Covariates In Model Research Articles

Association between depression severity and trouble sleeping: A population-based study.

This study investigates the association between insomnia and depression severity, exploring sleep disturbances in individuals with depression. The aim is to establish a new foundation for managing patients with co-occurring depression and insomnia, using 2015 to 2016 National Health and Nutrition Examination Survey (NHANES) data. We employed a cross-sectional design, using NHANES data from 2015 to 2018. The study included 11,261 participants after excluding incomplete data. Depression severity, assessed using Patient Health Questionnaire-9 (PHQ-9) scores, served as the exposure variable. We considered various demographic and lifestyle factors as covariates in the multivariate adjustment model. Statistical analyses adhered to CDC recommendations, with sample weights incorporated to account for NHANES' complex sample design. Our study, encompassing 19,225 participants, revealed that higher PHQ-9 scores correlated with an increased likelihood of sleep disorders. In the fully adjusted model, a positive association emerged between PHQ-9 scores and trouble sleeping (OR = 3.95, 95% CI: 3.35-4.66, P < .0001). This relationship displayed an inverted U-shaped curve, with an inflection point at 28. Subgroup analysis and interaction tests indicated no reliance on factors such as gender, age, marital status, or BMI for the connection between depression severity and trouble sleeping (all P for interaction > .05). We identified a significant inverted U-shaped correlation between sleep disturbances and depression severity. This underscores the crucial importance of assessing sleep disorder risks in individuals with varying degrees of depression severity, facilitating personalized therapeutic interventions.

Abstract IA004: Risk of therapy-related subsequent cancers in individuals with germline TP53 variants

Abstract Background. Based primarily on in vitro and animal studies, germline TP53 variants are considered to confer sensitivity to ionizing radiation-induced DNA damage, but data in humans are sparse. We sought to quantify risk of developing radiotherapy and chemotherapy-related subsequent neoplasms by pooling individual-level data from nine cohorts of individuals with confirmed pathogenic/likely pathogenic germline TP53 variants. Methods. 891 individuals were followed from six months after first cancer until diagnosis of a subsequent neoplasm, death or date of last follow-up. Radiotherapy and chemotherapy for each cancer were considered as time-dependent covariates in Cox regression models with age as the time-scale, adjusted for sex and occurrence of prior malignant or benign tumors. Subsequent cancers were classified as in- or out-of-field based on the body region of previous cancers. Results. Among 891 individuals, 643 (72.2%) were female and 297 (33.3%) were diagnosed with a first cancer before age 20 years. Breast cancer was the most commonly diagnosed first cancer (N=371), followed by soft tissue sarcoma (N=131) and central nervous system cancers (N=84). First cancer treatment included radiotherapy for 237 (26.6%) and/or chemotherapy for 421 (47.3%) individuals. Analyses are underway to define the characteristics of subsequent neoplasms (including age at diagnosis, latency, and distribution of diagnosis type) and to calculate relative and absolute risk estimates for radiotherapy and chemotherapy overall and by subsequent neoplasm type. Conclusions. This study will quantify the contribution of radiotherapy and chemotherapy to the risk of subsequent cancers among individuals with Li-Fraumeni syndrome. Understanding the magnitude of this risk will support health care providers and patients in making informed decisions about cancer management. Citation Format: Anita Villani, Payal Khincha, Jessica Hatton, Sara Schonfeld, Catherine Goudie, Leatrisse Oba, Kishan Pithadia, Birte Sänger, Christian Kratz, Anh N. Le, Caitlin Orr, Kara N. Maxwell, Anne Naumer, Jennie Vagher, Wendy Kohlmann, Joshua Schiffman, Elizabeth Santana dos Santos, Orli Michaeli, Jacob J. Carson, Derek S. Tsang, Raymond Kim, Jamie L. Maciaszek, Kim E. Nichols, Victoria E. Goodman, Suzanne P. MacFarland, Lara Reichman, Maria Isabel Achatz, Sharon Savage, David Malkin, Lindsay M. Morton. Risk of therapy-related subsequent cancers in individuals with germline TP53 variants [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr IA004.

