Strong Predictor Research Articles

Effects of spruce budworm defoliation on in-stream algal production and carbon use by food webs

Insect defoliation is a widespread cause of forest disturbance in Canada, and it has the potential to alter terrestrial carbon contributions to stream consumers and thus affect stream ecosystems. Although defoliation by spruce budworms ( Choristoneura fumiferana) is considered a natural disturbance with importance to forest succession, the magnitude and duration of outbreaks are increasing, and there is a growing need to understand their downstream consequences. To examine this, algal productivity and autochthonous (in-stream) energy supporting macroinvertebrate and fish consumers (using δ13C, δ15N) were examined in 12 streams in the Gaspé Peninsula, Québec, Canada, that ranged in watershed defoliation from spruce budworm. Hierarchical partitioning models were used to assess the contributions of watershed and stream variables to these endpoints. Total seasonal algal production ranged fourfold among sites, and cumulative defoliation was the strongest predictor. Consumers from streams with greater defoliation (cumulative or annual) had lower reliance on autochthonous carbon, despite increased algal production, and this effect was greater for brook trout than macroinvertebrates. These findings demonstrate for the first time that insect outbreaks—which alter forest structure and function—also similarly affect downstream aquatic ecosystems by causing changes in the production and contributions of carbon sources. This suggests that insect control strategies and forest management decisions should also consider implications for downstream aquatic ecosystems.

Ovarian response to controlled stimulation and its predictors in a limited-resource setting

BackgroundInfertility remains a serious health concern for Ethiopian women. Most of its treatment approaches entail controlled ovarian stimulation, the responses of which vary. However, there are no data on ovarian response to stimulation or its predictors in our situation. Thus, the current study aimed to assess the ovarian response to controlled stimulation and identify predictors.MethodsA retrospective follow-up study was undertaken from April 1, 2021, to March 31, 2022, among patients who had first-cycle controlled ovarian stimulation at St.Paul’s Hospital Fertility Center in Addis Ababa, Ethiopia. Clinical data were extracted using a checklist. SPSS-26 for data analysis and Epidata-4.2 for data entry were employed. The binary logistic regression model was fitted. A p-value < 0.05 indicated a significant association. The ROC curve was used to determine cutoff values and identify accurate predictors.ResultsA total of 412 study participants were included in the final analysis. The patients had a mean age of 32.3 ± 5.1 years (range: 20 − 4). The good ovarian response rate was 67% (95% CI: 62.2–71.5). An anti-Mullerian hormone (AMH) concentration < 1.2ng/ml (AOR = 0.19, 95% CI (0.06–0.57)), an antral follicle count (AFC) < 5 (AOR = 0.16, 95% CI (0.05–0.56)), and an induction length < 10 days (AOR = 0.23, 95% CI (0.06–0.93)) were significantly associated with ovarian response. The prediction accuracies for the AFC and AMH concentrations were 0.844 and 0.719, respectively. The optimal cutoff point for prediction was 5.5 AFC, which had a sensitivity of 77.2% and a specificity of 72.8%. However, its positive and negative predictive values were 85.2% and 61.1%, respectively. For AMH, the optimal cutoff value was 0.71ng/mL, with a corresponding sensitivity and specificity of 65.2% and 66%. At this value, the positive and negative predictive values were 63.8% and 67.3%, respectively.ConclusionOnly two-thirds of our patients achieved a good ovarian response. Induction duration, AMH concentration, and AFC were found to be predictors, with the AFC being the strongest predictor. Therefore, the AFC should be performed on all of our patients, and the AMH is selectively employed. Future research must verify the best cutoff points and investigate additional factors affecting ovarian response.

Insulin sensitivity estimates and their longitudinal association with coronary artery disease in type 1 diabetes. Does it matter?

