Analysis Of Longitudinal Data Research Articles

Estimating Obesity Levels Using Decision Trees and K-Fold Cross-Validation: A Study on Eating Habits and Physical Conditions

This study harnesses the predictive capabilities of machine learning to explore the determinants of obesity within populations from Mexico, Peru, and Colombia, using a Decision Tree algorithm bolstered by 5-fold cross-validation. Our comprehensive analysis of 2111 individuals' lifestyle and physical condition data yielded accuracy, precision, recall, and F1-scores that notably peaked in the third and fifth folds. The findings affirmed the significance of dietary habits and physical activity as substantial predictors of obesity levels. The variability in model performance across the folds underscored the importance of robust cross-validation in enhancing the model's generalizability. This research contributes to the burgeoning field of data science in public health by providing a viable model for obesity prediction and laying the groundwork for targeted health interventions. Our study's insights are pivotal for public health officials and policymakers, serving as a stepping stone towards more sophisticated, data-driven approaches to combating obesity. The study, however, recognizes the inherent limitations of self-reported data and the need for broader datasets that encompass more diverse variables. Future research directions include the analysis of longitudinal data to establish causal relationships and the comparison of various machine learning models to optimize predictive performance

Bayesian relative composite quantile regression with ordinal longitudinal data and some case studies

ABSTRACT In real applied fields such as clinical medicine, environmental sciences, psychology as well as economics, we often encounter the task of conducting statistical inference for longitudinal data with ordinal responses. The traditional methods of longitudinal data analysis are often inclined to model continuous responses, which are no longer suitable for such ordinal data. Logistic regression and probit regression are two considerable methods which are frequently used to model ordinal longitudinal responses. However, such modelling methods just depict the mean feature of latent outcome variable and may produce non-robust results when encountering nor-normal errors or outliers. As a proper alternative of mean regression models, composite quantile regression (CQR) method is usually employed to derive robust estimation. The target of this paper is to investigate the CQR estimation approach for ordinal latent longitudinal model. The joint Bayesian hierarchical model is established and a relative CQR estimation approach is suggested to conduct posterior inference for the considered model. Further, in longitudinal data modelling, excessive predictors may be brought into in the models which result in the decrease of the model prediction precision. Bayesian L 1 / 2 regularized prior is incorporated into ordinal longitudinal CQR model to conduct variable selection simultaneously. Finally, simulation studies and two ordinal longitudinal data analysis are hired to illustrate the considered method.

Quantitative analysis of air pollution levels and its health implications in Delhi-NCR: A longitudinal study

Air pollution is a pressing global issue, particularly acute in rapidly urbanizing regions like Delhi-NCR. This research presents a longitudinal study to quantitatively analyze air pollution levels and their health implications in Delhi-NCR. The research objectives include assessing air quality trends, examining the relationships between various pollutants, and investigating the impact of air pollution on respiratory admissions. Data was sourced from the Ambient Air Quality Monitoring Network, covering the years 2020 to 2022, focusing on key pollutants, including PM2.5, PM10, NO2, SO2, CO, and O3. A range of data analysis techniques, including correlation analysis, regression analysis, longitudinal data analysis, spatial analysis, and compliance with WHO guidelines, were applied. Key findings highlight persistently high levels of air pollutants, strong interrelations among pollutants, and consistent respiratory admissions, especially in winter. Regression analysis confirms a significant link between PM2.5 and respiratory admissions. Longitudinal analysis demonstrates the long-term health consequences of air pollution, and spatial analysis reveals district-wise variations in air quality. The study also emphasizes seasonal strategies, compliance with international guidelines, and socioeconomic disparities in health outcomes. This research has broader implications for evidence-based policymaking, emphasizing the urgency of addressing air quality concerns. It calls for targeted interventions, district-level strategies, season-specific measures, and equitable access to healthcare. These findings offer a comprehensive basis for addressing the air quality crisis in Delhi-NCR, ultimately promoting the well-being of its residents.

