Hierarchical Model Research Articles

The harmful side of absent leaders: Multifactor leadership and employees’ job-stress-related presenteeism

Abstract This study tests the role of the full range leadership model’s leadership styles in employees’ job-stress-related presenteeism (JSRP). Further, the study tests a model that introduces mediating variables in the relationship between absent leaders and JSRP. Employees from four different types of organizations: police (N = 148), public service (N = 479, not-for-profit (N = 96), and construction (N = 214) completed the Multifactor Leadership Questionnaire on their direct supervisor, as well as a self-report measures of JSRP, psychological distress, and work–life balance. Correlations and hierarchical linear regression models showed that laissez-faire leadership had the strongest influence on JSRP for all four organizations. The parallel mediation model results showed that both employee psychological distress and work–life balance partially mediated the relationship between laissez-faire leadership style and employees’ JSRP. These results underscore the importance of looking at absent leaders and how they affect employees negatively.

Abstract Su702: Association Between In-hospital Cardiac Arrest Incidence and Survival in Older Patients

Background: Survival after an in-hospital cardiac arrest (IHCA) varies markedly across hospitals in the U.S. Whether hospitals with IHCA survival also excel in ‘preventing’ IHCA remains unclear. Methods: Using 2013-2019 data from the Get-With-The-Guidelines–Resuscitation (GWTG-R) registry linked with Medicare and American Hospital Association data, we identified all patients > 65 years with IHCA at participating hospitals. Using two-level hierarchical multivariable regression models, we calculated hospital rates of IHCA incidence, adjusted for case-mix index, and risk-standardized survival to discharge (RSSR) for IHCA, adjusted for patient and cardiac arrest variables. We also examined the association of IHCA incidence and RSSR with hospital variables. Results: Among >10 million admissions at 335 hospitals during 2013-2019, 77676 patients experienced an IHCA. The median hospital rate of IHCA incidence was 6.9 per 1000 admissions, and the median case-survival rate among those with IHCA was 21.9%. After case-mix adjustment, the median IHCA incidence was 7.9 per 1000 admissions with considerable variation across hospitals: IQR: 5.8-10.3 per 1000 admissions, range 1.2 to 25.4 per 1000 admissions. The median RSSR for IHCA was 22.3%, which varied from 11.5% to 35.7% across hospitals (IQR: 19.5%-24.9%). There was a weak negative correlation between risk-adjusted hospital IHCA incidence and its RSSR (rho = -0.11; p = 0.037) (Figure 1). Adjustment for hospital variables attenuated the negative association between IHCA incidence and RSSR (rho = -0.08; p = 0.13). The nurse-patient ratio was the only modifiable factor significantly associated with lower IHCA incidence (OR = 0.97; p = 0.004) and higher RSSR (OR = 1.05; p <.0001). Conclusion: Even after case-mix adjustment, hospital IHCA incidence and survival rates varied markedly. Notably, hospitals with higher survival rates for IHCA did not have a higher incidence. Since case-survival rates for IHCA have plateaued in recent years, our findings highlight that efforts focused on reducing IHCA incidence may yield additional gains in reducing resuscitation deaths in hospitals.

The Impact of Digital Transformation on Service Models and Employee Skill Requirements in Taiwan's Real Estate Brokerage Industry

This paper investigates how digital transformation impacts service delivery models and employee skill requirements in Taiwan's real estate brokerage industry. Through a multiple-case comparison approach, data was collected from 200 participants across real estate firms to examine organizational adaptation to technological change. The research employed structural equation modeling and hierarchical linear modeling to analyze relationships between compensation satisfaction (β = 0.45, p < 0.001), digital competency levels, and internal case circulation patterns. Results demonstrate that digital technologies significantly reshape brokerage operations, with digitalized companies achieving 32% higher client acquisition rates and 45% reduction in transaction processing time. Analysis reveals that employee digital literacy accounts for 28% of performance variance, while organizational support systems explain 23% of technology adoption rates. The findings extend service innovation literature by establishing empirical links between compensation systems and digital transformation success, providing a practical framework for technology integration in Taiwan's real estate sector. This research offers evidence-based recommendations for firms implementing digitalization strategies and developing employee capabilities in response to industry evolution.