BackgroundInsulin resistance and chronic kidney disease are both associated with increased coronary artery disease risk. Many formulae estimating glucose disposal rate in type 1 diabetes infer insulin sensitivity from clinical data. We compare associations and performance relative to traditional risk factors and kidney disease severity between three formulae estimating the glucose disposal rate and coronary artery disease in people with type 1 diabetes.MethodsThe baseline glucose disposal rate was estimated by three (Williams, Duca, and Januszewski) formulae in FinnDiane Study participants and related to subsequent incidence of coronary artery disease, by baseline kidney status.ResultsIn 3517 adults with type 1 diabetes, during median (IQR) 19.3 (14.6, 21.4) years, 539 (15.3%) experienced a coronary artery disease event, with higher rates with worsening baseline kidney status. Correlations between the three formulae estimating the glucose disposal rate were weak, but the lowest quartile of each formula was associated with higher incidence of coronary artery disease. Importantly, only the glucose disposal rate estimation by Williams showed a linear association with coronary artery disease risk in all analyses. Of the three formulae, Williams was the strongest predictor of coronary artery disease. Only age and diabetes duration were stronger predictors. The strength of associations between estimated glucose disposal rate and CAD incidence varied by formula and kidney status.ConclusionsIn type 1 diabetes, estimated glucose disposal rates are associated with subsequent coronary artery disease, modulated by kidney disease severity. Future research is merited regarding the clinical usefulness of estimating the glucose disposal rate as a coronary artery disease risk factor and potential therapeutic target.

Orchid trade at the source: Epiphytic species with conspicuous flowers in low‐elevation forests are more locally collected in a Philippine key biodiversity area

AbstractOrchids are the most heavily traded plant group globally, putting pressure on wild populations in many source countries like the Philippines. Despite its rich orchid diversity, there remains a notable gap in understanding the factors driving orchid trade within the country. To address this knowledge gap and support orchid conservation efforts, we utilized a 5‐year orchid diversity dataset extensively collected through floristic field and village garden surveys in one of the largest key biodiversity areas in the southern Philippines. We employed a trait‐based approach to investigate ecological drivers of local orchid collection within this source area. Our results show that around 36% of local orchid diversity have predicted collection risks of ≥50%. Notably, locally collected orchid species exhibited multiple, large, and conspicuously colored flowers that are found in low‐elevation forests and higher up in forest stratum. Elevational distribution and flower size emerged as the strongest predictors, potentially influencing collection preferences. Our analysis of predicted collection risks underscores the vulnerability of both threatened and non‐threatened orchid species to local collection pressures. Moreover, we highlight the practical utility of our trait‐based approach in predicting risks and informing management strategies for local orchid conservation. This research marks a significant step toward identifying ecological drivers influencing orchid trade at its source, providing insights that can inform targeted conservation strategies across many key biodiversity areas for this highly diverse, charismatic, and threatened plant family.

The role of serum chloride ion in the prognosis of COPD

Background: As exacerbations of chronic obstructive pulmonary disease (COPD) are one of the leading causes of hospitalization and are associated with significant mortality, it is particularly important to accurately assess the risk of exacerbations in COPD. Most of the current clinical biomarkers are related to inflammation and few consider how ion levels affect COPD. While chloride ions, the second most abundant serum electrolyte, have been shown to be associated with poor prognosis in several diseases, but their relationship with COPD remains unclear. Methods: In total, 105 patients with acute exacerbations of COPD were recruited. Data on clinical characteristics, lung function, blood count, blood biochemistry, relevant scales including the Clinical COPD Questionnaire (CCQ), BODE (BMI, airflow obstruction, dyspnea, exercise capacity) index and the St George's Respiratory Questionnaire (SGRQ) were collected from all patients for statistical analysis. Result: There were significant differences in lung function indicators and disease severity in the low chloride ion subgroup compared with the high chloride ion subgroup. On multiple logistic regression analysis, chloride ion was an independent factor affecting lung function in COPD patients (OR= 0.823, 95% CI: 0.730 - 0.929, p=0.002). The sensitivity of chloride ion in predicting COPD severity was 78%, the specificity was 63% and the area under the curve was 0.724 (p < 0.001). Subgroup analysis showed that chloride ion was a stronger predictor in male, smoking patients. Conclusions: Chloride ion is a novel prognostic biomarker for COPD, and low levels of chloride ion are independently associated with exacerbations in COPD patients.