Joint analysis of multivariate longitudinal, imaging, and time-to-event data

Abstract Alzheimer’s (AD) is a progressive neurodegenerative disease frequently associated with memory deficits and cognitive decline. Despite its irreversible once onset, some discoveries revealed the existence of a certain percentage of people who are non-susceptible to AD. This study proposes a joint analysis of multivariate longitudinal data, survival data with a non-susceptible fraction, and ultrahigh-dimensional imaging data. The proposed model comprises three major components. The first component is a mixture proportional hazards cure model with images to examine the potential predictors of the non-susceptible probability and hazards of interest. The second component is a dynamic factor analysis model with images to characterize group-specific latent factors through multiple observed variables. The last component is a semiparametric trajectory model to reveal the change patterns of the dynamic latent factors in the ‘non-susceptible’ and ‘susceptible’ groups. A two-stage approach is developed for statistical inference. The first stage manages the imaging data through high-dimensional functional principal component analysis. The second stage develops a Bayesian approach coupled with penalized splines, data augmentation, and Markov chain Monte Carlo techniques to perform estimation. The application to the Alzheimer’s Disease Neuroimaging Initiative dataset sheds new insight into the pathology of AD.

Conceptualising the (dis)abling marketplace through value creation and destruction

ABSTRACT Drawing upon value theory, this study investigates both the enabling and disabling features of marketplaces for consumers in the disability market. Analysis of longitudinal qualitative data collected before and after the introduction of a new disability service provision scheme in Australia offer empirical evidence of such marketplaces that are both creating and destroying value for people with disability and their carers. In some instances, value creation and destruction can co-occur for individual consumers. These empirical insights lead to a theoretical conceptualisation of the marketplace as not being wholly disabling, but rather consisting of disabling and enabling factors. Understanding these factors allows service providers and policy makers to make adjustments in view of maximising value creation and minimising value destruction.

Abstract 2556: Longitudinal analyses of clinical sequencing data provide novel insights into the evolutionary dynamics of lung adenocarcinoma

Abstract Background: Tumor heterogeneity plays a crucial role in disease progression, metastasis and treatment response in lung adenocarcinoma (LUAD). Limited availability of multiple molecularly profiled samples from the same patients poses a challenge to validate models of tumor evolution using real-world data. We investigated genomic changes in a large cohort of patients with clinically directed DNA sequencing of multiple LUAD samples. Methods: We analyzed longitudinal genomic data from 524 patients with at least two LUAD samples sequenced with MSK-IMPACT- a targeted panel that identifies somatic mutations, copy number alterations and gene fusions in 341-505 genes. Our analysis of 1084 tumors (634 primaries [P] and 450 metastases [M]) included 189 matched P-P pairs, 99 M-M pairs and 271 P-M pairs. Pairs were required to share an identical somatic mutation to confirm relatedness. Additional criteria included: excision of primary tumor prior to excision of the metastasis in P-M pairs collected over 90 days apart and collection of M-M pairs from the same anatomic site. Intra-pulmonary metastases were removed from P-P pairs. Results: Tumor mutational burden was correlated in paired specimens from the same patient, irrespectively of P-P (R= 0.75, p<0.001; Spearman correlation), P-M (R=0.72, p<0.001) or M-M (R=0.6, p<0.001) status. Chromosomal instability, measured as the fraction of genome altered by copy number changes (FGA), was also correlated in P-P (R=0.69, p<0.001) and M-M (R=0.57, p<0.001) pairs, but tended to increase in metastases with respect to matched primaries (median 0.58 vs. 0.72, p<0.001; Wilcoxon test). In M-M pairs, changes in FGA differed by anatomic site. Liver pairs had the strongest correlation (n=17 pairs, R=0.86, p <0.01), whereas brain pairs had the weakest (n=35 pairs, R=0.085, p=0.71). Most somatic mutations were shared between paired samples (P-P: 639/1055, 60%, P-M: 1563/2877, 54%, M-M: 550/958, 57%), including those in LUAD drivers- TP53, KRAS, and EGFR. Conversely, most oncogenic copy number alterations - including CDKN2A deletions and MET amplifications - were private to one specimen (P-P: 183/276, 66%, P-M: 880/1148, 76%, M-M: 430/601, 71%), most often in the later sample (P-P: 113/183, 61%, P-M: 636/880, 72%, M-M: 212/430, 49%). Clinically targetable alterations (OncoKB Level 1) tended to be shared by tumor pairs from the same patient (93% shared vs. 6% private in P-P, p<0.01; 85% vs. 14% in P-M, p<0.01; 78% vs. 21% in M-M, p <0.01). Conclusions: In LUAD, metastatic specimens exhibit increased chromosomal instability in relation to their matched primaries. This translates into unique copy number alterations detected only in the metastasis. By contrast, driver mutations - which account for most of the clinically targetable alterations with currently approved FDA drugs - are more often shared between paired samples from the same patient. Citation Format: Brooke Mastrogiacomo, Elizabeth G. Dunne, Cameron N. Fick, John Nguyen, Jairam Hathwar, Manendra Lankadasari, Yuan Liu, Soo-Ryum Yang, Jason Chang, Walid K. Chatila, Nikolaus Schultz, David R. Jones, Francisco Sanchez-Vega. Longitudinal analyses of clinical sequencing data provide novel insights into the evolutionary dynamics of lung adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2556.

