Revisiting longitudinal qualitative studies in social work: considerations for design and methodological insights.

This paper undertakes an analysis and discussion of the methodological challenges and insights derived from three longitudinal qualitative studies, all conducted in Chile during the COVID-19 pandemic and subject to comprehensive theoretical-methodological reflection processes centred on their respective designs. This analysis makes a significant contribution to interdisciplinary discussions within social research, with a particular emphasis on longitudinal trajectories. First, we present a comparative analysis of three studies in social work, utilising Saldaña's questions addressing changes and learning in longitudinal studies. The first study explores the labour trajectories of researchers, the second focuses on the educational trajectories of students, and the last examines therapeutic alliance trajectories between social workers and families within the child protection system. Following this, we delve into the methodological decisions made by the research group during the execution of these longitudinal studies. This encompasses an examination of participant involvement, temporal definitions of the adopted designs, and the most suitable methodological tools for analysing change processes over time. The outcomes of this comparative analysis reveal the distinctive characteristics of the three longitudinal studies, providing insights into how the time dimension is explored within them. We highlight key criteria essential for consideration in longitudinal qualitative research, particularly regarding participants and methodology. In conclusion, we advocate for an expanded reflection within the realm of longitudinal qualitative methodology, encompassing aspects such as design choices, approaches to data analysis, integration of technology in information processing, and strategies for maintaining participant engagement.

Quantitative risk assessment for the introduction of bluetongue virus into mainland Europe by long-distance wind dispersal of Culicoides spp.: A case study from Sardinia.

Europe faces regular introductions and reintroductions of bluetongue virus (BTV) serotypes, most recently exemplified by the incursion of serotype 3 in the Netherlands. Although the long-distance wind dispersal of the disease vector, Culicoides spp., is recognized as a virus introduction pathway, it remains understudied in risk assessments. A Quantitative Risk Assessment framework was developed to estimate the risk of BTV-3 incursion into mainland Europe from Sardinia, where the virus has been present since 2018. We used an atmospheric transport model (HYbrid Single-Particle Lagrangian Integrated Trajectory) to infer the probability of airborne dispersion of the insect vector. Epidemiological disease parameters quantified the virus prevalence in vector population in Sardinia and its potential first transmission after introduction in a new area. When assuming a 24h maximal flight duration, the risk of BTV introduction from Sardinia is limited to the Mediterranean Basin, mainly affecting the southwestern area of the Italian Peninsula, Sicily, Malta, and Corsica. The risk extends to the northern and central parts of Italy, Balearic archipelago, and mainland France and Spain, mostly when maximal flight duration is longer than 24h. Additional knowledge on vector flight conditions and Obsoletus complex-specific parameters could improve the robustness of the model. Providing both spatial and temporal insights into BTV introduction risks, our framework is a key tool to guide global surveillance and preparedness against epizootics.

A Novel Two-Step Method for Converting Lumbar Cortical Screw to Pedicle Screw: A Case Report.

The cortical bone trajectory (CBT) technique has emerged as a minimally invasive approach for lumbar fusion but may result in pseudoarthrosis and hardware failure. This report presents a case of successful pedicle screw revision in a patient with previous failed L2 and L3 fusion using a novel "two-step" technique, including (1) drilling a new trajectory with Medtronic EM800N Stealth MIDAS Navigated MR8 drill system (Medtronic, Dublin, Ireland) and (2) placement of Solera 4.75 ATS (awl-tapped screws) with navigated POWEREASE™ (Medtronic), described here for the first time. This method involves utilizing neuronavigation and specialized instruments to safely place pedicle screws through the path of the old cortical screw trajectory, addressing the challenges associated with CBT hardware failure.

Body mass index growth trajectories and body composition influencing factors: An ambidirectional preschooler cohort.