The differential effect of psychopathy on active and bystander trolling behaviors: the role of dark tetrad traits and lower agreeableness.

This study aimed to develop the Global Assessment of Active Trolling and Passive Bystanderism (GAATPB) scale and investigate the influence of personality traits on trolling behaviors. Focusing on the Dark Tetrad (DT) traits and agreeableness, the present study examined their associations and predictive utility on active trolling and passive bystanderism. Participants were recruited from social networking sites (SNSs), and eligibility criteria included active SNS usage and engagement in online interactions. A total of 797 healthy adult students participated in the study, with data from 300 used for the initial exploratory factor analysis (EFA) and the remaining 497 (Mage = 22.25years, SD = 3.37) for the subsequent analyses. Results indicated a significant correlation between DT traits and agreeableness across both active trolling and passive bystanderism, revealing a shared personality profile. Hierarchical multiple regression analyses showed that narcissism, Machiavellianism, and trait sadism were predictors of active trolling, with psychopathy being the strongest predictor. However, psychopathy did not emerge as a predictor for passive bystanderism. The study also highlighted that DT traits mediated the relationship between lower agreeableness and overall trolling behavior, suggesting that trolling manifests from lower agreeableness through the instigation of callous-unemotional, manipulative, and self-centered traits inherent in DT.

Grade six students’ multidigit arithmetic strategy adaptivity and flexibility: evaluating a novel tri-phase assessment tool

In this paper we present a novel adaptation of a tri-phase assessment tool, originally devised to investigate students’ linear equations-related strategy flexibility, to evaluate Danish grade-six students’ multidigit arithmetic-related strategy adaptivity and flexibility. Participants, 731 students, median age 12 years and drawn from 20 demographically different schools, completed a series of positive integer addition, subtraction and multiplication tasks designed to elicit shortcut strategies. First, students solved each task by means of their preferred strategy, with those using a shortcut strategy being defined as showing adaptivity for that task. Second, students solved the same tasks by means of whatever alternative strategies they could devise; those that offered at least two strategies were defined as showing flexibility for that task. Third, for each task, students were asked to indicate which of their strategies they believed was optimal. Statistical analyses, based on the total number of tasks on which students demonstrated adaptivity or flexibility, found students to be more flexible than adaptive, with 55% of students showing moderate or high levels of flexibility but only 21% for adaptivity. Both strategy adaptivity and flexibility, which differed according to operation, were implicated in students’ solution accuracy, with adaptivity being a stronger predictor than flexibility.

Serological profiling of pneumococcal proteins reveals unique patterns of acquisition, maintenance and waning of antibodies throughout life.

Streptococcus pneumoniae is a leading cause of morbidity and mortality in children and older adults. Yet knowledge on the development of pneumococcal protein-specific antibody responses throughout life is limited. To investigate this, we measured serum IgG levels to 55 pneumococcal proteins in 11-month old infants (n=73), 24-month old children (n=101), parents (n=99), adults without children <6 years of age (n= 99) and older adults aged >60 years (n=100). Our findings revealed low IgG levels in infancy, with distinct development patterns peaking in adults. A decrease in levels was observed for 27 antigens towards older age. Adults and older adults had increased IgG levels during pneumococcal carriage and at increased exposure risk to S. pneumoniae. Carriage was a stronger predictor than exposure or age for antibody responses. These findings highlight the dynamic nature of naturally acquired humoral immunity to pneumococcal proteins throughout life, offering insights for age-targeted interventions.