Abstract 4129075: Racial and Ethnic Differences in Semaglutide Prescriptions in the Veterans Affairs Healthcare System

Introduction: Recent advances in obesity treatment added incretin-based injectables like semaglutide to treatments ranging from lifestyle modification to bariatric surgery. While the burden of obesity in the United States is high and disproportionately affects minoritized individuals, obesity interventions may not be equitably distributed. Insurance coverage is often cited as a barrier to accessing novel treatments. Research Question: Do inequities in semaglutide use among patients with obesity persist without insurance barriers to care? Goals: Characterize the role of race and ethnicity in the receipt of semaglutide among Veterans with obesity. Methods: Among VA patients with BMI ≥27 from 2018-2023, we used a hierarchical multivariable mixed effects logistic regression model to evaluate the association between race and ethnicity (White, Non-Hispanic Black, Hispanic, Asian/Native Hawaiian/Pacific Islander, American Indian/Alaska Native) and receipt of semaglutide prescriptions. We adjusted for age, gender, diabetes status, Charlson Comorbidity Index, education, and urbanicity, with a random effect for diagnosis year. Results: Among Veterans with BMI ≥27 (n=2,423,070), 38.8% had Class I obesity (BMI 30-34.9), 18.2% had Class II obesity (BMI 35-39.9), and 9.8% had Class III obesity (BMI>40), with differences by race and ethnicity (p<0.01). Across the cohort, 184,690 (7.6%) received at least one prescription for semaglutide during the study period. Higher severity of obesity was associated with odds of semaglutide prescription (Figure). Compared to White Non-Hispanic patients, Black and Hispanic/Latino Veterans were less likely to receive a semaglutide prescription, with adjusted odds ratios (AOR) of 0.63 (95% confidence interval [CI]): 0.60-0.68) and 0.81 (95% CI: 0.74-0.90), respectively. Receipt of a semaglutide prescription was also highly associated with diabetes status, with an AOR of 35.2 (95% CI 32.5-38.0) for those with a diagnosis of diabetes compared to those without. Conclusions: Racial and ethnic minority Veterans with obesity are less likely to receive prescriptions for semaglutide in VA, suggesting that challenges to equitable obesity care are more complex than financial coverage alone.

Abstract 4128698: Mental Health and Sleep Quality as Determinants of Physical Activity Levels in Depressed Rural Patients with Coronary Heart Disease

Background: Disparities in coronary heart disease (CHD) and other chronic related conditions, such as poor sleep quality and psychological distress, have been observed in rural areas. Both conditions can negatively affect disease progression, possibly through their impact on physical activity. The relationships, however, among sleep quality, psychological distress, and physical activity among depressed rural CHD patients have not been examined. Purpose: The purpose of this study was to determine the association of sleep quality (i.e., sleep fragmentation [frequent sleep interruption] and nocturnal/sleep movement [increased rates of movement, ‘tossing and turning’ during sleep]) and psychological distress (i.e., anxiety and perceived stress) with levels of physical activity (i.e., sedentary, light, and moderate to vigorous) in depressed rural patients with CHD. Methods: A total of 142 depressed rural CHD patients (aged 57.0±11.9 years, 97% White) completed surveys on demographic characteristics, anxiety (Brief Symptom Inventory), and stress (Perceived Stress Scale-4). Participants also wore accelerometer activity monitors for seven days (ActiGraph GT9X Link) to capture physical activity levels and sleep quality. Three different hierarchical regression models were conducted to predict each level of physical activity (sedentary, light, and moderate-vigorous) with predictor variables entered in blocks. Block 1 included demographic variables (i.e., age, sex, marital status, employment status). Block 2 included sleep quality measures, and Block 3 included psychological distress. Results: Participants spent 466±126.0 min/day while awake being sedentary, 483±119.9 min/day in light activity, and 90±65.9 min/day in moderate to vigorous activity. We found that stress was significantly associated with greater sedentary time (B = 6.56, p = .043) and less time in light activity (B = -7.99, p = .024). Nocturnal/sleep movement was significantly associated with increased sedentary time (B = 3.14, p < .001) and decreased time in light (B = -5.29, p =.002) and moderate-vigorous activity (B = -2.58, p = .003). Anxiety was not associated with physical activity. Conclusions: Poor sleep quality and greater perceived stress are associated with a more sedentary lifestyle, a major risk factor for CHD. Addressing both stress and sleep management may play a role in reducing CHD risks associated with inactivity among depressed rural patients with CHD.