Long-lasting effects of in utero heat stress on subsequent performances of heifers and primiparous cows

The performance of an adult dairy cow may be influenced by heat stress that occurs during her gestation. The present study investigated potential effects of temperature-humidity index (THI) experienced by a cow during pregnancy, on the gestated daughter's performance on her first lactation, for the French Holstein and Montbeliarde dairy cattle populations. Fourteen traits were analyzed, all measured on genotyped cows: 305-d milk, fat, and protein yields, 305-d somatic cell score, clinical mastitis (both occurrence and number of events), body conformation traits, and heifer and cow conception rate. To study the effect of heat stress, we considered the THI experienced by the gestating cow, averaged for each month of her pregnancy and then categorized in 7 classes (≤40; 40-45; 45-50; 50-55; 55-60; 60-65; and >65). These average THI classes were then fitted as categorical covariates in the regression models used for this study, which included other fixed effects, and the genomic estimated breeding value as a covariate, both specific to each trait, the latter previously obtained from the official French evaluations. The THI effect was therefore estimated as the deviation between the observed and the predicted performances. In general, the estimated heat stress effects were small, presenting limited practical impact on the studied traits, and particularly for fertility and udder health, the estimated heat stress effects were not statistically significant. For the production traits, i.e., milk, fat, and protein yields, the estimated effect associated to high THI experienced at the beginning of the gestation was negative, and lightly positive when associated to high THI experienced by the dam at the end of her pregnancy. Finally, our results suggest that under the current French climate conditions, heat stress experienced by cows during any stage of their pregnancy has limited impact on future performances of their gestated daughters, however we cannot exclude that significant in utero heat stress effect may be present in climate conditions warmer than the French.

Associations between type 2 diabetes mellitus and risk of falls among community-dwelling elderly people in Guangzhou, China: a prospective cohort study

BackgroundSeveral studies have demonstrated that older adults with type 2 diabetes mellitus (T2DM) have a higher risk of falls compared to those without T2DM, which may lead to disability and a lower quality of life. While, limited prospective studies have quantified the associations in southern China. We conducted a longitudinal cohort study to quantify the associations between T2DM and falls and investigate the risk factors of falls among community-dwelling elderly people in Guangzhou, China.MethodsThe population-based study included 8800 residents aged 65 and over in 11 counties of Guangzhou at baseline in 2020 and then prospectively followed up through 2022. Of 6169 participants had complete follow-up and were included in the present study. A fall event was identified by self-reported. The Cox regression was applied to quantify the associations between T2DM and falls, and hazard ratios (HRs) were calculated to the factors associated with falls among participants.ResultsThe median follow-up time for participants was 2.42 years. During the follow-up period, the incidence of falls among all participants was 21.96%. After adjusting for covariates in Cox regression models, T2DM remained a significant risk factor for falls, with HR of 1.781 (95% CI: 1.600-1.983) in the unadjusted covariates model and 1.757 (1.577–1.957) in the adjusted covariates model. Female (1.286, 1.136–1.457), older age (≥ 80: 1.448, 1.214–1.729), single marital status (1.239, 1.039–1.477), lower education level (primary school and below: 1.619, 1.004–1.361), hypertension (1.149, 1.026–1.286) and stroke (1.619, 1.176–2.228) were associated with a higher risk of falls, whereas everyday physical exercise (0.793, 0.686–0.918) was associated with a lower risk of falls.ConclusionFalls are common, with risks between T2DM and falls quantified and several factors investigated in the longitudinal cohort study among community-dwelling elderly people in Guangzhou, China. Targeted action on the risk factors may reduce the burden of falls in elderly people with T2DM in the future.

Modelling climate change-induced nonstationarity in rainfall extremes: A comprehensive approach for hydrological analysis

Climate change and global warming have induced a dynamic shift in extreme rainfall patterns, leading to nonstationary behaviour. This alteration in behaviour challenges conventional hydrologic design, which assumes stationarity and can yield misleading outcomes. This study aims to address nonstationarity by modelling distribution parameters with covariates. Utilizing a 70-year (1951–2020) high-resolution India Meteorological Department (IMD) gridded dataset, extreme annual rainfall across diverse Indian cities was extracted and modelled. Previous research and goodness-of-fit tests favour the Generalized Extreme Value (GEV) distribution for modelling extremes. This study incorporates indices like Nino3.4, dipole mode index, global and local temperature, CO2, and time to characterize nonstationarity in extreme annual rainfall, leveraging climate cycles and global warming. Performance assessment employs the Akaike information criterion, Bayesian information criterion and Likelihood ratio test, while quantile reliability is evaluated through confidence intervals (CIs). Findings reveal widespread nonstationary trends in most grid points, translating to wider CIs in estimated quantiles for chosen non-exceedance probability and covariates in fitted models. Generally, nonstationary conditions are associated with broader confidence bands in return levels, highlighting nonstationary model weaknesses compared to stationary models. However, the results showed that the rainfall extremes follow a nonstationary pattern. Hence, there is a strong need to develop nonstationary models of low uncertainty.

