Search Results (849)

The rational-power shifted Lagrangian distribution and its corresponding regression model are discrete Lagrange probability distributions. The proposed model is constructed from a shifted Lagrangian framework with a rational-power component that introduces an additional shape parameter and provides greater flexibility in modeling dispersion and tail behavior. The derivation of the distribution is presented, and its main statistical properties are discussed, together with maximum likelihood estimation based on the expected Fisher information matrix. Using this distribution, a rational-power shifted Lagrangian regression model is formulated for analyzing count data. Simulation results are used to examine the performance of the parameter estimators and to compare the proposed model with the Poisson and modified Sunil models. A real data application using domestic violence data is also provided to illustrate its practical usefulness. The proposed model has a better fit and lower information criteria than the competing models, suggesting it could be used to model overdispersed count data. Full article

Introduction: Medical students are particularly susceptible to nutritional deficiencies and mental health problems due to intensive study demands, stress, and lifestyle factors. Vitamin D3, vitamin B12, and folate deficiencies have been implicated in mental well-being, although evidence remains inconsistent. Objective: To assess the prevalence of vitamin D3, vitamin B12, and folate deficiencies among medical students at the University of Warmia and Mazury in Olsztyn, and to explore associations between serum concentrations of these vitamins, lifestyle factors, and self-reported well-being. Materials and Methods: The study included 97 medical students. Serum vitamin concentrations were measured using electrochemiluminescence immunoassay. Well-being was assessed with the WHO-5 Well-Being Index. Group comparisons were performed using non-parametric tests, and a Poisson regression model was applied as an exploratory analysis to examine associations between selected lifestyle factors and well-being. Results: Vitamin D3 deficiency was observed in 78% of students, folate deficiency in 20%, and vitamin B12 deficiency in 8%. In unadjusted analyses, differences in serum vitamin D3 and vitamin B12 concentrations were observed between students with lower and higher self-reported well-being, whereas folate concentrations did not differ. However, after correction for multiple testing using the Benjamini–Hochberg procedure, none of these associations remained statistically significant. Exploratory regression analysis suggested that physical activity and gender may be associated with well-being, while no association with vitamin D3 supplementation was observed. Conclusions: Vitamin D3, vitamin B12, and folate deficiencies were common among medical students. Exploratory analyses suggested differences in vitamin D3 and vitamin B12 concentrations across well-being groups; however, these findings did not remain significant after correction for multiple testing and should be interpreted with caution. Overall, the results indicate that lifestyle-related factors, particularly physical activity, may play a more prominent role in student well-being than serum vitamin concentrations alone. Further longitudinal studies are required to clarify these relationships. Full article

Background/Objectives: Cystatin C-based and combined creatinine–cystatin C estimated glomerular filtration rate (eGFR) equations improve early chronic kidney disease (CKD) detection and prediction of adverse outcomes compared to creatinine alone. However, their role in predicting microvascular complications such as diabetic retinopathy (DR) is less clear. We examined the association between diabetic kidney disease (DKD), defined using creatinine-, cystatin C-, and combined eGFR measures, as well as albuminuria, and the risk of incident DR among Asian adults in Singapore. Methods: We analysed 1135 Chinese and Indian adults with diabetes aged ≥40 years from a population-based cohort study with baseline (2007–2011) and 6-year follow-up (2013–2017) data. DR was graded from retinal photographs, and incident DR was defined as new-onset at follow-up. DKD was defined as eGFR < 60 mL/min/1.73 m² using eGFRcr, eGFRcys, combined eGFRcr-cys, and albuminuria (UACR ≥ 30 mg/g), assessed individually and jointly. Modified Poisson regression models adjusted for age, sex, ethnicity, diabetes duration, HbA1c, and systolic blood pressure were used to estimate relative risks (RRs). Results: Overall, incident DR occurred in 13.0% of participants. Among those with DKD, incidence was 18.2% (eGFRcr), 16.7% (eGFRcys), 23.7% (eGFRcr-cys), and 18.3% (albuminuria). eGFRcr-DKD (RR = 2.18, 95% CI 1.33–3.58), eGFRcys-DKD (2.38 [1.51–3.78]), and eGFRcr-cys-DKD (3.15 [1.94–5.12]) were independently associated with incident DR, whereas albuminuria alone was not. Risk increased with increasing number of markers,2.00 (1.02–3.92) by dual and 4.91 (2.50–9.65) by triple markers. Conclusions: DKD defined using multiple kidney markers, particularly combined creatinine–cystatin C, was strongly associated with incident DR. These findings support the use of multiple kidney function markers to improve risk stratification for developing DR. Full article

