatial property, and a global displacement of population receptive fields (pRFs) in primary visual cortex. Computational modeling further demonstrated that the perceptual distortion and the pRF displacements were quantitatively linked through SF channel modulation. Together, these results provide converging evidence for the neural implementation of an adjustable mental ruler and suggest a rescaling mechanism through which the visual system dynamically calibrates perceived spatial properties across different pictorial, image-based contexts.
Pedestrians are among the most vulnerable road users in urban transport systems. Studies have explored the effects of the built environment, traffic, and human characteristics on pedestrian crash risk. However, the majority of these studies have focused on the association between pedestrian safety and influencing factors at macroscopic spatial scales. The influences of micro-level factors, particularly streetscape features, on pedestrian safety are less studied due to the unavailability of high-resolution spatial data. In this study, the influences of streetscape features, in terms of the percentage of green view, sky view, road space, sidewalks, buildings, and traffic signs, on pedestrian crash frequency are evaluated using a computer vision approach and citywide street view imagery. Additionally, the influences of other micro-level factors, such as pedestrian network configuration and transport facilities, and macro-level factors, including land use and socio-demographics, are accounted for. Since data at different spatial scales are used, a modified multi-level multiple membership model is adopted to jointly estimate the influences of both micro- and macro-level factors on pedestrian safety, accounting for possible spatial dependence and between- and within-level correlations. Results indicate that pedestrian crash frequency increases with the presence of a bus stop or metro exit, the number of crosswalks, general and barrier-free walking accessibility, and the percentage of building view. In contrast, pedestrian crash frequency decreases with the presence of a footbridge or underpass and the percentage of green, sky, road space, sidewalk, and traffic sign views at the microscopic spatial scale. Furthermore, land use and population socioeconomics also significantly affect pedestrian safety. The findings should shed light on urban design and planning strategies that can enhance walkability without compromising pedestrian safety.
Educational attainment (EA) is a major determinant of well-being and is influenced by genetic and environmental factors. This study investigated whether polygenic scores for EA (EA-PGS) relate to school performance in adolescents with and without psychiatric disorders, and whether associations vary by parental education and sex. We analyzed 86,122 individuals (36,659 with psychiatric disorders) from the Danish iPSYCH2015 case-cohort. Associations between EA-PGS, psychiatric diagnoses, and ninth-grade examination outcomes (passing rates and Danish and mathematics grades) were assessed using regression models, adjusting for covariates. Higher EA-PGS was associated with lower odds of several psychiatric disorders, including attention-deficit/hyperactivity, attachment, neurotic, oppositional defiant/conduct, and substance use disorders, and intellectual disability. Regardless of case status, individuals with higher EA-PGS were more likely to pass the examination and achieve higher grades. At comparable EA-PGS values, adolescents with psychiatric disorders performed worse than controls. For pass/fail, EA-PGS effects differed between cases and controls in attachment, eating, neurotic, mood, substance use, and tic disorders, and intellectual disability (qFDR<0.05), being larger in cases for all groups except intellectual disability, where effects were attenuated. Parental education, but not sex, modified the association between EA-PGS and passing (interaction p=0.008), with differences by parental education evident at lower EA-PGS levels. Higher EA-PGS was associated with better school performance, but adolescents with psychiatric disorders performed worse than controls after accounting for EA-PGS. Performance differences persisted after accounting for EA-PGS. Both EA-PGS and parental education were associated with educational outcomes, indicating that genetic and familial factors are related to variation in school performance.
Education is among the strongest correlates of health behavior, yet its relationship with vaccine acceptance varies sharply across European contexts. Using the SHARE COVID-19 Survey 2 (summer 2021) linked to rich pre-pandemic data from SHARE and SHARELIFE - a longitudinal survey of adults aged 50 and above across 27 European countries - we document a striking East-West asymmetry: schooling is strongly and positively associated with COVID-19 vaccine take-up in Central and Eastern Europe (CEE) but only weakly related in Western and Central Europe (WCE). We argue that this contrast is consistent with the institutional legacies of communist rule, which generated persistent deficits in institutional trust and social capital that education may help bridge. To investigate which pre-pandemic domains account for the steeper CEE gradient, we add conceptually motivated blocks of covariates capturing cognitive resources, social capital, social networks, health, and early-life circumstances. Cognitive functioning accounts for the largest observable share of the gradient, but a sizable residual remains after extensive adjustment and is robust to sensitivity analysis for unobserved confounding. A within-Germany comparison by birthplace (East vs West) confirms that the education gradient is steeper among those raised in the former GDR, reinforcing the interpretation that institutional context shapes how education translates into vaccine acceptance.