Under pressure – Association of the arm position and leading circulatory structure behind the pressure point in cardiopulmonary resuscitation patients

BackgroundThoracic computed tomography scans (CT) are used by several study groups to investigate the circulatory structures (heart and vessels) located behind the pressure point for chest compressions. Yet, it remains unclear how the positioning of these structures is influenced by factors such as intubation, the respiratory cycle and arm positioning. MethodsWe retrospectively analyzed data of adult patients with in- or out-of-hospital cardiac arrest who underwent thoracic CT imaging within one year before or up to six months after arrest. A region of interest (ROI) behind the pressure point was defined. The largest structure within this region was defined as “leading circulatory structure”, which was the primary outcome. Airway status (intubated versus spontaneous breathing), respiratory cycle (inspiration, expiration, resting expiratory position), and arm position (up over the head versus down beside the trunk) served as covariates in an ordinal regression model. ResultsAmong 500 initially screened patients, 411 (82.2 %) were included in the analysis. There was a significant association between the arm position and the leading circulatory structure behind the pressure point. However, no association was found with airway status or respiratory cycle. The most frequently identified leading circulatory structure was the left atrium (arms up: 41.8 %, down: 50.7 %), followed by the ascending aorta (up: 23.8 % vs. down: 16.7 %). The left ventricle was the leading structure in only one case (0.2 %, arms down). ConclusionThis study shows that arm position is significantly associated with the leading circulatory structure behind the pressure point for chest compressions in cardiac arrest.

Leveraging local habitat suitability models to enhance restoration benefits for species of conservation concern

AbstractEfforts to restore habitats and conserve wildlife species face many challenges that are exacerbated by limited funding and resources. Habitat restoration actions are often conducted across a range of habitat conditions, with limited information available to predict potential outcomes among local sites and identify those that may lead to the greatest returns on investment. Using the Gunnison sage-grouse (Centrocercus minimus) as a case study, we leveraged existing resource selection function models to identify areas of high restoration potential across landscapes with variable habitat conditions and habitat-use responses. We also tested how this information could be used to improve restoration planning. We simulated change in model covariates across crucial habitats for a suite of restoration actions to generate heatmaps of relative habitat suitability improvement potential, then assessed the degree to which use of these heatmaps to guide placement of restoration actions could improve suitability outcomes. We also simulated new or worsening plant invasions and projected the resulting loss or degradation of habitats across space. We found substantial spatial variation in projected changes to habitat suitability and new habitat created, both across and among crucial habitats. Use of our heatmaps to target placement of restoration actions improved habitat suitability nearly fourfold and increased new habitat created more than 15-fold, compared to placements unguided by heatmaps. Our decision-support products identified areas of high restoration potential across landscapes with variable habitat conditions and habitat-use responses. We demonstrate their utility for strategic targeting of habitat restoration actions, facilitating optimal allocation of limited management resources to benefit species of conservation concern.

3-Dimensional Virtual Reality Versus 2-Dimensional Video for Distraction During the Induction of Anesthesia in Children to Reduce Anxiety: A Randomized Controlled Trial.