Background: Infection following total knee arthroplasty (TKA) is a challenging complication. Optimal empirical antibiotic therapy and surgical management hinge on up-to-date knowledge of local pathogen distribution and resistance patterns. However, few studies have examined whether geographical factors, specifically rural versus urban residence, influence the microbiology or clinical outcomes of periprosthetic joint infection (PJI) within integrated healthcare systems. The goal of this study was to assess the temporal evolution of bacterial species and antimicrobial resistance in knee PJI over an 11-year period. As a secondary objective, we wanted to evaluate the potential impact of patient residence on microbiological trends and treatment success. Methods: We conducted a retrospective analysis of all patients diagnosed with knee PJI who underwent surgical treatment between 2013 and 2023 at our center. Infections were classified as acute postoperative, acute hematogenous, or chronic. Patient residence was categorized as rural (<5000 inhabitants) or urban. Temporal trends were modeled using Poisson regression, and comparisons between subgroups were performed using Fisher’s exact test and Student’s t-test. Results: A total of 98 patients were analyzed, with 99 microorganisms identified. Gram-positive organisms predominated (72.3%), with Staphylococcus aureus (33.3%) and Coagulase-negative Staphylococci (CoNS) (29.3%) as the most frequent isolates. Resistance to vancomycin was not detected in S. aureus isolates. However, CoNS demonstrated high resistance to fluoroquinolones (55.2%) and rifampicin (20.7%). No significant annual shifts were observed for Gram-positive (IRR = 0.94; 95% CI: 0.86–1.03; p = 0.413) or Gram-negative cases (IRR = 0.75; 95% CI: 0.53–1.05; p = 0.086). Comparing rural versus urban populations, no differences were found in microbiological profiles (Fisher’s exact test, all p > 0.05). Furthermore, clinical treatment success rates were comparable (Rural 69.4% vs. Urban 63.0%, p = 0.500), despite a significantly higher prevalence of diabetes mellitus in rural patients (34.7% vs. 10.2%, p = 0.007). Conclusions: The microbiological landscape of knee PJI has remained stable, with no emergence of multidrug-resistant S. aureus. In our setting, standardized management protocols appeared to be equally effective regardless of patient residence. However, given the single-center nature and sample size of this study, broader multicenter validation is required before these findings can be generalized. Full article

Efficient calibration of discrete element meso-parameters is essential for reliable rock fragmentation modeling. This study focuses on green sandstone, combining uniaxial compression tests with PFC3D simulations to establish an XGBoost–stepwise regression framework for macro–meso-parameter calibration of the parallel bond model. XGBoost was used to identify the dominant meso-parameters governing peak strength, elastic modulus, and Poisson’s ratio, and stepwise regression was applied to construct explicit nonlinear mapping equations. Peak strength is mainly controlled by shear strength τ_cp and normal strength σ_cp, while elastic modulus and Poisson’s ratio are primarily influenced by bond modulus E_cp and stiffness ratio k_p^*. Introducing quadratic and interaction terms improved model fit, with adjusted R² increasing by 27.5% and 11.2%, respectively. The calibrated parameters reproduced laboratory mechanical indices with errors of 0.09%–3.745% and showed good agreement with the observed shear–brittle failure pattern. Based on the calibrated model, a representative impact-fragmentation simulation further revealed staged conversion of input energy into fracture-related energy during crack initiation, propagation, and through-failure. The proposed framework improves the efficiency and interpretability of PBM parameter calibration and supports DEM-based analysis of rock fragmentation and energy evolution. Full article