Advances in the analysis of intensive longitudinal pain data: a commentary on Leroux et al.

Advances in the analysis of intensive longitudinal pain data: a commentary on Leroux et al.

A longitudinal study on the effect of labor values on benign/malicious envy: the mindfulness reperceiving model

This study investigates the relationship between labor values and two forms of envy—benign and malicious—as well as the potential mediating role of mindfulness using a mindfulness reperceiving model. Two thousand three hundred sixty three Chinese teenagers participated in a longitudinal study over an eight-month period, completing questionnaires measuring labor values, benign envy, malicious envy, and mindfulness. The cross-sectional data showed that labor values had an immediate negative effect on malicious envy, with mindfulness partially mediating this relationship. Additionally, labor values had an immediate positive effect on benign envy, but mindfulness did not mediate this relationship. Longitudinal data analysis revealed that the delayed effect of labor values on later benign/malicious envy was similar to its immediate effect. However, mindfulness only played a mediating role in the relationship between labor values and later malicious envy. Cross-gender stability was found in both the immediate effect model and the delayed effect model. Overall, this study sheds light on the influence of labor values on the development of social emotions and the potential mediating role of mindfulness in the Chinese cultural context.

Board gender diversity and bank performance in Jordan

Board diversity is crucial for corporate governance and improves corporate outcomes by aligning management with stakeholders’ interests. Compared to advanced environments, Jordan’s decent sociocultural backdrop exhibits a higher level of gender bias. This study investigates the influence of board gender diversity (BGD) on Jordanian banking sector performance, an under-explored area. This quantitative paper employs Ordinary Least Squares (OLS), random, and fixed-effect approaches to analyze 182 bank-year observations for balanced longitudinal data analysis. These approaches correctly establish the BGD-Tobin’s Q nexus during 2010–2022. The coefficient of determination was 70.57%. The model confirms a positive correlation between BGD and market-based performance indicators. Findings support agency and resource dependency hypotheses, showing BGD’s role in decision-making. Hence, a one-unit increase in BGD causes a 37.2-cent increase in Tobin’s Q measure. Moreover, a one-unit change in board independence, board meetings, size, women’s representation in top management, and capital adequacy ratio, assuming all other factors remain constant, results in Tobin-Q changes of 2.57 cents, 32.8 cents, 5.78 cents, 51.2 cents, 30.55 cents, and 22.86 cents, respectively, and the same direction. The results show how BGD enhances bank performance and contributes to relevant theories. The results are vigorous in a variety of identification and estimation methodologies.

Longitudinal Change in Serum Neurofilament Light Chain in Type 2 Diabetes and Early Diabetic Polyneuropathy: ADDITION-Denmark.

To investigate the longitudinal development of neurofilament light chain (NfL) levels in type 2 diabetes with and without diabetic polyneuropathy (+/-DPN) and to explore the predictive potential of NfL as a biomarker for DPN. We performed retrospective longitudinal case-control analysis of data from 178 participants of the Anglo-Danish-Dutch Study of Intensive Treatment in People with Screen-Detected Diabetes in Primary Care-Denmark (ADDITION-Denmark) cohort of people with screen-detected type 2 diabetes. Biobank samples acquired at the ADDITION-Denmark 5- and 10-year follow-ups were analyzed for serum NfL (s-NfL) using single-molecule array, and the results were compared with established reference material to obtain NfL z-scores. DPN was diagnosed according to Toronto criteria for confirmed DPN at the 10-year follow-up. s-NfL increased over time in +DPN (N = 39) and -DPN participants (N = 139) at levels above normal age-induced s-NfL increase. Longitudinal s-NfL change was greater in +DPN than in -DPN participants (17.4% [95% CI 4.3; 32.2] or 0.31 SD [95% CI 0.03; 0.60] higher s-NfL or NfL z-score increase in +DPN compared with -DPN). s-NfL at the 5-year follow-up was positively associated with nerve conduction studies at the 10-year follow-up (P = 0.02 to <0.001), but not with DPN risk. Areas under the curve (AUCs) for s-NfL were not inferior to AUCs for the Michigan Neuropathy Screening Instrument questionnaire score or vibration detection thresholds. Higher yearly s-NfL increase was associated with higher DPN risk (odds ratio 1.36 [95% CI 1.08; 1.71] per 1 ng/L/year). Our findings suggest that preceding s-NfL trajectories differ slightly between those with and without DPN and imply a possible biomarker value of s-NfL trajectories in DPN.