Preoperative anxiety is common in children. It can contribute to negative experiences with anesthetic induction and may cause adverse physiological and psychological effects. Virtual reality (VR) and electronic tablet devices are 2 audiovisual distraction tools that may help to reduce anxiety and enhance the preoperative experience. This study aimed to compare the use of an immersive 3-dimensional (3D) VR to 2-dimensional (2D) video on anxiety in children during induction of general anesthesia. Two hundred children (4-13 years) undergoing elective or emergency surgery under general anesthesia were enrolled in this randomized, controlled trial. Participants were randomized to use either the 3D VR goggles (intervention) or 2D video tablet (control) during anesthetic induction. Anxiety, the primary outcome, was measured using the modified Yale Preoperative Anxiety Scale Short Form (mYPAS-SF) at 2 time points: in the preoperative holding area before randomization (T1) and during induction of general anesthesia (T2). The primary outcome was analyzed using a linear regression model, including demographic and other covariates, to investigate any differences in anxiety scores. Secondary outcomes included evaluating compliance during the anesthetic induction (Induction Compliance Checklist), emergence of delirium (Cornell Assessment of Pediatric Delirium), perceived usefulness of the device, and child satisfaction. Participant characteristics were similar between the 3D VR (n = 98) and 2D video (n = 90) groups, with a mean (±standard deviation) age 8. 8 ± 2.8 years. The median (lower quartile, upper quartile) mYPAS-SF scores for the 3D VR group at the preoperative holding area were 22.9 (22.9, 35.4), then 29.2 (24.0, 41.7) during induction. For the 2D Video group, the scores were 27.1 (22.9, 35.4) and then 30.2 (22.9, 41.1). No significant difference was observed in the increase in mYPAS-SF scores between groups (P = .672). Children in the 3D VR group were less likely to be rated as having a perfect induction (P = .039). There was no evidence of a difference between the groups in emergence delirium. Both devices were rated highly for usefulness and patient satisfaction. Children preferred VR, while anesthesiologists and parents felt the 2D was more useful. This randomized controlled trial demonstrated that preoperative anxiety was equally low and induction compliance high with both 3D VR and 2D video distraction in children with parental presence during anesthetic induction.

Landscape-scale predictions of future grassland conversion to cropland or development.

Grassland conservation planning often focuses on high-risk landscapes, but many grassland conversion models are not designed to optimize conservation planning because they lack multidimensional risk assessments and are misaligned with ecological and conservation delivery scales. To aid grassland conservation planning, we developed landscape-scale models at relevant scales that predict future (2021-2031) total and proportional loss of unprotected grassland to cropland or development. We developed models for 20 ecoregions across the contiguous United States by relating past conversion (2011-2021) to a suite of covariates in random forest regression models and applying the models to contemporary covariates to predict future loss. Overall, grassland loss models performed well, and explanatory power varied spatially across ecoregions (total loss model: weighted group mean R2=0.89 [range: 0.83-0.96], root mean squared error [RMSE]=9.29ha [range: 2.83-22.77ha]; proportional loss model: weighted group mean R2=0.74 [range: 0.64-0.87], RMSE=0.03 [range: 0.02-0.06]). Amount of crop in the landscape and distance to cities, ethanol plants, and concentrated animal feeding operations had high variable importance in both models. Total grass loss was greater when there were moderate amounts of grass, crop, or development (∼50%) in the landscape. Proportional grass loss was greater when there was less grass (∼<30%) and more crop or development (∼>50%). Some variables had a large effect on only a subset of ecoregions, for example, grass loss was greater when ∼>70% of the landscape was enrolled in the Conservation Reserve Program. Our methods provide a simple and flexible approach for developing risk layers well suited for conservation that can be extended globally. Our conversion models can support conservation planning by enabling prioritization as a function of risk that can be further optimized by incorporating biological value and cost.

Population Pharmacokinetic-Pharmacodynamic Analysis of a Reserpine-Induced Myalgia Model in Rats.

(1) Background: Fibromyalgia syndrome (FMS) is a chronic pain condition with widespread pain and multiple comorbidities, for which conventional therapies offer limited benefits. The reserpine-induced myalgia (RIM) model is an efficient animal model of FMS in rodents. This study aimed to develop a pharmacokinetic-pharmacodynamic (PK-PD) model of reserpine in rats, linking to its impact on monoamines (MAs). (2) Methods: Reserpine was administered daily for three consecutive days at dose levels of 0.1, 0.5, and 1 mg/kg. A total of 120 rats were included, and 120 PK and 828 PD observations were collected from 48 to 96 h after the first dose of reserpine. Non-linear mixed-effect data analysis was applied for structural PK-PD model definition, variability characterization, and covariate analysis. (3) Results: A one-compartment model best described reserpine in rats (V = 1.3 mL/kg and CL = 4.5 × 10-1 mL/h/kg). A precursor-pool PK-PD model (kin = 6.1 × 10-3 mg/h, kp = 8.6 × 10-4 h-1 and kout = 2.7 × 10-2 h-1) with a parallel transit chain (k0 = 1.9 × 10-1 h-1) characterized the longitudinal levels of MA in the prefrontal cortex, spinal cord, and amygdala in rats. Reserpine stimulates the degradation of MA from the pool compartment (Slope1 = 1.1 × 10-1 h) and the elimination of MA (Slope2 = 1.25 h) through the transit chain. Regarding the reference dose (1 mg/kg) of the RIM model, the administration of 4 mg/kg would lead to a mean reduction of 65% (Cmax), 80% (Cmin), and 70% (AUC) of MA across the brain regions tested. (4) Conclusions: Regional brain variations in neurotransmitter depletion were identified, particularly in the amygdala, offering insights for therapeutic strategies and biomarker identification in FMS research.