Implementation of ward's agglomerative hierarchical clustering model to detect pulmonary tuberculosis endemic areas in Aceh Utara regency

This study aims to detect pulmonary Tuberculosis (TB) endemic areas in Aceh Utara Regency based on altitude, population density, and the number of TB cases. The Agglomerative Hierarchical Clustering (AHC) algorithm was used to cluster 27 subdistricts, each measured by these three factors. The clustering results divided the subdistricts into three main clusters with distinct characteristics. Cluster 1 consists of subdistricts with low altitude, high population density, and relatively high numbers of TB cases, identifying this area as having the highest risk of TB endemicity. Cluster 2 includes areas with moderate population density and TB case numbers, while Cluster 3 consists of subdistricts at higher altitudes with fewer TB cases. The clustering results were evaluated using three key metrics: Silhouette Score, Davies-Bouldin Index, and Dunn Index, which indicated that the clustering model performed well, although some subdistricts were positioned near the cluster boundaries. This research provides valuable information for health authorities to prioritize interventions and allocate resources to areas most in need of TB management.

Using Multilevel Models and Generalized Estimating Equation Models to Account for Clustering in Neurology Clinical Research.

In clinical and health services research, clustered data (also known as data with a multilevel or hierarchical structure) are frequently encountered. For example, patients may be clustered or nested within hospitals. Understanding when data have a multilevel structure is important because clustering of individuals can induce a homogeneity in outcomes within clusters, so that, even after adjusting for measured covariates, outcomes for 2 individuals in the same cluster are more likely to be similar than outcomes for 2 individuals from different clusters. Using conventional statistical regression models to analyze clustered data can result in incorrect conclusions being drawn. In particular, estimated CIs may be artificially narrow, and significance levels may be artificially low. As a result, one may conclude that there is a statistically significant association when there is none. To avoid this problem, investigators should ensure that their analyses use techniques that account for clustering of data. Generalized linear models estimated using generalized estimating equation (GEE) methods and multilevel regression models (also known as hierarchical regression models, mixed-effects models, or random-effects models) are two such techniques. We provide an introduction to clustered or multilevel data and describe how GEE models or multilevel models can be used for the analysis of multilevel data.

Abstract 4137165: Changes in Contrast Volume among Patients Undergoing Percutaneous Coronary Intervention: a Report from NCDR CathPCI registry