Long-term outcomes after replantation of avulsed anterior teeth remain difficult to predict. This retrospective study evaluated post-replantation tooth survival and assessed the tooth- and patient-level factors associated with tooth loss and ankylosis. Patients with replanted avulsed anterior teeth treated between 2008 and 2021 were identified from a clinical database. Observation time extended from replantation to tooth failure or last follow-up. Kaplan-Meier analysis was used to estimate the survival probabilities using patient-cluster bootstrap confidence intervals (CIs). Cox and logistic regression models with patient-cluster robust standard errors evaluated the factors associated with tooth loss and ankylosis, respectively. The cohort included 248 replanted anterior teeth from 180 patients; 19 teeth (7.7%) were lost and 103 teeth (41.5%) had ankylosis. The estimated 1- and 5-year survival probabilities were 96.8% (95% CI, 94.1%-98.8%) and 92.9% (95% CI, 87.7%-97.2%), respectively. In Cox regression analysis, no clinical variables were significantly associated with tooth loss after patient-cluster robust inference. Mandibular location (odds ratio [OR], 0.41; 95% CI, 0.17-0.97) and alveolar bone fracture (OR, 0.45; 95% CI, 0.22-0.89) were associated with lower univariable odds of ankylosis, but neither remained significant in the multivariable model. Tooth retention and ankylosis should be interpreted as distinct outcomes after replantation of avulsed anterior teeth. Tooth loss was uncommon, but ankylosis was frequent, and independent prognostic factors for failure were not confirmed after accounting for sparse events and patient-level clustering.
As the leading cause of disability and death in children, paediatric traumatic brain injury (pTBI) is a clinical concern that impacts children on a global scale [1]. The incidence of TBI varies dramatically both between and within countries, ranging between 47 and 280 per 100,000 children, and is generally more common in males [1]. All ages are affected by TBI throughout childhood, though typically two peaks during infancy (0-2 years) and adolescence (15-18 years) are the most common intervals [1]. Mild TBIs (mTBIs) are the most frequently diagnosed, accounting for between 75 and 90% of cases, with a vast majority demonstrating no pertinent radiological findings and discharged home without follow-up.
 In recent years, the term active wetting has gained some traction in works describing, analyzing, and modeling a wide variety of wetting phenomena, for instance, in the contexts of biomolecular condensates, of cell layers or cell aggregates, and of active Brownian particles. The present perspective discusses a coarse classification of wetting phenomena that accounts for this. First, different categories of static and dynamic wetting of passive liquids are briefly introduced, in particular, distinguishing equilibrium wetting, relaxational wetting, driven wetting, and reactive wetting. Second, an overview is given of the various phenomena recently described as active wetting. We conclude by discussing a possible definition of active wetting together with a number of caveats that one might want to keep in mind when using such classifications.
Vertical stratification has long been recognized as a key dimension of biodiversity in structurally complex ecosystems, shaping animal movement and community structure. Camera traps provide a powerful means to extend biodiversity monitoring across forest strata through continuous, standardized observation. However, most camera trapping studies focus on terrestrial observations or a single arboreal layer, limiting inference about vertically structured communities. Here, we evaluate a standardized "camera column" approach for assessing mammal community occupancy in the Congo Basin. We deployed camera traps in three forest strata (canopy, understory-midstory, and ground) at each sampling point in a standardized grid and used a multispecies, multi-scale occupancy model to assess how incorporating observations across strata influences estimates of species occupancy. Our results demonstrate that incorporating vertical space can alter the inferred relationship between mammal communities and environmental gradients, with a significant positive effect of elevation on mean occupancy emerging only when observations from all forest strata were incorporated. These results suggest that even small elevation gradients in lowland tropical forests can shape mammal diversity, likely through soil-mediated effects on habitat structure and resource availability. Furthermore, accounting for three-dimensional habitat structure may be essential for accurately characterizing community-environment relationships in vertically structured systems.