A novel block-coordinate gradient descent algorithm for simultaneous grouped selection of fixed and random effects in joint modeling.

Joint models for longitudinal and time-to-event data are receiving increasing attention owing to its capability of capturing the possible association between these two types of data. Typically, a joint model consists of a longitudinal submodel for longitudinal processes and a survival submodel for the time-to-event response, and links two submodels by common covariates that may carry both fixed and random effects. However, research gaps still remain on how to simultaneously select fixed and random effects from the two submodels under the joint modeling framework efficiently and effectively. In this article, we propose a novel block-coordinate gradient descent (BCGD) algorithm to simultaneously select multiple longitudinal covariates that may carry fixed and random effects in the joint model. Specifically, for the multiple longitudinal processes, a linear mixed effect model is adopted where random intercepts and slopes serve as essential covariates of the trajectories, and for the survival submodel, the popular proportional hazard model is employed. A penalized likelihood estimation is used to control the dimensionality of covariates in the joint model and estimate the unknown parameters, especially when estimating the covariance matrix of random effects. The proposed BCGD method can successfully capture the useful covariates of both fixed and random effects with excellent selection power, and efficiently provide a relatively accurate estimate of fixed and random effects empirically. The simulation results show excellent performance of the proposed method and support its effectiveness. The proposed BCGD method is further applied on two real data sets, and we examine the risk factors for the effects of different heart valves, differing on type of tissue, implanted in the aortic position and the risk factors for the diagnosis of primary biliary cholangitis.

Bias correction of the hourly satellite precipitation product using machine learning methods enhanced with high-resolution WRF meteorological simulations

Accurate precipitation data are crucial in atmospheric and hydrological studies, especially for water resource management and disaster early warning. Satellite precipitation product (SPP) with high spatiotemporal resolution has been regarded as a valuable alternative precipitation source to ground observations. However, the hourly SPP generally performs poorly compared to daily SPP, thereby bias correction is urgently required. This study investigates the viability of utilizing machine learning methods to correct the bias of the hourly Integrated Multi-satellitE Retrievals for Global Precipitation Measurement-Early (IMERG-E) product. Meanwhile, the Weather Research and Forecasting (WRF) model is utilized to generate high-resolution fields of four hourly meteorological variables, namely, temperature at 2 m (TEMP2), specific humidity at 2 m (Q2), wind direction at 10 m (WDIR10), and wind speed at 10 m (WSPD10), which further serve as covariates in machine learning models to enhance the correction process. Four machine learning models were developed, i.e., Random Forest (RF) and Bidirectional Long Short-Term Memory Networks (Bi-LSTM) without WRF-simulated covariates, and RF-WRF and Bi-LSTM-WRF with meteorological covariates. The results demonstrated that incorporating WRF-simulated meteorological covariates improved model performance. Specifically, correlation coefficient (CC) values increased from 0.47 (RF) to 0.51 (RF-WRF) and rose from 0.55 (Bi-LSTM) to 0.60 (Bi-LSTM-WRF), along with reduced root mean square error (RMSE) and increased critical success index (CSI) values. Furthermore, two Bi-LSTM models consistently outperformed two RF models. Overall, the Bi-LSTM-WRF model emerged as the most effective correction method, which increased CC from 0.43 (IMERG-E) to 0.60, reduced RMSE from 1.91 mm to 1.08 mm, and enhanced CSI from 0.34 to 0.41. This study underscores the potential of integrating high-resolution WRF meteorological outputs into machine learning frameworks for correcting hourly SPPs, contributing significantly to the advancement of precipitation estimation in meteorological and hydrological applications.