Background: Acute kidney injury (AKI) is the most common complication after percutaneous coronary intervention (PCI) and can be mitigated by using less iodinated contrast. The National Cardiovascular Data Registry (NCDR) supports quality improvement initiatives by providing quarterly, risk-adjusted, institutional AKI rates. However, it remains uncertain whether these efforts have reduced procedural contrast volume, particularly in high-risk patients. Aims: Examine temporal trends in contrast volume during PCI across different pre-procedural AKI risk strata. Methods: Within the NCDR CathPCI Registry, we identified PCIs performed between April 1, 2018, and December 31, 2022, and examined changes in mean contrast volume over time across different pre-procedural AKI risk strata defined by the validated NCDR AKI risk model. A multivariable hierarchical model, with the physician as a random effect, was constructed to assess the trend in contrast volume use over time. Results: Among 3,126,559 patients undergoing PCI (mean age = 66.8 ± 11.7 years, 69.4% men, and 39.9% elective procedures), contrast volume declined from a mean of 168.1±77.6 ml in Q2 2018 to 149.8±71.2 ml in Q4 2022 ( p < 0.001 for trend) with the trend being consistent across AKI risk strata ( Figure ). After adjusting for patient and pre-procedural characteristics, the contrast volume declined by 18.9 ml (95%CI 19.1 to 18.6, P <0.001) between 2018 and 2022. Despite marked physician variability in mean contrast use, the lowest mean contrast doses were observed in patients at greatest AKI risk (>15%). Conclusions: PCI contrast administration has declined over time, and the average exposure was lowest in patients at highest risk for AKI, suggesting improved efforts to reduce AKI over time.

Abstract Su704: Body Mass Index and Outcomes of In-Hospital Cardiac Arrest

Background: Although previous studies have reported an association between a patient’s body mass index (BMI) and outcomes for various cardiovascular conditions, the relationship between BMI and survival for in-hospital cardiac arrest (IHCA), a condition for which emergent response is required, has not been fully described. Aims: Examine the association between BMI and survival outcomes for IHCA. Methods: Within the Get With The Guidelines®-Resuscitation, we identified 56,411 patients with IHCA and available BMI data during 2005-2012 when weight and height data were collected in the registry. BMI was classified as underweight [<18.5 kg/m 2 ], normal [18.5 to 24.9 kg/m 2 ], overweight [25.0 to 29.9 kg/m 2 ], obese [30.0 to 34.9 kg/m 2 ], and very obese [≥35.0 kg/m 2 ]). Using multivariable hierarchical models with hospital as a random effect, we examined the association between BMI and survival to discharge, stratified by cardiac arrest rhythm type (shockable and non-shockable). As secondary outcomes, we examined rates of sustained return of spontaneous circulation for > 20 minutes (ROSC) and favorable neurological survival (i.e., survival to discharge without severe neurological disability). Results: Among 10,219 patients with a shockable arrest rhythm, 3,964 (38.7%) survived to discharge. After multivariable adjustment, compared with overweight patients, those who were underweight, of normal weight, and very obese had lower survival rates, whereas obese patients had similar survival rates ( Table ). Underweight patients also had a lower rate of ROSC and favorable neurologic survival ( Table ). Among 46,192 patients with a non-shockable arrest rhythm, 7,331 (15.8%) survived to discharge. After multivariable adjustment, all BMI groups had similar rates of survival, ROSC, and favorable neurologic survival, except for underweight patients ( Table ). Conclusions: Although the association between BMI and survival outcomes for IHCA varied by initial rhythm, underweight patients consistently had lower survival rates of survival. Very obese patients generally had similar outcomes to other weight groups, underscoring that morbid obesity was not a negative predictor of survival outcomes for IHCA.

Abstract 4124005: Sex, ethnic and social determinants of health differences in high-potency P2Y12 inhibitors prescription among patients with acute coronary syndrome: An analysis of the American Heart Association Get With The Guidelines®–Coronary Artery Disease Registry

