UNASSIGNED: In recent times, growing uncertainty has emerged regarding the effectiveness of standard pressure ulcer (PU) risk assessment tools, which are suspected to be no better than clinical judgment, especially in the frail and comorbid elderly population. This study aimed to identify the primary clinical predictive variables for PU development and severity in hospitalized older adults, utilizing a multidimensional frailty assessment, and compare them with the Braden scale.
UNASSIGNED: The population consisted of 316 patients, admitted to the Geriatric Unit and Transitional Care of San Bartolomeo Hospital in Sarzana (Italy) during the period 21/02/22-01/07/22. The collected information included both anamnestic and laboratory data. A comprehensive geriatric assessment was performed, including also anthropometric and physical performance measurements. Multivariate logistic analysis was used, both in a binary classification test and in the subsequent ordinal classification test of severity levels. The final performance of the model was assessed by ROC curve estimation and AUC comparison with the Braden scale.
UNASSIGNED: Within the population, 152 subjects (48%) developed PU at different levels of severity. The results showed that age, Braden scale (subscales of mobility and friction/shear), Barthel scale, Mini Nutritional Assessment, hemoglobin, and albumin are predictors associated with the development of PU (AUC 85%). The result is an improvement over the use of the Braden scale alone (AUC 75%). Regarding the identification of predictive factors for PU severity, 4AT also emerges as potentially relevant.
UNASSIGNED: Assessing the subject\'s nutritional status, physical performance, and functional autonomies enables the effective integration of the Braden scale in identifying patients most susceptible to developing PU. Our findings support the integration of a comprehensive set of methodologically robust frailty determinants into traditional risk assessment tools. This integration reflects the mutual interplay between patients\' frailty, skin frailty, and PU development in very old hospitalized patients.

Early childhood marks a pivotal period in the maturation of executive function, the cognitive ability to consciously regulate actions and thoughts. Mindfulness-based interventions have shown promise in bolstering executive function in children. This study used the functional near-infrared spectroscopy technique to explore the impact of mindfulness-based training on young children. Brain imaging data were collected from 68 children (41 boys, aged 61.8 ± 10.7 months) who were randomly assigned to either an intervention group (N = 37, aged 60.03 ± 11.14 months) or a control group (N = 31, aged 59.99 ± 10.89 months). Multivariate and multiscale sample entropy analyses were used. The results showed that: (1) brain complexity was reduced in the intervention group after receiving the mindfulness-based intervention in all three executive function tasks (ps < 0.05), indicating a more efficient neural processing mechanism after the intervention; (2) difference comparisons between the intervention and control groups showed significant differences in relevant brain regions during cognitive shifting (left dorsolateral prefrontal cortex and medial prefrontal cortex) and working memory tasks (left dorsolateral prefrontal cortex), which corroborates with improved behavioral results in the intervention group (Z = -3.674, P < 0.001 for cognitive shifting; Z = 2.594, P < 0.01 for working memory). These findings improve our understanding of early brain development in young children and highlight the neural mechanisms by which mindfulness-based interventions affect executive function. Implications for early intervention to promote young children\'s brain development are also addressed.

Effective wastewater management is crucial in regions experiencing water scarcity and environmental stressors, such as pollution and climate change. Optimizing treatment processes is essential for achieving environmental sustainability. This study aims to highlight the importance of effective wastewater management strategies, particularly in regions facing water scarcity. Our objective was to identify key factors influencing the treatment process. Therefore, we evaluated associations between physicochemical parameters using multivariate statistical methods, including Principal Component Analysis (PCA) and Hierarchical Ascendant Classification (HAC). Our findings categorize the monthly water samples into three distinct groups based on levels of organic pollution: the first group (July, August, and September) is characterized by high oxygenation levels and significantly low organic pollution, indicating optimal system operation. The second group (April, October, November, and December) exhibits low oxygenation and low organic pollution, promoting sludge settling and pollutant reduction. The third group (January, February, March, May, and June) shows significantly high organic pollution and low oxygenation, which corresponds to unfavorable environmental conditions. Our study demonstrates the effectiveness of multivariate statistical methods in optimizing wastewater treatment processes, providing crucial insights for environmental sustainability and water resource management.