Background/Objectives: Congenital gastrointestinal malformations (CGIMs) are important causes of neonatal surgical morbidity with potential long-term consequences. Although some can be suspected on prenatal ultrasound, data on their clinical spectrum, burden, and distribution remain limited in Eastern Europe. This study aimed to describe the diagnostic spectrum, timing of diagnosis, documented prenatal ultrasound suspicion, and the early outcomes of CGIMs managed at a Romanian tertiary referral centre between 2020 and 2024, a period overlapping the COVID-19 pandemic. Methods: We conducted a retrospective, single-centre observational study including all consecutive paediatric patients with a CGIM admitted between January 2020 and December 2024. Cases were analysed by index anatomical diagnosis, phenotypic complexity, and etiologic background. Logistic regression was used to examine factors associated with documented prenatal suspicion and in-hospital mortality, and annual hospital-based CGIM admission rates were modelled with Poisson regression, using the number of paediatric surgical admission as the offset. Results: Among the 231 children (58.9% male), the most frequent diagnoses were persistent omphalomesenteric duct remnants (16%), oesophageal atresia with or without tracheoesophageal fistula (15.6%), and anorectal malformations (13.9%). Documented prenatal ultrasound suspicion was present in 17.7% of pregnancies (41/231) and was likely underestimated because antenatal documentation was unavailable for 17.7% of the cohort. The highest proportions of documented prenatal suspicion were observed in jejuno-ileal and duodenal atresia. Foregut malformations were the most common by embryological grouping (93/231, 40.3%). Most cases were diagnosed during the neonatal period (n = 161, 69.7%). CGIM admission rates per 1000 surgical admissions ranged from 20.8 to 38.2. An exploratory Poisson model yielded a hospital-based rate ratio per calendar year of 0.88 (95% CI 0.81–0.97; p = 0.008). However, given the limited number of annual observations and increasing total surgical admissions, this finding should be considered exploratory and hypothesis-generating only. Complex cases accounted for 8.2% and associated extra-intestinal anomalies were present in 70.1%. In-hospital mortality was 13.0% and occurred predominantly in patients with complex or foregut malformations. In the primary complete-case multivariable model, prematurity remained independently associated with mortality, whereas complex CGIMs were not independently associated with mortality after adjustment. A prespecified multiple-imputation sensitivity analysis yielded a stronger estimate for complex CGIMs, but this finding was interpreted cautiously and not treated as a primary result. Conclusions: In this tertiary referral cohort, documented prenatal suspicion of CGIM was low and strongly diagnosis-dependent, while most cases were identified in the neonatal period. Mortality was concentrated in foregut and clinically complex presentations in the descriptive analysis, while prematurity remained independently associated with death in the primary multivariable model. These findings highlight the need to strengthen prenatal referral pathways and coordinated national surveillance. Full article

Background/Objectives: Excess consumption of energy-dense foods (EDF; ultra-processed snacks, sweets, and sugar-sweetened beverages) among preschool-aged children is a public health concern, particularly in low-income families. Caregiver parenting style, psychological stress, and food-parenting practices (FPP) may shape children’s EDF consumption, yet little is known about how these factors operate in real time. This exploratory pilot study examined (1) associations between baseline characteristics and EDF feeding episodes across 1 week and (2) whether caregivers’ momentary stress during EDF episodes related to FPP used. Methods: In total, 22 caregivers of Head Start children (ages 3–5) completed baseline measures and 7 days of ecological momentary assessment (up to seven prompts/day). At each prompt, caregivers reported child EDF consumption in the past hour; if confirmed, they reported FPP used and rated momentary stress. Aim 1 used Poisson regression to model caregiver-level EDF episode counts. Aim 2 tested momentary stress–practice associations during EDF episodes using GEE, with within-person and between-person stress modeled separately. Results: Authoritarian parenting was associated with a higher weekly rate of EDF episodes (RR = 1.43, 95% CI 1.23–1.66, p < 0.001); authoritative parenting trended lower (RR = 0.90, p = 0.065). Higher baseline stress was associated with more EDF episodes (RR = 1.25, p = 0.001). Momentarily, elevated stress above a caregiver’s own average increased odds of using food as a reward (OR = 1.08 per +10 points, p = 0.011), while higher average momentary stress was associated with co-eating (OR = 1.59, p = 0.042). Domain-level FPP composites showed no association with momentary stress. Conclusions: Authoritarian parenting and higher caregiver stress were associated with increased EDF feeding, and momentary stress was linked to reward-based feeding during those episodes. These hypothesis-generating findings suggest potential behavioral targets for just-in-time adaptive intervention, pending replication in adequately powered studies. Full article