Background: Sex and racial differences in the outcomes of patients with acute coronary syndrome (ACS) persist and could be related to the differences in management including high-potency P2Y12 inhibitors. Aim: This study aims to examine the contribution of social determinants of health on the association between sex and racial differences in the prescription of high-potency P2Y12 inhibitor upon discharge. Methods: Patients with ACS undergoing percutaneous coronary intervention (PCI) from the American Heart Association Get With The Guidelines®–Coronary Artery Disease Registry between October 2019 to December 2022 were included. Multivariable hierarchical models were used to assess whether there are differences in high-potency P2Y12 inhibitors (i.e., ticagrelor or prasugrel) prescription at discharge adjusting for race/ethnicity, insurance, age, social vulnerability index (SVI), zip code designation, and medical history. Analyses were performed in women and men separately. Results: Among 135,153 patients with ACS who underwent PCI, 59.8% were discharged on a high-potency P2Y12 inhibitor. Compared with men, women were less likely prescribed high-potency P2Y12 inhibitor (66.9% vs 72%), and this pattern did not change during the study period (P=0.50) (Figure). There was a significant interaction between sex and race for high-potency P2Y12 inhibitor prescription (P< 0.05). Among women, the likelihood of high-potency P2Y12 inhibitors prescription was not significantly different across different race/ethnicities. However, in men, non-Hispanic Blacks and Hispanics had lower odds of high-potency P2Y12 inhibitors prescription compared with non-Hispanic Whites among men after adjusting for all covariates. Conclusions: In this large contemporary observational analysis of patients with AMI undergoing PCI, women were less likely prescribed a high-potency P2Y12 inhibitor upon discharge. Among women, the likelihood of high-potency P2Y12 inhibitors prescription was not significantly different across different race/ethnicities; however, in men, non-Hispanic Blacks and Hispanics had lower odds of high-potency P2Y12 inhibitors prescription. Further efforts should be directed to minimize these sex and racial disparities.

Overview of hepatocarcinogenesis focusing on cellular origins of liver cancer stem cells: a narrative review.

Hepatocellular carcinoma (HCC) accounts for 85% to 90% of primary liver cancers and generally has a poor prognosis. The hierarchical model, which posits that HCC originates from liver cancer stem cells (CSCs), is now widely accepted, as it is for other cancer types. As CSCs typically reside in the G0 phase of the cell cycle, they are resistant to conventional chemotherapy. Therefore, to effectively treat HCC, developing therapeutic strategies that target liver CSCs is essential. Clinically, HCCs exhibit a broad spectrum of pathological and clinical characteristics, ranging from well-differentiated to poorly differentiated forms, and from slow-growing tumors to aggressive ones with significant metastatic potential. Some patients with HCC also show features of cholangiocarcinoma. This HCC heterogeneity may arise from the diverse cellular origins of liver CSCs. This review explores the normal physiology of liver regeneration and provides a comprehensive overview of hepatocarcinogenesis, including cancer initiation, isolation of liver CSCs, molecular signaling pathways, and microRNAs. Additionally, the cellular origins of liver CSCs are reviewed, emphasizing hematopoietic and mesenchymal stem cells, along with the well-known hepatocytes and hepatic progenitor cells.

A Hierarchical Bayesian Model for Estimating Age-Specific COVID-19 Infection Fatality Rates in Developing Countries.

The COVID-19 infection fatality rate (IFR) is the proportion of individuals infected with SARS-CoV-2 who subsequently die. As COVID-19 disproportionately affects older individuals, age-specific IFR estimates are imperative to facilitate comparisons of the impact of COVID-19 between locations and prioritize distribution of scarce resources. However, there lacks a coherent method to synthesize available data to create estimates of IFR and seroprevalence that vary continuously with age and adequately reflect uncertainties inherent in the underlying data. In this article, we introduce a novel Bayesian hierarchical model to estimate IFR as a continuous function of age that acknowledges heterogeneity in population age structure across locations and accounts for uncertainty in the estimates due to seroprevalence sampling variability and the imperfect serology test assays. Our approach simultaneously models test assay characteristics, serology, and death data, where the serology and death data are often available only for binned age groups. Information is shared across locations through hierarchical modeling to improve estimation of the parameters with limited data. Modeling data from 26 developing country locations during the first year of the COVID-19 pandemic, we found seroprevalence did not change dramatically with age, and the IFR at age 60 was above the high-income country estimate for most locations.