The Mundeswari River, an ecologically distressed river in eastern India, has been subjected to water quality deterioration largely due to anthropogenic activities in its vicinity. This study aimed to comprehensively evaluate the current state of pollution in the river and assess the appropriateness of river water for irrigation, given its extensive use for agricultural purposes. Monthly water quality monitoring was undertaken at four distinct sampling sites (SP1-SP4) over a two-year period (2020-2022), considering seventeen water quality parameters. This research employed principal component analysis/factor analysis (PCA/FA) and absolute principal component score-multiple linear regression (APCS-MLR) receptor modelling. These methodologies were used to discern and quantify potential sources of pollution influencing the water quality of the Mundeswari River. The study revealed that the water quality of the Mundeswari River was most degraded during the pre-monsoon season. Among the four sampling sites, SP3 exhibited the highest level of pollution with mean biochemical oxygen demand (BOD) and chemical oxygen demand (COD) values of 5.36 mg/L and 44.72 mg/L, respectively. According to the one-way analysis of variance (ANOVA), there was considerable spatial and seasonal disparities (P < 0.05) in most water quality parameters. The PCA/FA extracted four latent pollution sources, accounting for 81.5% of the total variance. The primary factors influencing the quality of river water are natural weathering processes, discharge of domestic effluent and waste, and agricultural runoff. The APCS-MLR receptor model further revealed that agricultural drainage factors and the discharge of domestic effluent and waste had a greater impact on the Mundeswari River. The investigation concluded that the mean values of all indicators for irrigation suitability were below the defined threshold limits, indicating that the water of the studied river appears suitable for irrigation. The outcomes of this study may significantly contribute to the formulation of sustainable strategies for the ecological rejuvenation of the Mundeswari River.

BACKGROUND: Alactic base excess (ABE) is a novel biomarker to evaluate the renal capability of handling acid-base disturbances, which has been found to be associated with adverse prognosis of sepsis and shock patients. This study aimed to evaluate the association between ABE and the risk of in-hospital mortality in patients with acute myocardial infarction (AMI).
METHODS: This retrospective cohort study collected AMI patients\' clinical data from the Medical Information Mart for Intensive Care (MIMIC)-IV database. The outcome was in-hospital mortality after intensive care unit (ICU) admission. Univariate and multivariate Cox proportional hazards models were performed to assess the association of ABE with in-hospital mortality in AMI patients, with hazard ratios (HRs) and 95% confidence intervals (CI). To further explore the association, subgroup analyses were performed based on age, AKI, eGFR, sepsis, and AMI subtypes.
RESULTS: Of the total 2779 AMI patients, 502 died in hospital. Negative ABE (HR = 1.26, 95%CI: 1.02-1.56) (neutral ABE as reference) was associated with a higher risk of in-hospital mortality in AMI patients, but not in positive ABE (P = 0.378). Subgroup analyses showed that negative ABE was significantly associated with a higher risk of in-hospital mortality in AMI patients aged>65 years (HR = 1.46, 95%CI: 1.13-1.89), with eGFR<60 (HR = 1.35, 95%CI: 1.05-1.74), with AKI (HR = 1.32, 95%CI: 1.06-1.64), with ST-segment elevation acute myocardial infarction (STEMI) subtype (HR = 1.79, 95%CI: 1.18-2.72), and without sepsis (HR = 1.29, 95%CI: 1.01-1.64).
CONCLUSIONS: Negative ABE was significantly associated with in-hospital mortality in patients with AMI.