OBJECTIVES: The purpose of the present study was to explore the latent growth trajectory of body mass index (BMI) from birth to 24 months and comprehensively analyze body composition development influencing factor in preschool children. METHODS: This ambidirectional cohort study was conducted in Tianjin, China, from 2017 to 2020, and children's regular medical check-up data from birth to 24 months were retrospectively collected. The growth models were used to fit BMI z-score trajectories for children aged 0-24 months. Crossover analysis and interaction model were used to explore the interaction of influencing factors. RESULTS: We analyzed the growth trajectories of 3217 children, of these, 1493 children with complete follow-up data were included in the influencing factors analysis. Trajectories and parental prepregnancy BMI (ppBMI) were independent factors influencing children's body composition. When paternal ppBMI ≥24 kg/m2, regardless of maternal ppBMI, the risk of overweight and obesity in senior-class children was increased. The high trajectories played a partial mediating role in the association between paternal ppBMI and body composition in preschool children. CONCLUSIONS: BMI growth in children aged 0-24 months can be divided into three latent trajectories: low, middle, and high. These trajectories and parental ppBMI were independent and interactive factors influencing children's body composition. The high trajectories played a partial mediating role in the association between paternal ppBMI and body composition in preschool children. It is necessary to pay attention to the BMI growth level of children aged 0-24 months, which plays an important role in the development of body fat in the future.

A single-cell transcriptomic study of heterogeneity in human embryonic tanycytes.

Disruptions in energy homeostasis can lead to diseases like obesity and diabetes, affecting millions of people each year. Tanycytes, the adult stem cells in the hypothalamus, play crucial roles in assisting hypothalamic neurons in maintaining energy balance. Although tanycytes have been extensively studied in rodents, our understanding of human tanycytes remains limited. In this study, we utilized single-cell transcriptomics data to explore the heterogeneity of human embryonic tanycytes, investigate their gene regulatory networks, analyze their intercellular communication, and examine their developmental trajectory. Our analysis revealed the presence of two clusters of ß tanycytes and three clusters of α tanycytes in our dataset. Surprisingly, human embryonic tanycytes displayed significant similarities to mouse tanycytes in terms of marker gene expression and transcription factor activities. Trajectory analysis indicated that α tanycytes were the first to be generated, giving rise to ß tanycytes in a dorsal-ventral direction along the third ventricle. Furthermore, our CellChat analyses demonstrated that tanycytes generated earlier along the developmental lineages exhibited increased intercellular communication compared to those generated later. In summary, we have thoroughly characterized the heterogeneity of human embryonic tanycytes from various angles. We are confident that our findings will serve as a foundation for future research on human tanycytes.

Trajectories of serum HBsAg during treatment and association with HBsAg loss in children with HBeAg-positive chronic hepatitis B: a latent class trajectory analysis.

BACKGROUND: The change of serum hepatitis B surface antigen (HBsAg) during treatment are associated with HBsAg loss. However, little is known about the trajectory patterns of HBsAg in early treatment and their relationship with subsequent HBsAg loss. This study aimed to identify trajectories of HBsAg in children with HBeAg-positive chronic hepatitis B (CHB) and investigate the association between trajectory patterns and HBsAg loss. METHODS: A retrospective study was conducted on 166 treatment-naive children with HBeAg-positive CHB. Latent class trajectory analysis was used to identify trajectory groups of serum HBsAg. Cox proportional hazard model was used to assess the association between HBsAg trajectory groups and HBsAg loss. RESULTS: The median follow-up time was 20.70 (12.54, 34.17) months, and HBsAg loss occurred in 70(42.17%) of all study participants. Using latent class trajectory analysis, HBeAg-positive CHB patients were classified into three trajectory groups: trajectory 1 (sustained stability, 24.70%), trajectory 2 (slow decline, 38.55%), and trajectory 3 (rapid decline, 36.75%), respectively. The median decline levels of HBsAg at the 3-month and 6-month follow-ups were the highest in trajectory 3 (1.08 and 3.28 log10 IU/ml), followed by trajectory 2 (0.27 and 1.26 log10 IU/ml), and no change in trajectory 1. The risk of achieving HBsAg loss was higher in both trajectory 2 (HR, 3.65 [95% CI, 1.70-7.83]) and trajectory 3 (HR, 7.27 [95% CI, 3.01-17.61]), respectively. CONCLUSION: Serum HBsAg levels during early treatment can be classified into distinct trajectory groups, which may serve as an additional predictive indicator for HBsAg loss in HBeAg-positive CHB children.