Fusion of Lagrangian drifter data and numerical model outputs for improved assessment of turbulent dispersion

Abstract. Transport and dispersion processes in the ocean are crucial, as they determine the lifetime and fate of biological and chemical quantities drifting with ocean currents. Due to the complexity of the coastal ocean environment, numerical circulation models have difficulties to accurately simulate highly turbulent flows and dispersion processes, especially in highly energetic tidal basins such as the eastern English Channel. A method of improving the results of coastal circulation modeling and tracer dispersion in the Dover Strait is proposed. Surface current velocities derived from Lagrangian drifter measurements in November 2020 and May 2021 were optimally interpolated in time and space to constrain a high-resolution coastal circulation MARS model, with careful attention given to selecting ensemble members composing the model covariance matrix. The space–time velocity covariances derived from model simulations were utilized by the optimal interpolation algorithm to determine the most likely evolution of the velocity field under constraints provided by Lagrangian observations and their error statistics. The accuracy of the velocity field reconstruction was evaluated at each time step. The results of the fusion of model outputs with surface drifter velocity measurements show a significant improvement (by ∼ 50 %) of the model capability to simulate the drift of passive tracers in the Dover Strait. Optimized velocity fields were used to quantify the absolute dispersion in the study area. The implications of these results are important, as they can be used to improve existing decision-making support tool or design new tools for monitoring the transport and dispersion in a coastal ocean environment.

The influence of socioeconomic characteristics on active travel in US metropolitan areas and the contribution to health inequity.

The prevalence of chronic disease in the US adult population varies across socioeconomic groups in the USA where approximately six in 10 adults have a chronic condition. Walking or cycling reduces the risk to many of these diseases and is influenced by the built environment, accessibility, and safety. We performed multivariate logistic and linear regression on the Health-Oriented Transportation model parameters using the 2009 and 2017 US National Household Transportation surveys, restricted to adults in major metropolitan areas. Model covariates included socioeconomic and environmental characteristics. Using odds ratios (OR) adjusted for model covariates, we observe several significant variables in 2009 and 2017. Residents of households with no cars were more likely to walk or cycle than those with two cars; OR=5.4 (4.8, 6.0). Residents of households in a census block with population density greater than 2,5000 persons/square mile were more likely to walk or cycle than those with a population density of 2000-3999; OR=2.6 (2.3, 2.8). Individuals with a graduate or professional degree were more likely to walk or cycle than those with a high school degree; OR=2.1 (1.9, 2.2). Individuals that self-report as Black or African American, or Asian are less likely to walk or cycle than White; OR=0.60 (0.56, 0.66), OR=0.70 (0.65, 0.75). The proportional increase in all-cause mortality from estimated reductions in physical activity for African American, Asian, and Hispanic populations were 1.0%, 0.7%, 0.8%, respectively. Access to automobiles and the surrounding population density are primary factors in the decision to walk or cycle. After adjusting for these and other factors, members of low-income, low-education, Black or African American, and Asian populations in US metropolitan areas are less likely to walk or cycle than high-income, high-education, or White populations and the discrepancy in physical activity is likely to contribute to health inequity.

Testing the unit root of social, environmental, and governance stock price indexes using a multivariate ARDL model

ABSTRACT The establishment of a green stock market (GSM) has significant implications for the advancement of sustainable development. However, it is susceptible to fluctuations caused by fluctuations in fossil fuel prices, economic policy and geopolitical uncertainties, and monetary policy. This study evaluates the persistence of shocks to five social, environmental, and governance (ESG) stock price indexes using the novel multivariate ARDL unit root test. The Federal Fund Effective Rate (FFER) and West Texas Intermediate Crude Oil Price (WTIOIL) were separately included as covariates in the ARDL model and tested for the null hypothesis of a unit root using a multivariate ARDL unit root test. The results of this study indicate that the ESG stock price indexes exhibit unit root behaviour, suggesting that policy shifts and shocks have a lasting impact on the dynamics of the green stock market and sustainable development.

Estimation of Transition Probabilities from a Large Cohort (> 6000) of Australians Living with Multiple Sclerosis (MS) for Changing Disability Severity Classifications, MS Phenotype, and Disease-Modifying Therapy Classifications.