BACKGROUND: Patients in the intensive care unit (ICU) are highly susceptible to malnutrition, and while enteral nutrition via nasogastric tube is the preferred method, there is a risk of inadvertent reflux and aspiration. Therefore, clinicians have turned to nasointestinal tubes (NET) for enteral nutrition as an alternative option. But the precise localization of NET presents an ongoing challenge. We proposed an innovative approach to provide a valuable reference for clinicians involved in NET placement.
METHODS: Data were obtained retrospectively from the medical records of adult patients with a high risk of aspiration or gastric feeding intolerance who had a NET placed in the ICU of Zhejiang Provincial People\'s Hospital between October 1, 2017, and October 1, 2023. The collected data were subjected to statistical analysis using SPSS and R software.
RESULTS: There were 494 patients who met the inclusion and exclusion criteria. The first-pass success rate was 81.4% (n = 402). The success of a patient\'s initial NET placement was found to be associated with Angle SPC and Distance CP, as determined by univariate analysis (25.6 ± 16.7° vs. 41.9 ± 18.0°, P < 0.001; 40.0 ± 26.2 mm vs. 62.0 ± 31.8 mm, P < 0.001, respectively). By conducting a multivariate regression analysis, we identified a significant association between pyloric types and the success rate of placing NET (OR 29.559, 95%CI 14.084-62.038, P < 0.001).
CONCLUSIONS: Angle SPC, Distance CP, and the type of pylorus are independently associated with successful initial placement of NET. Besides, patients with the outside type of pylorus (OP-type) exhibit a higher rate of initial placement success.

OBJECTIVE: Neuroticism was found to be associated with cerebral small vessel disease (CSVD) in observational studies. We aimed to explore the causal relationship between distinct components of neuroticism and CSVD.
METHODS: Two-sample mendelian randomization (MR) study was conducted to explore the bidirectional causal relationships between three genetically distinct subclusters of neuroticism (depressed affect, worry, and sensitivity to environmental stress and adversity [SESA]) and MRI markers of CSVD using publicly available genome-wide association studies (GWAS) data. Inverse variance weighted (IVW) method was used for the primary causal estimates. Alternative MR approaches and extensive sensitivity analyses were conducted to ensure the robustness of the findings. Multivariable MR (MVMR) analysis was used to estimate the direct causal effects with adjustment of other known risk factors for CSVD.
RESULTS: Genetically determined SESA was significantly associated with reduced fractional anisotropy (FA) (beta: -1.94, 95%CI: -3.04 to -0.84, p=5.29e-4), and associated with increased mean diffusivity (MD) (beta=1.55, 95%CI: 0.29 to 2.81, p=0.016) and white matter hyperintensities (WMH) (beta=0.25, 95% CI: 0.03 to 0.47, p=0.029) at the nominally significant level. MVMR analysis suggested the significant associations remained significant after accounting for body mass index (BMI), smoking, alcohol drinking, type 2 diabetes (T2D), hypertension, and depression. The other two neuroticism subclusters (depressed affect and worry) didn\'t have significant causal effects on the MRI markers. In the reverse MR analysis with the MRI markers as exposures, no significant associations were found.
CONCLUSIONS: This study supported the casual role of SESA in the development of CSVD. Further research to explore the underlying mechanism are warranted.

BACKGROUND: The aim of our study was to investigate serum chitotriosidase level in tuberculosis patients, its relationship with microbiological and clinical parameters, and response to treatment.
METHODS: This longitudinal panel study included 149 patients with confirmed TB disease. Serum chitotriosidase activity was measured at the beginning and the end of treatment. Factors associated with chitotriosidase activity were explored using univariate and multivariable logistic regression analysis.
RESULTS: Out of 149 study participants, 71(47.7%) were female. The mean age was 53.0 (SD = 18.2). Majority of cases were new 118(79.2), predominantly 145 (97.3%) having pulmonary tuberculosis. More than half of the patients were sputum smear positive 91 (61.1%) while culture positive in 146 (98%) of them. According to radiological findings, cavitary lesions were found in 92 (63.4%) patients. Anti TB treatment was associated with significant decrease in serum chitotriosidase level (< 0.001). New TB treatment (OR = 4.41%;95% CI = 1.20-9.89), and cavitary lesions (OR = 3.86;95%CI = 0,59-26.57) were found to be significantly associated with decrease of chitotriosidase activity.
CONCLUSIONS: The results of our study showed that serum chitotriosidase values are strong biomarkers for starting anti TB treatment and for treatment monitoring, since decrease in serum chitotriosidase level can predict favorable treatment response in patients with tuberculosis. Further studies are needed to explore these, and other factors associated with chitotriosidase activity among tuberculosis patients.