Characterizing efficient feature selection for single-cell expression analysis.

Unsupervised feature selection is a critical step for efficient and accurate analysis of single-cell RNA-seq data. Previous benchmarks used two different criteria to compare feature selection methods: (i) proportion of ground-truth marker genes included in the selected features and (ii) accuracy of cell clustering using ground-truth cell types. Here, we systematically compare the performance of 11 feature selection methods for both criteria. We first demonstrate the discordance between these criteria and suggest using the latter. We then compare the distribution of selected genes in their means between feature selection methods. We show that lowly expressed genes exhibit seriously high coefficients of variation and are mostly excluded by high-performance methods. In particular, high-deviation- and high-expression-based methods outperform the widely used in Seurat package in clustering cells and data visualization. We further show they also enable a clear separation of the same cell type from different tissues as well as accurate estimation of cell trajectories.

Joint trajectories of pain, depression and frailty and associations with adverse outcomes among community-dwelling older adults: A longitudinal study.

This study aimed to examine joint trajectories of pain, depression and frailty and their associations with adverse outcomes. Four waves of national data from the China Health and Retirement Longitudinal Study (CHARLS 2011-2018) were used, involving 4217 participants aged ≥60 years. Joint trajectories were fit using parallel-process latent class growth analysis, and their associations with adverse outcomes were evaluated using modified Poisson regression. Four joint trajectories were identified. Compared with most favorable group, other three joint trajectory groups had higher risk of functional disability and hospitalization. Slowly progressive pain, depression and frailty and persistent combination of pain, depression and frailty were also associated with cognitive decline, while slowly reduced pain and depression but persistent frailty was associated with all-cause mortality. The findings highlight unique characteristics and health impacts of concurrent changes in pain, depression and frailty over time, implicating the integrated physical and psychological care for older adults.

Content-Aware Human Mobility Pattern Extraction.

Extracting meaningful patterns of human mobility from accumulating trajectories is essential for understanding human behavior. However, previous works identify human mobility patterns based on the spatial co-occurrence of trajectories, which ignores the effect of activity content, leaving challenges in effectively extracting and understanding patterns. To bridge this gap, this study incorporates the activity content of trajectories to extract human mobility patterns, and proposes acontent-aware mobility pattern model. The model first embeds the activity content in distributed continuous vector space by taking point-of-interest as an agent and then extracts representative and interpretable mobility patterns from human trajectory sets using a derived topic model. To investigate the performance of the proposed model, several evaluation metrics are developed, including pattern coherence, pattern similarity, and manual scoring. A real-world case study is conducted, and its experimental results show that the proposed model improves interpretability and helps to understand mobility patterns. This study provides not only a novel solution and several evaluation metrics for human mobility patterns but also a method reference for fusing content semantics of human activities for trajectory analysis and mining.

Trajectories of craving in the course of pharmacotherapy trials for methamphetamine use disorder.