Determinants of circulating calcitriol in cardiovascular disease

Circulating calcitriol may contribute to the risk of cardiovascular disease (CVD), but its regulation in patients with CVD is poorly characterized. We therefore aimed to assess determinants of circulating calcitriol in these patients. We analyzed 2183 independent samples from a large cohort of patients scheduled for coronary angiography and 1727 independent samples from different other cohorts from patients with a wide range of CVDs, including heart transplant candidates, to quantify the association of different parameters with circulating calcitriol. We performed univariable and multivariable linear regression analyses using the mathematical function that fitted best with circulating calcitriol. In the multivariable analysis of the large single cohort, nine parameters remained significant, explaining 30.0 % (32.4 % after exclusion of 22 potential outliers) of the variation in circulating calcitriol (r=0.548). Log-transformed 25-hydroxyvitamin D [25(OH)D] and log-transformed glomerular filtration rate were the strongest predictors, explaining 17.6 % and 6.6 %, respectively, of the variation in calcitriol. In the analysis of the combined other cohorts, including heart transplant candidates, the multivariable model explained a total of 42.6 % (46.1 % after exclusion of 21 potential outliers) of the variation in calcitriol (r=0.653) with log-transformed fibroblast growth factor-23 and log-transformed 25(OH)D explaining 29.0 % and 6.2 %, respectively. Circulating 25(OH)D was positively and FGF-23 inversely associated with circulating calcitriol. Although significant, PTH was only a weak predictor of calcitriol in both analyses (<2.5 %). In patients with CVD, FGF-23 and 25(OH)D are important independent determinants of circulating calcitriol. The relative importance of these two parameters may vary according to CVD severity. Future studies should focus on the clinical importance of regulating circulating calcitriol by different parameters.

Temperature, Water Depth, and Flow Velocity Are Important Drivers of Methane Ebullition in a Temperate Lowland Stream

AbstractStreams and rivers are a well‐recognized source of methane (CH4), with high spatiotemporal variability in fluxes. However, CH4 release in form of bubbles (ebullition) is rarely included in current global CH4 emission estimates from lotic ecosystems, due to the lack of reliable models to upscale ebullition. Our study aimed to determine the importance of individual emission pathways (diffusion and ebullition) for total CH4 emissions from a lowland stream with low sediment heterogeneity and explore the relations of ebullition to environmental variables to build a stream ebullition model for this simplified system. We measured CH4 and carbon dioxide (CO2) diffusive emissions and ebullition from a temperate lowland stream in Czech Republic (Central Europe) during the ice‐free season 2021. The studied stream was a significant source of CH4 (mean 260 ± 107 mg CH4 m−2 day−1), with ebullition as a prevailing pathway of CH4 emission (mean 74 ± 7%, range 55%–85%) throughout the whole monitored period. CH4 ebullition showed a high spatiotemporal heterogeneity, with sediment temperature and water depth as the strongest predictors, followed by the interaction between flow velocity and sediment temperature. Our model explained 81% of total variance of CH4 ebullition and suggests that it is possible to model ebullitive fluxes in lowland streams with homogeneous sediments. Since CH4 was an important part of the total CO2‐equivalent emissions from the examined stream, accounting for mean (±SD) 35 ± 7.4%, and ebullition the majority of the CH4 emission, the ability to adequately model ebullition is pertinent for lowland streams.

Association between predicted fat mass, predicted lean mass, predicted percent fat and type 2 diabetes mellitus in Japanese adults: a retrospective study.