A matching-based machine learning approach to estimating optimal dynamic treatment regimes with time-to-event outcomes.

Observational data (e.g. electronic health records) has become increasingly important in evidence-based research on dynamic treatment regimes, which tailor treatments over time to patients based on their characteristics and evolving clinical history. It is of great interest for clinicians and statisticians to identify an optimal dynamic treatment regime that can produce the best expected clinical outcome for each individual and thus maximize the treatment benefit over the population. Observational data impose various challenges for using statistical tools to estimate optimal dynamic treatment regimes. Notably, the task becomes more sophisticated when the clinical outcome of primary interest is time-to-event. Here, we propose a matching-based machine learning method to identify the optimal dynamic treatment regime with time-to-event outcomes subject to right-censoring using electronic health record data. In contrast to the established inverse probability weighting-based dynamic treatment regime methods, our proposed approach provides better protection against model misspecification and extreme weights in the context of treatment sequences, effectively addressing a prevalent challenge in the longitudinal analysis of electronic health record data. In simulations, the proposed method demonstrates robust performance across a range of scenarios. In addition, we illustrate the method with an application to estimate optimal dynamic treatment regimes for patients with advanced non-small cell lung cancer using a real-world, nationwide electronic health record database from Flatiron Health.

Measuring access distance and geographic catchment areas for the bus rapid transit interchange from a longitudinal survey

Many developed countries have adopted the 400 m (0.25 mile) and 800 m (0.5 mile) distances, respectively, as planning goals (walking) for bus and rail transit stop catchment areas. Planners, transit agencies and researchers use these transit catchment area criteria to prescribe regulations or formulate policies. Even though these distances may vary depending on the location and study purpose, they are good starting points for developing transit-related policies. However, no standards exist for gauging high-frequency bus or rail interchange geographic catchment areas where many car ‘(‘park-and-ride) users and feeder bus users board the transit. A case study of the bus rapid transit interchange on the Adelaide O-Bahn BRT was used to define the geographic catchment areas. This study surveyed bus rapid transit interchange users over three years (2019, 2020 and 2021) and reported key findings relating to the catchment area and feeder bus proximity issues. Responses highlighted two intriguing findings. First, park-and-ride users and feeder bus users travel significant distances to reach bus rapid transit interchanges when compared with traditional transit stop users who access transit buses and rail on foot, i.e., longitudinal data analysis showed that ‘park-and-'ride’ users travelled as far as 3.7 km to reach the interchange and the feeder bus catchment area ranged from 3.8 to 4.0 km. Second, providing feeder bus route coverage alone cannot increase the patronage levels for connecting the interchange. Although the catchment area extent did not change over these years, the similarity location analysis demonstrated a 30 % difference in the ‘origin-'destination’ pattern change during the pandemic. This research is significant since no previous longitudinal studies have determined the ‘origin-destination’ pattern for accessing a PT interchange.

Impact of bariatric surgery on ovarian reserve markers and its correlation with nutritional parameters and adipokines.

A reduction in anti-müllerian hormone (AMH) levels at short-term after bariatric surgery (BS) has been previously described. However, an assessment of ovarian reserve at longer-follow up, and a comprehensive evaluation of the potentially implicated factors has not been reported. Prospective cohort study. Twenty women aged 18-40 years with BMI 43.95 kg/m2 undergoing BS were studied at baseline (BS0), and at 1 month (BS1), 4 months (BS2), 12 months (BS3), and 24-36 months (BS4) after the surgery. Anthropometrics, reproductive hormones (AMH, FSH, LH, estradiol, testosterone, SHBG, androstenedione), metabolic parameters (adiponectin, leptin, ghrelin, insulin), and nutritional blood parameters (markers of nutritional status, vitamins, and minerals) were obtained at each study time point. Antral follicular count (AFC) was assessed by ultrasonography at BS0, BS3, and BS4. Mixed models were used for analysis of longitudinal data. The mean AMH level was 3.88 ng/mL at BS0, decreased at BS3 (mean= 2.59 ng/mL; p=0.009), and remained stable between BS3 and BS4 (mean= 2.96 ng/mL; p=0.409). We also observed a non-significant decrease in AFC at BS3 (mean=26.14 at BS0, mean 16.81 at BS3; p=0.088) that remained stable at BS4 (mean= 17.86; p=0.731). Mixed models analysis showed: (a) a decrease in 10kg of body weight was associated with an average decrease of 0.357 ng/mL in AMH (p=0.014); (b) a decrease in 1 BMI point was associated with an average decrease of 0.109 ng/mL in AMH (p=0.005); (c) an increase in 1 µg/mL of adiponectin was associated with an average decrease of 0.091 ng/ml in AMH (p=0.041) Significant positive correlations were found between the AMH levels after BS and plasma concentrations of testosterone, free androgen index, insulin and HOMA index. No significant correlations were detected between AMH levels and nutritional parameters. Our results were in line with previous observations, showing that AMH levels decreased significantly at 12 months after bariatric surgery, in parallel with a non-significant reduction in AFC. Both ovarian reserve markers showed a later stabilization up to the end of the study. Of note, postoperative AMH levels were positively correlated with key androgen and insulin resistance-related parameters.