Owing to multi-target tracking in scenarios with nonlinearity, uncertain measurement model and high clutter density, the Poisson multi-Bernoulli mixture (PMBM) recursion is prone to unstable covariance propagation under nonlinear dynamics as well as uncertainty in measurement-to-target association caused by mismatched gate that causes erroneous updates from clutters. In the prediction stage, the singular value decomposition (SVD) is used in place of Cholesky factorization to construct and propagate the square-root covariance factor in the square-root cubature Kalman filter (SCKF), yielding a numerically stable square-root implementation. Then, the resulting SVD-SCKF is incorporated into the PMBM prediction step and used to propagate the Gaussian-mixture components of both the Poisson point process (PPP) intensity and the Bernoulli component in the Multi-Bernoulli mixture (MBM), yielding predicted means and covariances under nonlinear dynamics. An adaptive fading factor is determined from innovation statistics, and covariance inflation is performed to improve robustness under target maneuvers and model mismatch. In the update stage, the unknown measurement function is regressed by Gaussian process (GP) using historical state–measurement samples, yielding an equivalent measurement mapping and state-dependent uncertainty. Furthermore, the predicted measurement distribution is generated from the GP-based conditional measurement distribution with state prior approximated by SVD-SCKF cubature points. An adaptive gate is determined from the GP-based conditional measurement distribution, which is approximated by an equivalent ellipsoidal gate via fitting for screening the current measurements and filtering out clutter. Residual in-gate clutter measurements are handled via Bayesian target discrimination, where the posterior probability of measurement originated from target is employed as a weight and incorporated into association weights and update likelihoods. Simulation results further confirm the effectiveness and stability of the proposed filter in complex scenarios. Full article

Extended reality (XR), encompassing augmented reality (AR), virtual reality (VR), and mixed reality (MR), is a key enabling technology for virtual worlds, and XR-related patents continue to grow rapidly. However, patent-based XR technology analysis faces a fundamental challenge: document–keyword matrix (DKM) built from patent titles and abstracts are typically high dimensional, sparse, and often exhibit excess zeros, which can distort inference when conventional text mining pipelines are applied without a generative count perspective. In this study, we propose a statistically grounded XR technology analysis framework that combines likelihood-based count modeling with interpretable structure mining to map XR sub-technologies from a patent DKM. Using an XR patent–keyword matrix, we fit Poisson regression (PR), negative binomial regression (NBR), and zero-inflated negative binomial regression (ZINBR) models via maximum likelihood estimation (MLE), controlling for document-length effects. Model selection by Akaike information criterion (AIC) consistently favored NBR for both target keywords, indicating substantial overdispersion in XR patent counts. We interpret exponentiated coefficients as incidence rate ratios (IRRs) and construct a technology relatedness network from significant IRR edges, revealing a dual-axis XR structure: reality is anchored in an AR or VR experience and content axis such as virtual and augment, whereas extend is embedded in a structure and integration axis for example, surface, edge, layer, and connectivity-related terms. To show how the proposed method can be applied to real domains, we searched the XR patent documents, and analyzed them for XR technology analysis. Full article

This study evaluates the performance of a semi-dynamic negative binomial model with cubic spline smoothing to characterize the spatiotemporal dynamics of COVID-19 mortality in Peru, a setting marked by significant data inconsistency and reporting delays. Using nationwide weekly mortality data, we compared a Poisson regression against a semi-dynamic NB model with a population offset and cubic splines (df = 6). The models were evaluated using Akaike Information Criterion and log-likelihood to handle overdispersion and temporal non-stationarity. The NB model demonstrated a superior fit, reducing the AIC from 136,596.4 to 75,668.25 and improving log-likelihood by over 30,000 points. Demographic analysis revealed an 81.6% higher risk of death in males (IRR = 1.816; 95% CI: 1.753–1.881) and an exponential gradient with age, peaking at an IRR of 4.717 (95% CI: 4.499–4.945) for individuals ≥80 years. Departmental fixed effects identified significant spatial heterogeneity, with higher diffusion in coastal regions. The semi-dynamic NB model with splines provides a robust, parsimonious, and scalable framework for epidemiological surveillance in resource-limited settings. By effectively correcting for overdispersion and stabilizing weekly reporting fluctuations, this approach offers a reliable tool for public health decision making in environments with fragmented data quality. Full article