Type 2 diabetes mellitus (T2DM) is known to have obesity as a risk factor. Body mass index cannot distinguish between lean mass and fat mass. We aimed to examine the association between predicted fat mass, predicted lean mass, predicted percent fat and risk of T2DM in Japanese adults. We also explored whether these three new parameters could predict T2DM better than other obesity markers. This present study is a secondary data analysis. The study enrolled 20,944 Japanese individuals who participated in the NAGALA medical assessment program between 2004 and 2015. 15,453 participants who are eligible and have complete information were included to our analysis. Through the use of Kaplan-Meier curve, restricted cubic spline and univariate and multivariate Cox regression analysis, the relationship between predicted fat mass, predicted lean mass, predicted percent fat and T2DM risk was examined. The area under the curve method was used to assess the differences between these markers of obesity. A total of 373 cases of T2DM occurred over a median time of 5.4 years. In the male group, we found a U-shaped connection between predicted fat mass, predicted lean mass, and T2DM onset (p value, non-linearity < 0.05). A linear relationship was found between predicted percent fat and T2DM onset. The linear relationship was also found in the female group for predicted fat mass, and predicted percent fat. And for women, predicted lean mass was not an independent predictor. The area under the curve (AUC) for predicted fat mass, predicted lean mass, predicted percent fat in men was 0.673 (95%CI: 0.639 ~ 0.707), 0.598 (95%CI: 0.561 ~ 0.635), 0.715 (95%CI: 0.684 ~ 0.745), respectively. In males, WHtR was the strongest predictor (AUC 0.7151, 95%CI: 0.684 ~ 0.746), followed by predicted percent fat (AUC 0.7150, 95%CI: 0.684 ~ 0.745). In the females, WHtR was also the strongest predictor (AUC 0.758, 95%CI: 0.703 ~ 0.813), followed by body mass index (AUC 0.757, 95%CI: 0.704 ~ 0.811) and predicted percent fat (AUC 0.742, 95%CI: 0.687 ~ 0.798). Predicted fat mass, predicted lean mass, predicted percent fat were strongly connected with an increased risk for developing T2DM in Japanese, particularly in males. WHtR and predicted percent fat had a slightly better discrimination than other common obesity indicators in males. In the females, predicted fat mass and predicted percent fat were associated with T2DM risk, WHtR and body mass index had the slightly higher predictive power.

EXAMINING THE ONLINE LEARNING CHALLENGES AND ITS RELATIONSHIP ON LEARNING PERFORMANCE: CASE AT SELECTED SCHOOLS

This study aims to investigate the challenges derived from implementing online learning and its effect on students' learning performances. The key challenges mentioned in this study were the learning resources, learning environment, self-discipline and technological sufficiency. In specific, it is to assess the relationship between the selected independent variables i.e. the key challenges with the dependent variable (learning performances). Research suggests that online learning has been shown to increase retention of information among students and consume less time. It is the objective of the researcher in this study to illustrate and present the effectiveness, relevancy and applicability of online learning as an alternative to sustainable education in government schools. Although quite a number of studies have been performed and some researchers have delved deep into their interest in investigating these issues, however, researchers still found limited information from online learning specifically on the challenges which crucially affect students’ learning performance. To achieve this goal, a total of 210 samples of students from two government secondary schools have been taken into consideration, and (from SMK Baru Bintulu and SMK Bintulu). The data collection technique was carried out by distributing questionnaires and all data were gathered, processed and analyzed using statistical technique SPSS version 26. The descriptive analysis was used to gauge various responses across various dimensions such as in the respondent’s demographic information, additionally, inferential analysis was mainly for examining the relationship between the challenges (learning resources, learning environment, self-discipline and technological sufficiency) and student’s learning performance. The results revealed learning environment challenge is the strongest predictor in influencing student’s learning performance with unstandardized coefficients, β = .356, t = 4.726 p &amp;lt;.05, followed by self-regulation challenge with β = .316, t = 4.182, p &amp;lt;.05. The most significant contribution of this study is that it explores for the first time the investigation of challenges and effect of online learning on students’ learning performance among students at government schools, this has brought a crucial impact and pushed to the government to take immediate action regarding the matter.&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/edu/0118/a.php" alt="Hit counter" /&gt;&lt;/p&gt;