Does household’s food and nutrient acquisition capacity predict linear growth in children? Analysis of longitudinal data from rural and small towns in Ethiopia

Nutritious foods are unaffordable to the majority of households in lower-income countries. Hence, starchy staples tend to be the main source of diets for men, women, and children, implying poor diet quality and deficiency in key nutrients that are crucial for child’s physical growth and cognitive development. Much of existing studies on child linear growth or stunting examined the impact of current dietary consumption on physical growth even though the effect of diets and nutrition would only be observed with time lag. This study examined the associations between sustained consumption of animal sourced foods (ASFs) and adequate nutrient intakes (measured by the mean nutrient adequacy (MPA)) and linear growth differences among children in rural and small towns in Ethiopia. Using nationally representative longitudinal data, results of fixed effects estimations suggested that a standard deviation increase in the household MPA was associated with a 10–11% increase in the height-for-age z-score; and a 10% increase in the household MPA was associated with a 3.2 – 5.6% reduction in stunting rate in children 6–59 months of age. Results also indicated some associations between past ASFs consumption and current linear growth outcomes in younger children. The gap in the household MPA was over 41%, indicating the need for nutrient-dense ASFs in the household diets despite the sustainability concerns around ASFs. Key implication is that policies and interventions aimed at improving linear growth outcomes of children in rural and small towns in Ethiopia should improve household’s access to ASFs and nutrient acquisition capacity.

Associations among symbolic functioning, joint attention, expressive communication, and executive functioning of children in rural areas

The purpose of this study is to investigate the relations among children’s symbolic functioning at 15 months, joint attention at 24 months, expressive communication at 24 and 36 months, and executive functioning at 36 months. With the sample from rural areas in the United States collected by the Family Life Project (N = 1,008), a longitudinal data analysis was conducted. The results of structural equation modeling suggested that children’s symbolic functioning at 15 months and children’s executive functioning at 36 months was directly related to each other. These two variables were also indirectly related to each other through joint attention at 24 months and expressive communication at 24 and 36 months. Psychological distancing and verbal and nonverbal communication were used to explain the role symbolic functioning plays in the development of executive functioning during the second and the third years of children’s lives.

Chondroitin Sulfate for Osteoarthritis – Is There a Risk for Cancer: an Analysis of Osteoarthritis Initiative Data

The aim of this study was to evaluate the association between chondroitin sulfate (CS) use and incidence of self-reported cancer during 6-year follow up in the publicly available Osteoarthritis Initiative (OAI) cohort participants.&#x0D; Materials and Methods: The current study included analysis of 6-year longitudinal data obtained from the OAI progression (n= 1390) and incidence (n = 3284) subcohorts that are publicly available at https://nda.nih.gov/oai/. The inclusion criteria for OAI were the following: age between 45 and 79 years for both subcohorts, symptomatic tibiofemoral knee osteoarthritis (OA) for the progression subcohort, and the presence of established or putative risk factors for incident knee OA for the incidence subcohort. The OAI participants were recruited and enrolled between February 2004 and May 2006 at four recruitment centres in the United States. This study received ethical approval from each recruitment centre. All participants provided written informed consent. To reduce the risk of bias, only participants who did not take CS at baseline were included in the analysis (a “new-user” design).&#x0D; Results: 570 (18%) new users of CS and 2597 (82%) CS non-users were compared. In the CS user group, 294 (51.6%) participants received CS for more than one year, 291 (33.5%) for more than 2 years, 123 (21.6%) for more than 3 years, and 60 (10.5%) for more than 4 years. None of the participants received CS for more than 5 years. CS users and non-users were of the same age, had similar male/female ratio, and similar body mass index. In the non-user group, there were more African-American participants and there were more current smokers. 160 (6.2%) and 37 (6.5%) cases of incident self-reported cancer in the non-users and user groups were identified. There was no association between the use of CS and incident self-reported cancer in the non-adjusted analyses. The adjustments for age, race and smoking status did not change the results.&#x0D; Conclusion: The results of the current study did not show an association between CS use and self-reported cancers. Considering the complex function of CS in the development and progression of malignant tumors, there is a need for further epidemiological studies evaluating CS effects on specific types of cancers and in different genetic backgrounds.