For decades, apoptosis has reigned supreme in cell death therapeutics, yet its clinical limitations in resistant cancers and degenerative diseases have unveiled the critical role of non-apoptotic regulated cell death (RCD) pathways, including ferroptosis, necroptosis, pyroptosis, and parthanatos. This review examines chromatin as a key regulatory layer influencing these pathways through dynamic histone modifications, DNA methylation, non-coding RNAs, and 3D genome architecture. We dissect how chromatin landscapes integrate metabolic, oxidative, and inflammatory signals in a cell-type- and lineage-dependent manner to steer cell fate, thereby enabling context-specific RCD activation or suppression. Emerging evidence suggests that epigenetic dysregulation can silence tumor-suppressive cell-death regulators such as GSDME and RIPK3 in some cancers and may contribute to neuronal susceptibility to parthanatos in specific neurodegenerative models. Therapeutically, the reversibility of epigenetic marks makes HDAC/DNMT inhibitors, BET-targeting agents, and CRISPR/dCas9-based editing attractive candidates for re-sensitizing selected preclinical models to RCD inducers; however, their clinical value will depend on improving tissue selectivity, minimizing toxicity, and demonstrating durable efficacy in heterogeneous patient tumors. Nanotechnology may improve delivery, but it does not fully overcome systemic exposure or targeting barriers. Emerging frontiers (single-cell epigenomics, phase-separated biomolecular condensates, and mitochondrial-nuclear crosstalk) may help identify candidate biomarkers and vulnerabilities, but these remain incompletely validated. By shifting from a genetic to a chromatin-centric paradigm and explicitly accounting for cell-type-specific chromatin states, this review highlights a promising framework for overcoming cell-death resistance, while recognizing that most pathway links, biomarkers, and delivery strategies still require robust validation in vivo and across patient cohorts before broad clinical translation.
The human gut virome is a critical yet understudied component of the microbiome that shapes microbial community structure and host-microbe interactions. However, most existing human gut virome reference databases have been constructed predominantly from populations in high-income countries, resulting in the substantial underrepresentation of African populations. To help address this disparity, we developed the Kenyan Human Gut Virome Catalogue (KHGVC), the first comprehensive human gut virome resource for Kenya and the first country-specific human gut virome catalogue from Africa. Using a standardized viromics pipeline applied to 626 fecal metagenomes spanning infants and adults across three Kenyan counties, we reconstructed 116,968 viral operational taxonomic units (vOTUs). Cross-catalogue comparisons revealed extensive novelty where 65.6% of KHGVC's vOTUs larger than 10 kb lacked matches in five major human gut virome databases, and 95% remained unique relative to the Unified Human Gut Virome (UHGV). Temperate bacteriophages accounted for ~ 70% of vOTUs, supporting a major role for lysogeny in gut ecosystem stability. Functional annotation assigned putative roles to ~ 27% of predicted viral proteins, primarily structural and replication-associated functions. Application of KHGVC revealed pronounced age-dependent virome structuring in which infant viromes were less diverse and enriched in Bifidobacterium-infecting phages, including Bifidobacterium longum, whereas adult viromes exhibited greater diversity and expansion of Prevotella-associated phages. Together, the KHGVC substantially expands known human gut viral diversity and provides a foundational reference for Kenyan and African virome research. The KHGVC can be accessed freely through a publicly available interactive web interface (https://igmr.org/software/kenyavirocat).
Appropriate transportation management significantly influences both operational costs and associated risks of diffusible chemicals distribution. Urban diffusible chemicals distribution differs distinctly from conventional distributions, presenting significant challenges for routing arrangement. This study investigates urban diffusible chemicals distribution, proposing a routing optimization model that incorporates urban rescue team points while accounting for response times with potential blockages, rescue team capabilities, and their impact on routing decision-making. A composite solution method is proposed, encompassing model pre-processing techniques and a two-stage solution framework. In Stage I, an Improved Non-dominated Sorting Genetic Algorithm-II (Improved NSGA-II) is conducted to generate the Pareto frontier; and in Stage II, a post-processing procedure is implemented to facilitate the decision-maker's selection of appropriate solutions. The method is tested by computational experiments, the results show that the Improved NSGA-II can enhance the Hypervolume by up to 20.20% (average 6.99%). Finally, sensitivity analysis on the population and crossover probability related parameters is reported. Furthermore, several insights governing the cost and risk of diffusible chemicals distribution are concluded, including selecting routes with densely distributed RT points and prioritizing regions where RT points maintain substantial rescue capabilities.