Hypoxia forecasting for Chesapeake Bay using artificial intelligence

Abstract Seasonal hypoxia is a recurring threat to ecosystems and fisheries in the Chesapeake Bay. Hypoxia forecasting based on coupled hydrodynamic and biogeochemical models has proven useful for many stakeholders, as these models excel in accounting for the effects of physical forcing on oxygen supply, but may fall short in replicating the more complex biogeochemical processes that govern oxygen consumption. Satellite-derived reflectances could be used to indicate the presence of surface organic matter over the Bay. However, teasing apart the contribution of atmospheric and aquatic constituents from the signal received by the satellite is not straightforward. As a result, it is difficult to derive surface concentrations of organic matter from satellite data in a robust fashion. A potential solution to this complexity is to use deep learning to build end-to-end applications that do not require precise accounting of the satellite signal from atmosphere or water, phytoplankton blooms, or sediment plumes. By training a deep neural network with data from a vast suite of variables that could potentially affect oxygen in the water column, improvement of short-term (daily) hypoxia forecast may be possible. Here we predict oxygen concentrations using inputs that account for both physical and biogeochemical factors. The physical inputs include wind velocity reanalysis information, together with 3D outputs from an estuarine hydrodynamic model, including current velocity, water temperature, and salinity. Satellite-derived spectral reflectance data are used as a surrogate for the biogeochemical factors. These input fields are time series of weekly statistics calculated from daily information, starting 8 weeks before each oxygen observation was collected. To accommodate this input data structure, we adopted a model architecture of long short-term memory networks with 8 time steps. At each time step, a set of convolutional neural networks are used to extract information from the inputs. Ablation and cross validation tests suggest that among all input features, the strongest predictor is the 3D temperature field, with which the new model can outperform the state-of-the-art by ∼20% in terms of median absolute error. Our approach represents a novel application of deep learning to address a complex water management challenge.

Factors Associated With Premature Termination of Hyperacute Stroke Trials: AReview.

We performed a review of acute stroke trials to determine features associated with premature termination of trial enrollment, defined by the authors as not meeting preplanned sample size. MEDLINE was searched for randomized clinical stroke trials published in 9 major clinical journals between 2013 and 2022. We included randomized clinical trials that were phase 2 or 3 with a preplanned sample size ≥100 and a time-to-treatment within 24 hours of onset for transient ischemic attack, ischemic stroke, or intracerebral hemorrhage. Data were abstracted on trial features including trial design, inclusion criteria, imaging, location and number of sites, masking, treatment complexity, control group (standard therapy, placebo), industry involvement, and preplanned stopping rules (futility and efficacy). Least absolute shrinkage and selection operator regression was used to select the most important factors associated with premature termination; then, a multivariable logistic regression was fit including only the least absolute shrinkage and selection operator selected variables. Of 1475 studies assessed, 98 trials met eligibility criteria. Forty-five (46%) trials were prematurely terminated, of which 27% were stopped for benefit/efficacy, 20% for lack of money/slow enrollment, 18% for futility, 16% for newly available evidence, 17% for other reasons, and 4% due to harm. Complex trials (adjusted odds ratio [aOR], 2.76 [95% CI, 1.13-7.49]), presence of a futility rule (aOR, 4.43 [95% CI, 1.62-17.91]), and exclusion of prestroke dependency (none/slight disability only; aOR, 2.19 [95% CI, 0.84-6.72] versus dependency allowed) were identified as the strongest predictors. Nearly half of acute stroke trials were terminated prematurely. Broadening inclusion criteria and simplifying trial design may decrease the likelihood of unplanned termination, whereas planned futility analyses may appropriately terminate trials early, saving money and resources.

Crossectional Study on the Performance of Screening Questionnaires for Prediction of Moderate to Severe Obstructive Sleep Apnea in Women