While South Africa’s recycling chain relies heavily on informal labour, the burden of non-fatal workplace injuries among landfill-based waste pickers remains poorly characterised. This study aimed to estimate the prevalence of self-reported non-fatal workplace injuries and identify associated factors among informal waste pickers at landfill sites in Johannesburg, South Africa. We conducted a cross-sectional study at two purposively selected landfill sites in Johannesburg. Using convenience sampling, 354 waste pickers were enrolled (median age 34 years; 73.2% male). A structured questionnaire captured worker characteristics and self-reported injuries over the preceding six months. Robust (modified) Poisson regression was utilised to determine associations with self-reported workplace injury. Overall, 86.2% of participants reported at least one injury. Lacerations caused by contact with waste materials predominated (82.7%), followed by violence (20.5%) and needle-stick injuries (19.9%). Notably, 94.1% of participants reported using personal protective equipment (PPE), yet the injury prevalence was high. In the multivariable model, each additional year of landfill work experience was associated with a 1.0% higher prevalence of reported injury (adjusted prevalence ratio [aPR] 1.01; 95% CI 1.01–1.02). Conversely, pickers aged 51 years and older had a 32% lower prevalence of injury than those aged 18–28 (aPR 0.68; 95% CI 0.51–0.90). To mitigate these risks, municipal authorities should implement mandatory safety training for site entry, provide industrial-grade, puncture-resistant PPE, and formalise the integration of landfill pickers into institutional occupational health frameworks. Full article

Background: Air pollution, antimicrobial use, and population ageing are increasingly recognised as co-occurring pressures shaping population health. This study explores their ecological association with mortality patterns in the province of Messina (Southern Italy), within a One Health-informed framework. Methods: An ecological analysis was conducted using district-by-year data (2015–2024), integrating environmental monitoring (PM₁₀, PM_2.5, NO₂, O₃), outpatient antibiotic consumption, and cause-specific mortality rates. Multivariable regression models were used to assess associations between exposures and mortality outcomes. A post-2020 indicator was included to account for COVID-19-related disruption. Results: Marked geographic variability in pollutant concentrations was observed, with higher levels in urban-industrial districts. Infectious disease mortality increased from 13.8 to 44.6 per 100,000 inhabitants between the pre-pandemic and post-pandemic periods. In Poisson regression models, particulate matter showed a small and non-significant association with respiratory mortality (RR = 1.02, 95% CI: 0.89–1.18), while antibiotic consumption was not independently associated with mortality (RR = 0.99, 95% CI: 0.94–1.05). The post-2020 period was associated with higher mortality estimates (RR = 1.15, 95% CI: 0.72–1.83), although with wide confidence intervals. Conclusions: The findings suggest the co-occurrence of environmental, demographic, and pharmaceutical pressures within the same territories, rather than demonstrating formal synergistic interaction. The observed post-pandemic increase in mortality highlights the importance of accounting for COVID-19-related disruption. These results should be interpreted as exploratory, given the ecological design and limited sample size, but support the need for integrated surveillance approaches within a One Health perspective. Full article