Health Promotion Activity in the Community -- Scoping Reviewed

Health promotion is a multidisciplinary field that aims to improve the health and well-being of people not only by treating diseases, but also by promoting healthy lifestyles, preventing diseases, and addressing social, economic, and environmental factors that affect health. However, the meaning may vary according to the perspective of different actors and professionals. Scoping review, using the Medical Literature Analysis and Retrieval System Online – US National Library of Medicine’s, for the articles that were published between January 1, 2018 and September 1, 2023, following the analysis procedures: title, summary reading, and total readership. The most mentioned activity in the 24 articles is health promotion associated with prevention in the community, with the home being the most referenced context. Based on Joanna Briggs’ Hierarchy of Evidence model, Institute, Redenç ao, indicates 5 levels of studies, namely: experimental studies, quasi-experimental studies, observational analytical studies, observational descriptive studies, and expert opinion. Therefore, the scope consisted of 24 articles from States United States, Brazil, Australia, South Asia, South Africa, Indonesia, Thailand, Newfoundland, Iran, Japan, South Africa, Nigeria, Tanzania, and Norway. The activity carried out by nursing at home focuses on individualized care and disease monitoring. Keywords: nursing, community health nursing, health promotion, primary prevention

Data Reconciliation-Based Hierarchical Fusion of Machine Learning Models

In the context of hierarchical system modeling, ensuring constraints between different hierarchy levels are met, so, for instance, ensuring the aggregation constraints are satisfied, is essential. However, modelling and forecasting each element of the hierarchy independently introduce errors. To mitigate this balance error, it is recommended to employ an optimal data reconciliation technique with an emphasis on measurement and modeling errors. In this study, three different machine learning methods for development were investigated. The first method involves no data reconciliation, relying solely on machine learning models built independently at each hierarchical level. The second approach incorporates measurement errors by adjusting the measured data to satisfy each constraint, and the machine learning model is developed based on this dataset. The third method is based on directly fine-tuning the machine learning predictions based on the prediction errors of each model. The three methods were compared using three case studies with different complexities, namely mineral composition estimation with 9 elements, forecasting of retail sales with 14 elements, and waste deposition forecasting with more than 3000 elements. From the results of this study, the conclusion can be drawn that the third method performs the best, and reliable machine learning models can be developed.

Minimally Processed Foods Have a Higher Total Antioxidant Content Compared to Processed and Ultra-processed Foods: Results from an Analysis of 1,946 Food Items.

Ultra-processed foods (UPF), per the NOVA Classification, provide a major source of calories within modern food systems and are associated with poor health outcomes related to chronic inflammation. Dietary antioxidants play a key role in preventing disease, however, the relationship between the NOVA Classification and the total antioxidant content (TAC) of foods is not well-characterized. We hypothesized that TAC would be highest in Minimally Processed (MPF), lower in Processed (PRF), and lowest in UPF. TAC data for 3,137 animal-based, mixed, and plant-based food items were obtained from a published data set. After data cleaning, 1,946 food items and their TAC values were analyzed using two hierarchal linear models (alpha: p<0.05). MPF had the highest mean TAC (10.79 ± 0.87 mmol/100g) and were 11.31-fold and 10.72-fold higher than PRF and UPF, respectively (p=0.023). Plant-based and Mixed foods had a higher mean TAC (8.55 ± 0.68 and 1.12 ± 0.11 mmol/100g, respectively) and were 22.67-fold and 2.98-fold higher compared to animal-based foods (p<0.001). Food processing did not change mean TAC in Mixed and Animal-based foods; however, plant-based MPF had a higher mean TAC (11.49 ± 0.93 mmol/100g) and were 9.88-fold and 15.12-fold higher compared to plant-based PRF and UPF, respectively (p<0.001). Mean TAC differed between NOVA processing groups for three categories of food: Vegetables, Beverages, and Beans, Nuts & Seeds (p<0.001). Across all food items, and especially plant-based foods, mean TAC decreased with food processing. The lower TAC of UPFs may at least partially explain why their consumption promotes inflammatory chronic disease.