Posttraumatic stress disorder (PTSD) is a psychiatric condition that may develop after trauma exposure. PTSD is characterized by considerable clinical heterogeneity. The amygdala's key role in fear conditioning makes it an important focus for investigating the neurobiology of PTSD. However, associations between amygdala volume and PTSD have been inconsistent. The amygdala consists of functionally distinct nuclei. Specific associations between amygdala nuclei volumes and PTSD may account for previous discrepancies between PTSD and whole amygdala volume. This study investigates the associations between amygdala nuclei volumes, PTSD diagnosis, severity, symptom cluster scores, age of onset and childhood trauma. Individuals with a PTSD diagnosis (n = 771) and controls (n = 1 081, 72% trauma-exposed) were sourced from the Enhancing Neuro-Imaging Genetics through Meta-Analysis and Psychiatric Genomics Consortium (mean age = 32.4 years, (SD = 13 years), 60% male). Nine amygdala nuclei volumes were compared to PTSD diagnosis, age of onset, overall severity, symptom cluster scores (re-experiencing, arousal, and avoidance/emotional numbing), and childhood trauma subscales. Analyses were performed using ordinary least-squares regression, corrected for age, sex, intracranial volume, and whole amygdala volume. PTSD diagnosis was not significantly associated with amygdala nuclei volumes. PTSD severity scores were associated with smaller right lateral nucleus volume (β = -0.26, pBON = 0.01). Smaller right lateral nucleus volume was also associated with re-experiencing (β = -1.01, pBON = 0.04) and arousal (β = -0.9, pBON = 0.04), smaller left paralaminar nucleus volume was associated with re-experiencing (β = -0.1, pBON = 0.04), smaller left corticoamygdaloid transition area volume was associated with avoidance (β = -0.31, pBON = 0.02). Larger left and right central nucleus volumes were significantly associated with childhood physical abuse (β = 0.24, pBON = 9 × 10-3) and neglect (β = 0.29, pBON = 0.04), respectively. Differences in select amygdala nuclei volumes among adults are associated with PTSD severity, symptom cluster scores, and childhood physical abuse and neglect. These findings demonstrate nuclei-specific patterns consistent with their functional roles in fear learning and expression.
Nowotny chimney ladder crystals combine features of ordered crystals and amorphous solids, making them attractive thermoelectric materials because of their intrinsically low thermal conductivity. We investigate the intermetallic compound Ru2Sn3 and show that, despite its crystalline order, its heat capacity exhibits a boson-peak-like glassy anomaly at 8-14 K. Combining experiments with first-principles calculations and molecular dynamics simulations, we trace this behavior to low-energy optical phonons emerging from the chimney ladder structure. These modes strongly couple to acoustic phonons, producing hybridization and avoided crossings that reshape the vibrational spectrum and cause the hybridized acoustic branches to contribute directly to the anomaly. Thermoelectric measurements reveal additional glass-like signatures linked to these excitations, while the electrical resistivity displays an extended linear temperature dependence and an anomalously large quadratic contribution at low temperatures. A simple theoretical model based on electron scattering by overdamped phonons qualitatively accounts for these observations.
Sex- and compartment-specific associations between quadriceps weakness and knee cartilage loss have been reported, and stiffer quadriceps has been related to clinical knee symptoms. Nevertheless, the relationship between quadriceps stiffness and knee cartilage health remains unclear. The primary aim of this study was to investigate the association between quadriceps stiffness and knee cartilage volumes. This study included 82 older adults (46 females (56.1%); mean age 65.9 years (SD 3.9)). Passive stiffness of three superficial quadriceps muscle heads was evaluated by using shear-wave elastography ultrasound. Quadriceps strength was measured by a Cybex dynamometer. Cartilage volumes of the tibia, femur, and patella were quantitatively assessed using MRI. Linear regressions were used to examine relationships of quadriceps stiffness and strength with cartilage volumes across different knee compartments, while controlling for potential covariates. Benjamini-Hochberg false discovery rate (FDR) correction was applied to account for multiple tests. Sex-specific relationships were evaluated when significant sex and quadriceps interactions were detected. Negative associations were observed between quadriceps stiffness and cartilage volumes of tibia (estimate -33.7 mm3/kPa (95% CI -63.2 to -4.2), p = 0.026), femur (-72.4 mm3/kPa (95% CI -128.8 to -16.0), p = 0.013), and total knee (-92.0 mm3/kPa (95% CI -183.2 to -0.7), p = 0.048). However, those associations became statistically non-significant after FDR corrections (FDR-corrected p = 0.104 to 0.128). Quadriceps strength was not associated with cartilage volumes in the full cohort, while a significant sex and strength interaction was observed for patellar cartilage. Sex-stratified analyses showed a positive association between quadriceps strength and patellar cartilage in females (558.2 mm3/Nm*kg-1 (95% CI 126.1 to 990.3), p = 0.013), but not males. Lower quadriceps strength is associated with smaller patellar cartilage volumes in females. Although there is a trend showing negative associations between quadriceps stiffness and tibiofemoral cartilage, there is insufficient evidence in the current sample supporting an affirmative conclusion. Future research is needed to confirm these preliminary findings, and to clarify potential causal effects and clinical implications.