AIMS: The aim of this study was to measure trajectories of craving for methamphetamine during the course of pharmacotherapy trials for methamphetamine use disorder. DESIGN, SETTING AND PARTICIPANTS: Craving trajectories were identified using Group-Based Trajectory Modeling. The association of craving trajectories with drug use trajectories was examined using a dual trajectory model. Association of craving trajectories with other health and social outcomes was also examined. The study used pooled data from five randomized controlled pharmacotherapy trials for methamphetamine use disorder. A total of 866 adults with methamphetamine use disorder participated in randomized controlled pharmacotherapy trials. MEASUREMENT: Craving was assessed weekly using the Brief Substance Craving Scale. Drug use was assessed using urine toxicology. Alcohol- and drug-related problems, as well as psychiatric, medical, legal, employment and relationship problems, were measured using the Addiction Severity Index. FINDINGS: A three-trajectory model with high, medium and low craving trajectories was selected as the most parsimonious model. Craving trajectories were associated with methamphetamine use trajectories in the course of trial; 88.4% of those in the high craving trajectory group had a consistently high frequency of methamphetamine use compared with 18.7% of those in the low craving group. High craving was also associated with less improvement in most other outcomes and higher rate of dropout from treatment. In turn, low craving was associated with a rapidly decreasing frequency of methamphetamine use, greater improvement in most other outcomes and a lower rate of dropout. Participants on modafinil daily and ondansetron 1 mg twice daily were less likely to be in the high craving group compared with those on placebo. CONCLUSIONS: Trajectories of methamphetamine craving in the course of clinical trials for methamphetamine use disorder appear to be both highly variable and strongly associated with greater frequency of drug use, other drug-related outcomes and dropout from trials. Two medications, modafinil daily and ondansetron at a dose of 1 mg two times daily, appear to be associated with greater reduction in craving in the course of treatment compared with placebo. A decrease in methamphetamine craving shows promise as an early indicator of recovery from methamphetamine use disorder.

Automating Video-Based Two-Dimensional Motion Analysis in Sport? Implications for Gait Event Detection, Pose Estimation, and Performance Parameter Analysis.

BACKGROUND: Two-dimensional (2D) video is a common tool used during sports training and competition to analyze movement. In these videos, biomechanists determine key events, annotate joint centers, and calculate spatial, temporal, and kinematic parameters to provide performance reports to coaches and athletes. Automatic tools relying on computer vision and artificial intelligence methods hold promise to reduce the need for time-consuming manual methods. OBJECTIVE: This study systematically analyzed the steps required to automate the video analysis workflow by investigating the applicability of a threshold-based event detection algorithm developed for 3D marker trajectories to 2D video data at four sampling rates; the agreement of 2D keypoints estimated by an off-the-shelf pose estimation model compared with gold-standard 3D marker trajectories projected to camera's field of view; and the influence of an offset in event detection on contact time and the sagittal knee joint angle at the key critical events of touch down and foot flat. METHODS: Repeated measures limits of agreement were used to compare parameters determined by markerless and marker-based motion capture. RESULTS: Results highlighted that a minimum video sampling rate of 100 Hz is required to detect key events, and the limited applicability of 3D marker trajectory-based event detection algorithms when using 2D video. Although detected keypoints showed good agreement with the gold-standard, misidentification of key events-such as touch down by 20 ms resulted in knee compression angle differences of up to 20°. CONCLUSION: These findings emphasize the need for de novo accurate key event detection algorithms to automate 2D video analysis pipelines.

The longitudinal growth trajectory of children with congenital hypothyroidism during the first 3 years of life.

Congenital hypothyroidism (CH) is detected through a newborn screening program in Iran, enabling early detection and prompt treatment. This study addresses the longitudinal growth trajectory of Iranian children with CH and explores associated factors during the first 3 years of life. Data from 1474 children with CH in Isfahan, Iran (2002-2022), were analyzed. Weight, height, and head circumference were measured, and z-scores for age were calculated. Group-based trajectory modeling was applied to distinct growth trajectories. Factors influencing growth patterns, including gender, treatment initiation age, delivery method, parental consanguinity, history of familial hypothyroidism, and thyroid-stimulating hormone (TSH) levels at 3-7 days, were investigated. Thirty-seven percent of children diagnosed with CH faced a delay in weight, while 36.6% experienced stunted height, and 25.7% showed a retardation in head circumference growth. The initiation of treatment, parental consanguinity, and family history of hypothyroidism varied among these groups. Children exhibiting an optimal growth pattern in the initial 3 years of life demonstrated lower average TSH levels. CONCLUSION: This research emphasizes the complexity of managing CH and stresses the importance of tailoring interventions based on individualized characteristics and the ongoing growth patterns of the children. Future research is required to understand the intricate relationships between growth patterns and various determinants and optimize the growth and developmental outcomes of children with CH. WHAT IS KNOWN: • Iran has a higher prevalence of congenital hypothyroidism (CH) with a nationwide screening program. • There are concerns about delayed growth in CH children, but limited research on long-term patterns and contributing factors. WHAT IS NEW: • Distinct patterns in weight, height, and head circumference among children with CH were identified. • Factors such as consanguinity, parental hypothyroidism, and TSH levels impact growth outcomes. • CH management is complicated, and there is a need for individualized interventions.