Analytical study of the merging rate of low-mass intermediate-mass black holes in preparation for the future Einstein Telescope

The detection of gravitational wave (GW) signals by Advanced LIGO, Virgo, and KAGRA interferometers opened a new chapter in our understanding of the formation of compact objects. In particular, the detection of GW190521 is observational confirmation of the existence of intermediate-mass black holes (IMBHs); yet more direct observations are needed to better understand the mechanisms behind their formation. In this study, we explore the potential of the next-generation ground-based detector, the Einstein Telescope (ET), to advance our understanding of astrophysics through the detection of GWs emitted by IMBHs. To achieve this, the ET is designed to have improved sensitivity in the low-frequency range of approximately 2-10 Hz, enabling the detection of GWs originating from binary systems containing IMBHs with masses in the range of approximately 10$^2$-10$^5$ $M_ odot We consider black holes (BHs) in the pair-instability form via the hierarchical merger model in galaxies, and approximate the number of events that could be observed by the ET. Our findings indicate that ET could detect a binary black hole (BBH) merger rate of around $2 yr^ $ for BH masses ranging from 10 to 200 M$ odot $, with around 100 $Gpc^ yr^ $ of this rate specifically attributed to BHs in the 100–200 M$ odot $ mass range, which we classify as low-mass IMBHs in this study. This suggests that ET could detect several dozen events similar to GW190521. The exact locations of these BBH mergers are not specified and we count our BH mergers across the entire universe up to a redshift of $z$ approx 2. Observations made with the ET are expected to significantly enhance our comprehension of galactic BH growth, and the existence and characteristics of low-mass IMBHs.

Unraveling demographic patterns in tropical birds across an elevational gradient

Abstract An increasing body of evidence has displayed upslope shifts in the high-diversity avian communities of tropical mountains. Such shifts have largely been attributed to warming climates, although their actual mechanisms remain poorly understood. One likely possibility is that changes in species-specific demographic rates underlie elevational range shifts. Fine-scale population monitoring and capture–mark–recapture (CMR) analysis could shed light on these mechanisms but, until recently, analytical constraints have limited our ability to model multiple demographic rates across bird communities while accounting for transient individuals. Here, we used Bayesian hierarchical multi-species CMR models to estimate the apparent survival, recruitment, and realized population growth rates of 17 bird species along an elevational gradient in the cloud forests of Honduras. For 6 species, we also modeled demographic rates across elevation and time. Although demographic rates varied among species, population growth rates tended to be higher in lower elevation species. Moreover, some species showed higher population growth rates at higher elevations, and elevational differences in growth rates were positively associated with previous estimates of upslope shifts at the study site. We also found that demographic rates showed contrasting trends across the duration of the study, with recruitment decreasing and apparent survival increasing, and stronger effects at lower elevations. Collectively, we provide the methodological tools to encourage more multi-species demographic analyses in other systems, while highlighting the potential for the demographic impacts of global change. We provide a Spanish translation in the Supplementary Materials.

Efficacy of Small Group Reading Intervention for Grade 2 and 3 Children With Reading Difficulties: A Cluster Randomized Controlled Trial.

We examined whether Phonics + Set for Variability (SfV) reading intervention would lead to better irregular word reading compared to Phonics + Morphology within a cluster randomized control trial (RCT) design with a follow-up measurement. The participants were 273 Grade 2 and 3 students with reading difficulties (139 in the Phonics + SfV and 134 in the Phonics + Morphology) who received intervention in small groups (2-4 children), 4 times a week, 30 minutes each time, for 15 weeks. Results of hierarchical linear modeling showed that there was a significant effect of intervention on all reading outcomes (e.g., from pre- to posttest the effect sizes for Phonics + SfV ranged from g = 0.74 to 1.54 and for Phonics + Morphology from g = 0.75 to 1.49). Unexpectedly, there were no differences between the intervention conditions in any of the outcome variables, including irregular word reading and morphological awareness that the interventions partly focused on.