Abstract Introduction The clinical manifestations of obstructive sleep apnea (OSA) are different between genders. Though there are several screening questionnaires for OSA, their performance in females is not fully understood, as women have been historically underrepresented in research studies. Objective To assess the performance of screening questionnaires and their capacity to identify a moderate to severe apnea-hypopnea index (AHI) in women. Materials and Methods The Epworth sleep scale (ESS), Berlin questionnaire, and STOP-BANG questionnaire (SBQ) were correlated with AHI. Also, the sensitivity (S), specificity (Sp), and area under the receiver operating characteristic (AUC-ROC) curve were calculated for each questionnaire and combinations thereof. Multiple regression models were used to identify ≥15 ev/h AHI. Results Our study included 5,344 patients: 1978 women (37.1%) aged 55.06 ± 14 years with body mass index (BMI): 32.6 ± 8.30 kg/m2, ESS: 7.69 ± 5.2 points, and high-risk Berlin score: 87.25%. An AHI ≥15 ev/h was found in 30.4% of women. In terms of the capacity to identify an ≥15 ev/h AHI in women, the AUC-ROC of ESS &gt;10 and high-risk Berlin was 0.53 and 0.58, respectively. Three components of SBQ in any combination showed: a S of 65.1% (95% CI: 61.2–68.9), a Sp: 61.5% (95% CI: 58.9–64.1), with the AUC-ROC: 0.67. Conclusions Questionnaires perform differently in women. Therefore, it is necessary to take a gender-specific approach. The SBQ showed a higher discriminative power and more specificity than the ESS and the Berlin questionnaire. The best performance was obtained with any combination of 3 SBQ components. Age, BMI, neck circumference, and hypertension were the strongest predictors.

Influences of Nursing Professionalism, Empathy, and Clinical Decision-Making Ability on Shared Decision-Making Awareness among Hemodialysis Nurses

Aim. To examine the relationships among nursing professionalism, empathy, and clinical decision-making ability and the factors influencing shared decision-making awareness in hemodialysis nurses. Background. Self-management and treatment for hemodialysis patients are essential for maintaining health and life in daily life. In this process, shared decision-making in which patients, nurses, and medical teams participate and make decisions together has a greater impact on the health recovery and improvement of quality of life for hemodialysis patients than for any other chronic disease patients. Methods. A cross-sectional descriptive design was employed. Participants were 145 nurses working in the hemodialysis centers at hospitals in Seoul and Gyeonggi-do. Measures included the general characteristics of study participants, nursing professionalism, empathy, clinical decision-making ability, and shared decision-making awareness. Data were collected from May to July, 2022, and multiple linear regression analysis was used to examine the predictive factors of shared decision-making awareness. Results. The strongest predictor was empathy, followed by clinical decision-making ability and the level of education. The explanatory power of the final regression model was 23%. Conclusions. Empathy towards hemodialysis patients was an important factor influencing the shared decision-making awareness in hemodialysis nurses. Implications for Nursing Management. In nursing management, nursing managers or nurses should pay attention to influencing factors to improve the shared decision-making awareness of hemodialysis nurses. Empathy towards hemodialysis patients need to be reinforced to improve the shared decision-making awareness of hemodialysis nurses.

A comparison of strategies for identifying patients at risk for carbapenem-resistant or extended β-lactam-resistant Pseudomonas aeruginosa.

To assess risk factors for carbapenem-resistant Pseudomonas aeruginosa (CR) and extended-β-lactam-resistant P. aeruginosa (EBR) infection/colonization, and to develop and compare tools for predicting isolation of CR and EBR from clinical cultures. This retrospective study analysed hospitalized patients with positive P. aeruginosa cultures between 2015 and 2021. Two case-control analyses were performed to identify risk factors and develop scoring tools for distinguishing patients with CR versus carbapenem-susceptible (CS) P. aeruginosa and EBR versus CS P. aeruginosa. The performance of institutionally derived scores, externally derived scores and the presence/absence of key risk factors to predict CR and EBR were then compared. A total of 2379 patients were included. Of these, 8.3% had a positive culture for CR, 5.0% for EBR and 86.7% for CS P. aeruginosa. There was substantial overlap in risk factors for CR and EBR. Institutional risk scores demonstrated modestly higher area under the ROC curve values than external scores for predicting CR (0.67 versus 0.58) and EBR (0.76 versus 0.70). Assessing the presence/absence of ≥1 of the two strongest predictors (prior carbapenem use or CR isolation within 90 days) was slightly inferior to scoring tools for predicting CR, and comparable for predicting EBR. Clinicians concerned about CR in P. aeruginosa should consider the likelihood of EBR when making treatment decisions. A simple approach of assessing recent history of CR isolation or carbapenem usage performed similarly to more complex scoring tools and offers a more pragmatic way of identifying patients who require coverage for resistant P. aeruginosa.