Trajectory Patterns of Weight and Length in Children: From Birth Until 2-Years of Age.

OBJECTIVE: The aim was to identify trajectory patterns of weight and length in children from birth until two years of life and establish associations with maternal and child characteristics. METHODS: A mixed-cohort study was conducted in public health services in Colombo-PR, Brazil, between 2018 and 2022. Pregnancy information was gathered through anthropometric data collection and questionnaires. Birth data were extracted from birth record forms, while weight and length data in the first two years of life were obtained from physical and electronic health service records. Weight and length trajectory patterns were identified using a group-based trajectory model. The definition of the number of trajectory patterns to be selected considered the model fit to the type of variable, its practical utility, as well as the probabilities of group membership. RESULTS: Two trajectory patterns of weight and length were identified among the children. The majority exhibited a pattern of weight (67.8%, n = 382) and length (90.9%, n = 472) considered high and stable, with a tendency to decelerate from one and a half years of age. The probability of belonging to the lower weight gain group was associated with female sex (41.5%, p < 0.001), smoking during pregnancy (48.7%, p = 0.008), prematurity (65.0%, p = 0.001), cesarean delivery (36.4%, p = 0.009), small for gestational age (69.0%, p < 0.001), and twinning (69.2%, p = 0.002). Similarly, the probability of belonging to the lower length gain group was associated with female sex (11.7%, p < 0.001), smoking during pregnancy (20.6%, p = 0.003), cesarean delivery (10.1%, p = 0.048), born small for gestational age (46.4%, p < 0.001), and twinning (46.1%, p < 0.001). CONCLUSION: Conditions during pregnancy and childbirth can impact growth patterns in the first two years of life.

Comprehensive source identification of heavy metals in atmospheric particulate matter in a megacity: A case study of Hangzhou.

Megacities face significant pollution challenges, particularly the elevated levels of heavy metals (HMs) in particulate matter (PM). Despite the advent of interdisciplinary and advanced methods for HM source analysis, integrating and applying these approaches to identify HM sources in PM remains a hurdle. This study employs a year-long daily sampling dataset for PM1 and PM1-10 to examine the patterns of HM concentrations under hazy, clean, and rainy conditions in Hangzhou City, aiming to pinpoint the primary sources of HMs in PM. Contrary to other HMs that remained within acceptable limits, the annual average concentrations of Cd and Ni were found to be 20.6 ± 13.6 and 46.9 ± 34.8 ng/m³, respectively, surpassing the World Health Organization's limits by 4.1 and 1.9 times. Remarkably, Cd levels decreased on hazy days, whereas Ni levels were observed to rise on rainy days. Using principal component analysis (PCA), enrichment factor (EF), and backward trajectory analysis, Fe, Mn, Cu, and Zn were determined to be primarily derived from traffic emissions, and there was an interaction between remote migration and local emissions in haze weather. Isotope analysis reveals that Pb concentrations in the Hangzhou region were primarily influenced by emissions from unleaded gasoline, coal combustion, and municipal solid waste incineration, with additional impact from long-range transport; it also highlights nuanced differences between PM1 and PM1-10. Pb isotope and PCA analyses indicate that Ni primarily stemmed from waste incineration emissions. This explanation accounts for the observed higher Ni concentrations on rainy days. Backward trajectory cluster analysis revealed that southern airflows were the primary source of high Cd concentrations on clean days in Hangzhou City. This study employs a multifaceted approach and cross-validation to successfully delineate the sources of HMs in Hangzhou's PM. It offers a methodology for the precise and reliable analysis of complex HM sources in megacity PM.