Acanthamoeba keratitis (AK) is a severe, vision-threatening protozoan infection with a rising global incidence linked to contact lens use, necessitating robust genotyping to clarify its epidemiology and pathogenesis. This study analyzed the genotype distribution of 102 Acanthamoeba isolates collected from clinical settings in China between 1991 and 2014, comprising 100 isolates from corneal scrapings of clinically diagnosed AK patients, one from soil, and one from a patient's contact lens solution. Genetic analysis was conducted via amplification and sequencing of the 18S rRNA hypervariable DF3 region, followed by phylogenetic reconstruction and sequence identity assessment against reference clades. Twenty-eight distinct DF3 sequence types were identified, with genotype T4 demonstrating overwhelming dominance (99.0%; 101/102). Three novel T4 variants (T4/42-T4/44) were discovered, expanding the known diversity of this pathogenic lineage. Notably, T4/31 and T4/41 together accounted for 36% of clinical isolates, suggesting regionally endemic, infection-enriched variants. Only one isolate belonged to the rarely reported T11 genotype in China. Molecular source tracing confirmed two transmission chains: one linking a patient's corneal infection to their contact lens solution (both T4/6 variant), and another linking infection to periresidential soil (both T4/25 variant). These findings confirm the near-exclusive dominance of T4 among Chinese AK cases, identify prevalent local T4 variants, and demonstrate the utility of high-resolution DF3 genotyping for transmission tracing and disease control.
This study aimed to evaluate relationships between delayed gastric emptying and appetite suppression during treatment with liraglutide, a glucagon-like peptide-1 receptor agonist (GLP-1RA). We conducted a secondary data analysis from a 16-week randomized, placebo-controlled liraglutide trial in patients with obesity. We examined correlations between solid food gastric emptying and measurements of satiation and energy intake in the entire cohorts at baseline and end of treatment and separately in placebo- and liraglutide-treated patients who completed the trial. We also compared appetitive measures among liraglutide-treated participants who displayed either normal, persistently delayed, or transiently delayed emptying during treatment. In the entire cohorts at baseline and completion, gastric emptying correlated significantly with energy intake and, at baseline, with one parameter of satiation. Gastric emptying accounted for only 4%-6% of the variance in these appetitive measures. No such correlations were found in the placebo- or liraglutide-treated groups alone. There were no differences in appetitive measures among the subgroups that displayed different gastric emptying patterns during liraglutide treatment. Delayed gastric emptying appears to play little direct role in appetite suppression induced by liraglutide. Further research should explore whether delayed emptying or other gastrointestinal effects of other GLP-1RAs affect appetite directly or indirectly. ClinicalTrials.gov identifier: NCT02647944.
To quantify out-of-pocket (OOP) costs and catastrophic health expenditure (CHE) among patients hospitalised with heart failure (HF) and to identify factors associated with CHE during a single index admission in northern Tanzania. Prospective cross-sectional study. Medical ward of Kilimanjaro Christian Medical Centre, a tertiary referral hospital in northern Tanzania, from 1 May to 31 October 2024. Consecutive patients aged 14 years or older admitted with acute decompensated HF diagnosed using Framingham criteria. Of 309 eligible patients, 290 completed the study and were included in the analysis. The primary outcome was CHE, defined as OOP spending exceeding 40% of household non-food expenditure for the index hospitalisation. Secondary outcomes included total inpatient OOP cost and cost distribution by category. Factors associated with CHE were assessed using multivariable logistic regression. Among 290 hospitalised patients with HF, 201 (69.3%) experienced CHE during the index admission. The median total cost of hospitalisation was US$229 (IQR 155-405), and the median OOP payment was US$192 (IQR 39-360). Diagnostic investigations accounted for the largest share of OOP expenditure. In multivariable analysis, family income US$≤115 (adjusted OR (aOR) 10.0, 95% CI 4.3 to 23.0) and lack of health insurance (aOR 22.9, 95% CI 9.3 to 56.1) were strongly associated with CHE. Other independent associated factors were non-use of mineralocorticoid receptor antagonists before admission (aOR 4.1, 95% CI 1.5 to 11.1), reduced left ventricular ejection fraction (aOR 3.1, 95% CI 1.2 to 8.0) and length of stay >7 days (aOR 4.1, 95% CI 1.7 to 10.0). CHE was common among patients hospitalised with HF in northern Tanzania during a single admission, driven mainly by diagnostic costs and limited financial protection. Expanding insurance coverage, improving access to guideline-directed HF therapy and reducing patient payment for essential diagnostics may lessen the financial burden of HF care.