Multiple sclerosis (MS) is a chronic autoimmune/neurodegenerative disease associated with progressing disability affecting mostly women. We aim to estimate transition probabilities describing MS-related disability progression from no disability to severe disability. Transition probabilities are a vital input for health economics models. In MS, this is particularly relevant for pharmaceutical agency reimbursement decisions for disease-modifying therapies (DMTs). Data were obtained from Australian participants of the MSBase registry. We used a four-state continuous-time Markov model to describe how people with MS transition between disability milestones defined by the Expanded Disability Status Scale (scale 0-10): no disability (EDSS of 0.0), mild (EDSS of 1.0-3.5), moderate (EDSS of 4.0-6.0), and severe (EDSS of 6.5-9.5). Model covariates included sex, DMT usage, MS-phenotype, and disease duration, and analysis of covariate groups were also conducted. All data were recorded by the treating neurologist. A total of N = 6369 participants (mean age 42.5 years, 75.00% female) with 38,837 person-years of follow-up and 54,570 clinical reviews were identified for the study. Annual transition probabilities included: remaining in the no, mild, moderate, and severe states (54.24%, 82.02%, 69.86%, 77.83% respectively) and transitioning from no to mild (42.31%), mild to moderate (11.38%), and moderate to severe (9.41%). Secondary-progressive MS was associated with a 150.9% increase in the hazard of disability progression versus relapsing-remitting MS. People with MS have an approximately 45% probability of transitioning from the no disability state after one year, with people with progressive MS transitioning from this health state at a much higher rate. These transition probabilities will be applied in a publicly available health economics simulation model for Australia and similar populations, intended to support reimbursement of a plethora of existing and upcoming interventions including medications to reduce progression of MS.

Outcomes Among Mexican American and Non-Hispanic White Informal Stroke Caregivers.

Informal home care is prevalent among Mexican American stroke survivors, but data on the impact on caregivers are not available. The aim was to assess ethnic differences in informal stroke caregiving and caregiver outcomes at 90 days poststroke. Informal caregivers were recruited from the population-based Brain Attack Surveillance in Corpus Christi Project (2019-2023), conducted in a bi-ethnic community in Texas. Caregivers of community-dwelling stroke survivors who were not cognitively impaired and not employed by a formal caregiving agency were interviewed. Interviews included sociodemographics, dyad characteristics, Modified Caregiver Strain Index (range 0-26, higher more positive), Positive Aspects of Caregiving scale (range, 5-45, higher more), Patient Health Questionnaire-8 (range, 0-30, higher worse), and PROMIS (Patient-Reported Outcomes Measurement Information System)-10 physical (range, 16.2-67.7, higher better) and mental health (range, 21.2-67.6, higher better) summary scores. Stroke survivor data was from interviews and medical records. Propensity score methods were used to balance caregiver and patient factors among Mexican American and Non-Hispanic White caregivers by fitting a model with ethnicity of caregiver as the outcome and predictors being caregiver sociodemographics, patient-caregiver dyad characteristics, and patient sociodemographics and functional disability. Propensity scores were included as a covariate in regression models, considering the association between ethnicity and outcomes. Mexican American caregivers were younger, more likely female, and more likely a child of the stroke survivor than Non-Hispanic White caregivers. Mexican American caregiver ethnicity was associated with less caregiver strain (β, -1.87 [95% CI, -3.51 to -0.22]) and depressive symptoms (β, -2.02 [95% CI, -3.41 to -0.64]) and more favorable mental health (β, 4.90 [95% CI, 2.49-7.31]) and positive aspects of caregiving (β, 3.29 [95% CI, 1.35-5.23]) but not associated with physical health. Understanding the mechanisms behind more favorable caregiver outcomes in Mexican American people may aid in the design of culturally sensitive interventions to improve both caregiver and stroke survivor outcomes, potentially across all race and ethnic groups.

Influence of age and race on axial elongation in myopic children: A systematic review and meta-regression.

Axial elongation is the basis of progression in primary myopia and the preferred metric to monitor its evolution. We conducted a meta-regression to model axial elongation and its associated factors in children with low to moderate myopia. A comprehensive electronic systematic search was performed using Ovid Medline, EMBASE, and Cochrane Central Register of Controlled Trials of studies conducted up until October 2021. The mean rate of axial elongation was analyzed using a multivariate linear mixed-effects meta-regression model, with backward stepwise elimination of nonsignificant covariates. The model included three levels of random effects, allowing both prediction and confidence intervals to be estimated. A total of 64 studies with 83 subpopulations and 142 evaluations of mean axial change from baseline met our inclusion criteria and had no missing significant covariates in the final model. A separate analysis including all populations with axial length data (202 evaluations) but missing variance or covariate data produced a similar model to that for the analysis with complete data. The mean axial elongation is 38% greater in Asian children (95% confidence interval, 19 to 61%; p<0.01) compared with non-Asians, but both groups show a 15% decline per year as age increases (95% confidence interval, 12 to 17% p<0.0001). Prediction intervals indicate substantial variability around the axial elongation estimates. This analysis provides mean values of axial elongation for evaluation of efficacy of myopia control. The broad prediction intervals emphasize the large range of individual axial elongation rates in the population, illustrating the challenge in managing individual children. Interpretation of the analysis is limited by the use of aggregated data rather than individual subject data.