Prediction Model for Chronological Weight Loss After Bariatric Surgery in Korean Patients.

Purpose: This study aimed to develop a predictive model for monitoring chronological weight loss during the early postoperative period following bariatric surgery in Korean patients with morbid obesity. Materials and Methods: The baseline characteristics and postoperative weight loss outcomes were collected for up to 24 months after surgery in patients who underwent sleeve gastrectomy (SG) or Roux-en-Y gastric bypass (RYGB). The factors influencing weight loss outcomes were analyzed, and longitudinal percentile charts were plotted using quantile regression models adjusted for the identified independent factors. Results: The analysis included 491 and 274 patients who underwent SG and RYGB, respectively, of whom 225 (29.4%) were men. A positive association was found between the maximum percentage of total weight loss (%TWL) and female sex, body mass index (BMI) ≥40, and age <40 years. Among patients who reached nadir BMI or had at least 12 months of follow-up data (n=304), 7.6% exhibited inadequate weight loss (TWL <20%). The predictors of insufficient weight loss were older age (>40 years), male sex, and psychological problems. Centile charts were generated for the entire cohort, incorporating age, sex, and the type of procedure as covariates. Conclusion: The percentile charts proposed in the present study can assist surgeons and healthcare providers in gauging patients' progress toward their weight loss goals and determining the timing of adjunctive intervention in poor responders during early postoperative follow-up.

Trajectory of medical expenditure and regional disparities in hypertensive patients in South Korea.

The aim of this study is to understand how different regions influence the management and financial burden of hypertension, and to identify regional disparities in hypertension management and medical expenditure. The study utilized data from the Korean Health Panel Survey conducted between 2014 and 2018, focusing on individuals with hypertension. Medical expenditures were classified into three trajectory groups: "Persistent Low," "Expenditure Increasing," and "Persistent High" over a five-year period using trajectory analysis. Inverse Probability Weighting (IPW) analysis was then employed to identify the association between regions and medical expenditure trajectories. The results indicate that individuals residing in metropolitan cities (Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan) and rural areas were more likely to belong to the "Expenditure Increasing" group compared to the "Persistent Low Expenditure" group (OR = 1.07; 95% CI; p < 0.001), as opposed to those in the capital city (Seoul) (OR = 1.07; 95% CI; p < 0.001). Additionally, residents of rural areas were more likely to be in the "High Expenditure" group compared to the "Persistent Low Expenditure" group than those residing in the capital city (OR = 1.05; 95% CI; p = 0.001). These findings suggest that individuals in rural areas may be receiving relatively inadequate management for hypertension, leading to higher medical expenditures compared to those in the capital region. These disparities signify health inequality and highlight the need for policy efforts to address regional imbalances in social structures and healthcare resource distribution to ensure equitable chronic disease management across different regions.

scMaSigPro: Differential Expression Analysis along Single-Cell Trajectories.

MOTIVATION: Understanding the dynamics of gene expression across different cellular states is crucial for discerning the mechanisms underneath cellular differentiation. Genes that exhibit variation in mean expression as a function of Pseudotime and between branching trajectories are expected to govern cell fate decisions. We introduce scMaSigPro, a method for the identification of differential gene expression patterns along Pseudotime and branching paths simultaneously. RESULTS: We assessed the performance of scMaSigPro using synthetic and public datasets. Our evaluation shows that scMaSigPro outperforms existing methods in controlling the False Positive Rate and is computationally efficient. AVAILABILITY AND IMPLEMENTATION: scMaSigPro is available as a free R package (version 4.0 or higher) under the GPL(≥2) license on GitHub at 'github.com/BioBam/scMaSigPro' and archived with version 0.03 on Zenodo at 'zenodo.org/records/12568922'.

Association of bioimpedance analysis parameters trajectories with clinical outcomes in neurocritical patients.