The Predictive Value of Virtue: Many Virtues Predict Lower Depression and Anxiety Symptom Scores Among College Students…But Gratitude Dominates

Depression and anxiety symptoms have risen in the last decade, especially among college students. Virtues are potentially strong predictive factors of mental health symptoms, but a minimal amount of research has explored which virtues are the strongest predictors. We examined the relative predictive strength of gratitude, forgiveness, patience, intellectual humility, and self-control using dominance analyses. Results suggested that gratitude had the strongest predictive value for lower anxiety and depressive symptom scores compared to forgiveness, intellectual humility, patience, and self-control. An implication of these findings is that when considering intervention work with young emerging adults, researchers may do well to start with gratitude, then promote other virtues such as forgiveness and self-control.

Centrally Distributed Adiposity as a Modifiable Risk Factor for Fecal Incontinence: United States Population-based Analysis

Fecal incontinence (FI) is highly prevalent with substantial impacts on quality of life and healthcare utilization. The impact of obesity on FI remains unclear, with differing conclusions using BMI as risk factor. We aimed to determine the association between obesity and FI, and whether this relationship is dependent on the distribution of adiposity (waist circumference-to-height ratio, WHtR). This was a population-based analysis of the National Health and Nutrition Examination Survey, including participants who responded to the bowel health survey in 2005-2010. FI was defined by the accidental bowel leakage of solid stool, liquid, or mucus at least once in the past month. Stepwise multivariable logistic regression models were constructed to assess risk factors for FI. A total of 7,606 participants were included, with an overall FI prevalence of 9.2%. When stratified by quartiles of body measurements, FI was increasingly prevalent from 1st to 4th quartile for both WHtR (range: 5.3%-12.5%) and BMI (range: 7.1%-10.5%). WHtR was associated with FI and was a stronger predictor than BMI in all quartiles of body measurement. On multivariable analysis, WHtR remained a significant predictor of FI comparing the 4th to the 1st quartile of body measurements (OR:1.77, CI:1.11-2.80, p=0.017), whereas BMI was not. A WHtR cutoff of >0.592 optimized the Youden index in prediction of FI in the overall sample. WHtR was independently associated with increased odds of FI in this nationally representative sample of US adults, whereas BMI was not consistently correlated. This suggests bowel continence may depend more on how body mass is distributed.

Predictive Factors of Long-Term Neurologic Outcome and Progression-Free Survival in Intramedullary Spinal Cord Tumors: A 10-year Single-Center Cohort Study and Review of the Literature

Intramedullary spinal cord tumors (IMSCTs) are a rare subgroup of neoplasms, encompassing both benign, slow-growing masses, and malignant lesions; radical surgical excision represents the cornerstone of treatment for such pathologies regardless of histopathology, which, on the other hand, is a known predictor of survival and neurologic outcome postsurgery. The present study aims to investigate the relevance of other factors in predicting survival and long-term functional outcomes. We conducted a review of current literature on functional outcomes of IMSCTs, as well as a 10-years prospective analysis of a wide cohort of patients with diagnosis of IMSCTs who underwent surgical resection at our institution. Our series encompasses 60 patients with IMSCTS, among which 36 ependymomas, 6 cavernous angiomas, 5 hemangioblastomas, 6 WHO Grade I-IV astrocytomas, 3 intramedullary spinal metastases and 4 miscellaneous tumors. GTR was achieved in 76,67% of patients, with high preoperative McCormick grade, syringomyelia and changes at neurophysiologic monitoring being the strongest predictors at multivariate analysis (P= 0.0027, P= 0.0017 and P= 0.001 respectively). Consistently with literature, preoperative neurologic function is the most important factor predicting long-term functional outcome (0.17, CI 0.069-0.57 with P= 0.0018), advocating for early surgery in the management of IMSCTs, whereas late complications such as myelopathy and neuropathic pain were present regardless of preoperative function.