TXA combined with whole blood transfusion in trauma patients does not increase the risk of VTE but shock index does

IntroductionPrevious studies have demonstrated the benefits of tranexamic acid (TXA) administration in combination with packed red blood cell (PRBC) transfusion in trauma patients without increasing the risk of venous thromboembolism (VTE). However, the effect of TXA in combination with whole blood (WB) has not been studied. Injury, abbreviated injury severity scores (ISS and AIS) and the need for blood transfusions are historically associated with VTE. The objective of this study was to determine the relationship between VTE and the combination of TXA administration and transfusion of PRBCs vs. WB. MethodsOur institutional trauma registry was queried for trauma patients between 2015 and 2022 who received either WB ​+ ​TXA or PRBC ​+ ​TXA either prehospital or within 4 ​h of arrival. Multivariate analysis was utilized to determine independent risk factors for VTE, which were defined as either a deep vein thrombosis (DVT) or a pulmonary embolism (PE). Model covariates included age, mechanism of injury (MOI), ISS, lower extremity AIS, comorbid conditions, and shock index (SI). Additional outcomes analyzed were hospital length of stay (LOS), ICU LOS, and ventilator days. ResultsThree hundred and five patients had complete data and were included in the analysis. Of those, 251 received WB ​+ ​TXA and 54 received PRBC ​+ ​TXA. A total of 34 patients were found to have VTE event (11.1 ​%); 28 (11.2 ​%) and 6 (11.1 ​%) from the WB ​+ ​TXA and PRBC ​+ ​TXA groups, respectively. An elevated pre-hospital SI was independently associated with increased VTE rate (OR 1.85, 95 ​% CI 1.07–3.20). WB transfusion, TXA administration, ISS, and MOI did not influence the rate of VTE. ConclusionThese data demonstrate that the combination of WB ​+ ​TXA administered to trauma patients has no higher risk of VTE than patients who receive PRBC ​+ ​TXA, a comparison that has not been studied clinically to date. Despite the pro thrombotic state enhanced by TXA and the decreased dilutional coagulopathy seen in WB resuscitation, there was no increased risk of VTE compared to TXA ​+ ​PRBC. There is no evidence that TXA combined with whole blood transfusion is associated with an increased risk of VTE. However, higher pre-hospital SI was associated with an elevated rate of VTE. These clinical features provide insight into patients who may be at an increased risk of developing VTE and may benefit from targeted prevention strategies.

Adolescent caffeine use and problematic school behavior: A longitudinal analysis of student survey data and teacher observations.

Caffeine is a psychostimulant possessing arousal, motor activation, and reinforcing properties, which is consumed daily by most adolescents aged 12-19 years. Although current understanding of the implications of adolescent caffeine consumption for school behaviors remains incomplete, studies have shown that in addition to acute effects of the drug, in common with other habit-forming psychoactive substances, regular use leads to physical dependence, evidenced by recurring negative withdrawal symptoms. Employing two waves of longitudinal data, we tested the prospective association between daily caffeine use and homeroom teacher-observed self-control and problem behavior in a sample of middle-school students in 20 schools in West Virginia in the United States. Caffeine was operationalized with two dichotomized variables, daily consumption of <100 mg, and daily consumption of >100 mg, versus no daily use. Gender, mother's education, family financial status, social support by primary caregiver and adults in school, and school climate, were applied as covariates in linear mixed models. Daily caffeine use of >100 mg was robustly and inversely associated with self-control and positively associated with problem behavior. Caffeine consumption and associated withdrawal symptoms may be an important factor in problematic school behavior among adolescents. Recent advent of highly concentrated caffeine products (e.g., caffeine "shots") commonly marketed directly at youth, should give rise to concerns including consideration about limiting caffeine consumption among children and youth.