Background and objective: Neurocritical patients often experience uncontrolled high catabolic metabolism state during the acuta phase of the disease. The complex interactions of neuroendocrine, inflammation, and immune system lead to massive protein breakdown and changes in body composition. Bioelectrical impedance analysis (BIA) evaluates the content and proportions of body components based on the principles of bioelectricity. Its parameters reflect the overall health status of the body and the integrity of cellular structure and function, playing an important role in assessing the disease status and predicting prognosis of such patients. This study explored the association of BIA parameters trajectories with clinical outcomes in neurocritical patients. Methods: This study prospectively collected BIA parameters of 127 neurocritical patients in the Department of Neurology admitted to the NICU for the first 1-7 days. All these patients were adults (≥18 years old) experiencing their first onset of illness and were in the acute phase of the disease. The group-based trajectory modeling (GBTM), which aims to identify individuals following similar developmental trajectories, was used to identify potential subgroups of individuals based on BIA parameters. The short-term prognosis of patients in each trajectory group with variations in phase angle (PA) and extracellular water/total body water (ECW/TBW) over time was differentially analyzed, and the logistic regression model was used to analyze the relationship between potential trajectory groups of PA and ECW/TBW and the short-term prognosis of neurocritical patients. The outcome was Glasgow Outcome Scale (GOS) score at discharge. Results: Four PA trajectories and four ECW/TBW trajectories were detected respectively in neurocritical patients. Among them, compared with the other latent subgroups, the "Low PA rapidly decreasing subgroup" and the "High ECW/TBW slowly rising subgroup" had higher incidences of adverse outcomes at discharge (GOS:1-3), in-hospital mortality, and length of neurology intensive care unit stay (all P < 0.05). After correcting for potential confounders, compared with the "Low PA rapidly decreasing subgroup", the risk of adverse outcome (GOS:1-3) was lower in the other three PA trajectories, with OR values of 0.0003, 0.0004, and 0.003 respectively (all P < 0.05). Compared with the "High ECW/TBW slowly rising subgroup", the risk of adverse outcome (GOS:1-3) was lower in the other three ECW/TBW trajectories, with OR values of 0.013, 0.035 and 0.038 respectively (all P < 0.05). Conclusion: Latent PA trajectories and latent ECW/TBW trajectories during 1-7 days after admission were associated with the clinical outcomes of neurocritical patients. The risk of adverse outcomes was highest in the "Low PA rapidly decreasing subgroup" and the "High ECW/TBW slowly rising subgroup". These results reflected the overall health status and nutritional condition of neurocritical patients at the onset of the disease, and demonstrated the dynamic change process in body composition caused by the inflammatory response during the acute phase of the disease. This provided a reference basis for the observation and prognostic evaluation of such patients.

Driving risk identification of urban arterial and collector roads based on multi-scale data.

Urban arterial and collector roads, while interconnected within the urban transportation network, serve distinct purposes, leading to different driving risk profiles. Investigating these differences using advanced methods is of paramount significance. This study aims to achieve this by primarily collecting and processing relevant vehicle trajectory data alongside driver-vehicle-road-environment data. A comprehensive risk assessment matrix is constructed to assess driving risks, incorporating multiple conflict and traffic flow indicators with statistically temporal stability. The Entropy weight-TOPSIS method and the K-means algorithm are employed to determine the risk scores and levels of the target arterial and collector roads. Using risk levels as the outcome variables and multi-scale features as the explanatory variables, random parameters models with heterogeneity in means and variances are developed to identify the determinants of driving risks at different levels. Likelihood ratio tests and comparisons of out-of-sample and within-sample prediction are conducted. Results reveal significant statistical differences in the risk profiles between arterial and collector roads. The marginal effects of significant parameters are then calculated separately for arterial and collector roads, indicating that several factors have different impacts on the probability of risk levels for arterial and collector roads, such as the number of movable elements in road landscape pictures, the standard deviation of the vehicle's lateral acceleration, the average standard deviation of speed for all vehicles on the road segment, and the number of one-way lanes on the road segment. Some practical implications are provided based on the findings. Future research can be implemented by expanding the collected data to different regions and cities over longer periods.