Background: Respiratory syncytial virus (RSV) is a leading cause of hospitalization for acute respiratory tract infection (ARTI) in young children. Respiratory viral coinfections are frequently identified in RSV-related ARTIs, yet their impact on disease severity remains controversial and may vary according to the co-pathogen involved. In the context of evolving RSV prevention strategies, a clearer understanding of RSV coinfection phenotypes is needed. Methods: We conducted a multicenter retrospective cohort study of children aged ≤ 5 years hospitalized for ARTI at two Italian tertiary-care pediatric hospitals between 1 September 2022 and 30 April 2025. Children with laboratory-confirmed RSV infection detected by multiplex polymerase chain reaction were included. Patients were classified as having RSV monoinfection, RSV–rhinovirus coinfection, or RSV–non-rhinovirus coinfection. Severe disease was defined as a composite outcome including intensive care unit (ICU) admission, need for respiratory or hemodynamic support, or death. Association between infection status and severe disease was evaluated using a Poisson regression model with robust variance, adjusted for age, sex, and comorbidities. Results: Among 231 RSV-related hospitalizations, 118 (51.1%) were classified as RSV monoinfection, 65 (28.1%) as RSV–rhinovirus coinfection, and 48 (20.8%) as RSV–non-rhinovirus coinfection. Children with RSV–rhinovirus coinfection were older and had shorter hospital stays. Severe disease occurred in 80.5% of RSV monoinfections, 70.8% of RSV–rhinovirus coinfections, and 75.0% of RSV–non-rhinovirus coinfections. After adjustment, neither RSV–rhinovirus coinfection (adjusted risk ratio [aRR]: 0.93; 95% confidence interval [95% CI]: 0.80–1.13) nor RSV–non-rhinovirus coinfection (aRR: 0.99; 95% CI: 0.83–1.18) was associated with increased disease severity compared with RSV monoinfection. Conclusions: RSV–rhinovirus and RSV–non-rhinovirus coinfections were not associated with greater disease severity compared with RSV monoinfection in hospitalized children. These findings support pathogen-specific interpretation of multiplex diagnostic results and inform clinical risk stratification in the era of expanding RSV prevention strategies. Full article

Despite its widespread use for mitigating multicollinearity in count data models, Poisson ridge regression (PRR) remains methodologically constrained by the choice of the ridge parameter $k$. Existing studies predominantly evaluate ridge parameter estimators using only the mean squared error (MSE) criterion, largely neglecting their distributional properties and estimation stability. Such a narrow evaluation framework may yield unreliable inference, particularly under high correlation and small sample sizes. This study makes two original contributions to the PRR literature. First, we conduct a comprehensive comparison of 13 commonly used ridge parameter estimators and introduce two new estimators that exhibit superior empirical performance. Second, we extend performance evaluation beyond MSE by incorporating outlier ratios and conformity to normality, thereby establishing a multidimensional framework that explicitly addresses distributional robustness and estimator stability. Monte Carlo simulations across 180 scenarios—varying the number of predictors, sample size, correlation level, and intercept value—show that several estimators deemed optimal under MSE perform poorly in terms of outlier prevalence and normality. In contrast, the proposed estimators consistently achieve a balanced performance between error minimization and distributional stability. Two real-data applications further support these findings. Full article

Background: The landscape of hepatitis C virus (HCV) infection has been changing with the introduction of direct-acting antivirals (DAAs). This study evaluates 15-year temporal trends of anti-HCV and HCV-RNA positivity in a regional referral center in Türkiye, analyzing the impact of DAA treatments, the COVID-19 pandemic, and the 2023 earthquakes on disease dynamics. Methods: Laboratory data of patients tested for anti-HCV antibodies and HCV-RNA between 2011 and 2025 were retrospectively analyzed after excluding repeat records. Positive patients were categorized by antibody titers (1–4.99 S/Co and ≥5 S/Co) and viremia status. Poisson, beta, and quantile regression models were determined annual trends in case numbers, positivity rates, and median ages. Results: A total of 402,557 patients underwent anti-HCV screening over 15 years. While annual test volume increased 2.25-fold, the number and rate of high-titer (≥5 S/Co) positive patients decreased four-fold, significantly. HCV-RNA positivity rates remained stable between 2011 and 2016 but declined sharply from 2017, falling approximately 19.2% annually (p < 0.001). Significant diagnostic disruptions occurred in 2020 (pandemic) and 2023 (earthquakes). An “aging trend” was identified; the median age of viremic patients increased by over 5.5 years throughout the study period. Conclusions: The introduction of DAAs in 2016 marked a milestone, leading to a nearly 90% reduction in the viremic patient burden in our region. The steady aging of the HCV-positive population suggests that the infected pool is shrinking and is not replenished. However, global and regional crises can hinder screening efforts, necessitating resilient public health strategies to achieve World Health Organization 2030 elimination targets. Full article