Factors associated with the use of regional anesthesia for calcaneal osteotomy in pediatric patients: A single-center, retrospective cohort study.

Despite known disparities in pediatric perioperative outcomes, few studies have examined factors associated with the use of regional anesthesia for pediatric orthopedic surgery. This investigation aimed to determine if minority and developmental disability status were associated with the allocation of peripheral nerve blocks in calcaneal osteotomy. We conducted a single-center, retrospective study of records of patients <18 years who underwent calcaneal osteotomy from 2013 to 2022. Regional technique was classified into three groups: popliteal-sciatic single-shot block, popliteal-sciatic catheter, and no block. Patients were classified as either nonminority (white, non-Hispanic) or minority. Developmental disability status was defined based on medical history and classified as binary. Anesthesiologists were classified as "regional" or "nonregional" based on clinical expertise. A Bayesian hierarchical multinomial model with random intercepts for patients and surgeons was used to investigate the association of minority status, developmental disability, and anesthesiologist expertise with block selection. We analyzed 287 cases in 225 patients; of these, 55% occurred in minority patients and 28% occurred in patients with developmental disability. Catheters were placed in 45% of cases, single shot blocks in 41%, and no block in 14%. Minority and nonminority patients had a similar likelihood of receiving of any block. Patients with developmental disability had a -22% absolute difference of receiving any block (95% credible interval [-38%, -7%]) compared to those without developmental disability (55% vs. 77%), an effect primarily driven by a lower rate of catheter placement in these children. Regional anesthesiologists were more likely to place catheters (23% absolute increase; 36% vs. 13%) and more likely to perform any block in children with developmental disability (30% absolute increase; 67% vs. 37%) than nonregional anesthesiologists. Decision-making surrounding the placement of regional anesthesia techniques is complex. In this study, developmental disability status and anesthesiologist experience were associated with a difference in the use of regional anesthesia in patients undergoing calcaneal osteotomy.

Diagnostic Accuracy of Optic Nerve Sheath Diameter Measurement by Ultrasonography for Noninvasive Estimation of Intracranial Hypertension in Traumatic Brain Injury: A Systematic Review and Meta-Analysis.

Intracranial hypertension (IH) is associated with an unfavorable outcome in traumatic brain injury (TBI), and management strategies guided by intracranial pressure monitoring improve prognosis. Owing to the limitations of using invasive devices, measurement of optic nerve sheath diameter (ONSD) by ultrasonography is an alternative noninvasive method. However, its accuracy has not been validated in patients with TBI, so we aim to determine the diagnostic accuracy of measuring ONSD by ultrasonography in patients with TBI to estimate IH, compared with invasive monitoring. Systematic review of electronic databases and manual literature review from inception to June 2023. The analysis included diagnostic accuracy studies of ultrasonographic measurement of ONSD compared with invasive monitoring published in any language and with patients of any age. A qualitative synthesis was performed describing the clinical and methodological characteristics, strengths, limitations, and quality of evidence. In addition, a bivariate random effects model meta-analysis and a hierarchical summary receiver operating characteristics model were performed for the pediatric and adult population separately. Five hundred and forty eight patients of 688 in 16 eligible studies were adults and 120 were children. Pooled sensitivity and specificity of ONSD measurement by ultrasonography were 84% (95% CI, 76%-89%) and 83% (95% CI, 73%-90%), respectively. During the sensitivity analysis, these parameters exhibited consistent values. Pooled area under the curve was 0.91 for adults and 0.76 for children. Optimal threshold for estimating IH was 5.76 mm for adults and 5.78 mm for children. Measurement of ONSD by ultrasonography is a reliable, low-cost, and safe alternative for the estimation of IH with TBI in adults. More robust studies are needed to overcome the high risk of bias and heterogeneity for this analysis.