Researchers often perform data-driven variable selection when modeling the associations between an outcome and multiple independent variables in regression analysis. Variable selection may improve the interpretability, parsimony and/or predictive accuracy of a model. Yet variable selection can also have negative consequences, such as false exclusion of important variables or inclusion of noise variables, biased estimation of regression coefficients, underestimated standard errors and invalid confidence intervals, as well as model instability. While the potential advantages and disadvantages of variable selection have been discussed in the literature for decades, few large-scale simulation studies have neutrally compared data-driven variable selection methods with respect to their consequences for the resulting models. We present the protocol for a simulation study that will evaluate different variable selection methods: forward selection, stepwise forward selection, backward elimination, augmented backward elimination, univariable selection, univariable selection followed by backward elimination, and penalized likelihood approaches (Lasso, relaxed Lasso, adaptive Lasso). These methods will be compared with respect to false inclusion and/or exclusion of variables, consequences on bias and variance of the estimated regression coefficients, the validity of the confidence intervals for the coefficients, the accuracy of the estimated variable importance ranking, and the predictive performance of the selected models. We consider both linear and logistic regression in a low-dimensional setting (20 independent variables with 10 true predictors and 10 noise variables). The simulation will be based on real-world data from the National Health and Nutrition Examination Survey (NHANES). Publishing this study protocol ahead of performing the simulation increases transparency and allows integrating the perspective of other experts into the study design.

OBJECTIVE: Schizophrenia is characterized by alterations in resting-state spontaneous brain activity; however, it remains uncertain whether variations at diverse spatial scales are capable of effectively distinguishing patients from healthy controls. Additionally, the genetic underpinnings of these alterations remain poorly elucidated. We aimed to address these questions in this study to gain better understanding of brain alterations and their underlying genetic factors in schizophrenia.
METHODS: A cohort of 103 individuals with diagnosed schizophrenia and 110 healthy controls underwent resting-state functional MRI scans. Spontaneous brain activity was assessed using the regional homogeneity (ReHo) metric at four spatial scales: voxel-level (Scale 1) and regional-level (Scales 2-4: 272, 53, 17 regions, respectively). For each spatial scale, multivariate pattern analysis was performed to classify schizophrenia patients from healthy controls, and a transcriptome-neuroimaging association analysis was performed to establish connections between gene expression data and ReHo alterations in schizophrenia.
RESULTS: The ReHo metrics at all spatial scales effectively discriminated schizophrenia from healthy controls. Scale 2 showed the highest classification accuracy at 84.6%, followed by Scale 1 (83.1%) and Scale 3 (78.5%), while Scale 4 exhibited the lowest accuracy (74.2%). Furthermore, the transcriptome-neuroimaging association analysis showed that there were not only shared but also unique enriched biological processes across the four spatial scales. These related biological processes were mainly linked to immune responses, inflammation, synaptic signaling, ion channels, cellular development, myelination, and transporter activity.
CONCLUSIONS: This study highlights the potential of multi-scale ReHo as a valuable neuroimaging biomarker in the diagnosis of schizophrenia. By elucidating the complex molecular basis underlying the ReHo alterations of this disorder, this study not only enhances our understanding of its pathophysiology, but also pave the way for future advancements in genetic diagnosis and treatment of schizophrenia.