Association Between Psychosocial Acuity and Glycemic Control in a Pediatric Type 1 Diabetes Clinic.

The purpose of this study was to describe the frequency of psychosocial risk and its associations with glycemic levels in youth with type 1 diabetes (T1D) seen by social work staff during regular clinical care. A retrospective longitudinal analysis of observational clinical data was conducted. Individuals (1-26 years) with known T1D who were seen at a pediatric diabetes clinic in a US academic medical center between 2014 and 2021 were included. Variables included psychosocial acuity, A1C, and demographic characteristics. Chi-square tests, Wilcoxon rank sum tests, and mixed linear regressions were used to examine associations between demographic variables, psychosocial acuity, and A1C. Of 966 patients, 513 (53.1%) were male, 76 (7.9%) were non-Hispanic Black, and 804 (83.2%) were non-Hispanic White. There was a mean of 6.9 annual social work encounters per patient, with 3 psychosocial domains measured at each visit. Results showed that as psychosocial acuity level increased, glycemic control decreased. There were significant differences in A1C according to race/ethnicity, insurance, age, and psychosocial acuity. In a real-world clinical population, psychosocial acuity was associated with glycemic control. Presenting for psychosocial issues in their diabetes clinic was associated with reduced glycemic control among youth with T1D. There is an opportunity to connect pediatric patients with appropriate mental health services and psychosocial supports.

Increasing primary care capacity and referral efficiency: A case study of a telehealth centre eConsult service in Brazil.

eConsults are asynchronous digital communications for primary care professionals to seek timely specialist advice. Potential benefits include increased primary healthcare capacity and referral efficiency. Santa Catarina Telehealth Centre in Brazil has offered eConsults for an increasing number of specialties since 2008. This study described the characteristics of this service, including referral efficiency, sustainability, and satisfaction. Retrospective longitudinal analysis of eConsults activity data from 2015 to 2022 with three domains of the Model for Assessment of Telemedicine Applications used to structure the analysis. Characteristics of the application: The total number of eConsults performed in 2015 was 4764, reaching 41,178 in 2022. While 30.3% of eConsults were synchronous in 2015, only asynchronous communication remained from 2021. Clinical effectiveness: eConsults requested to refer patients to specialist care resulting in primary care management remaining above 30% of the total for all specialties from 2019 to 2022, with hematology having the highest percentage (>52%). Organizational aspects: Established workflows with local specialists responding to eConsults (cardiology, endocrinology, hematology and orthopaedics) kept a constant or increasing number of eConsults and maintained the proportion of primary care management from 2019 to 2022, once recovered from COVID-19 and funding restrictions-related reductions. Over 90% of primary care professionals are either satisfied or very satisfied with the eConsult service. Over 8 years, 223,734 consultations were conducted, with high satisfaction, demonstrating the substantial potential for increased primary care-sensitive conditions management. Hiring local specialists, fostering integrated care, and enabling sustainable workflows are key to eConsults' success.

Irregular longitudinal data analysis with statistical and machine learning methods for hazardous asteroids

Observations of the asteroids have been performed as long as it has been feasible by the available observational equipment. Recorded data, going back to 18th century, allowed a classification of these celestial objects’ hazardous status. Unfortunately, previous studies used methods that ignore subject dependency in Near-Earth Asteroids (NEA) data. This study aims to perform hazard classification of asteroids by proposing various statistical and machine learning methods on NEA data to overcome these shortcomings. We analyze data from 751 asteroids observed at irregular time intervals through the NASA. We compare algorithms suitable for longitudinal data structure, such as the Generalized Linear Mixed Models (GLMM), marginal model, GLMM-Tree, Historical Random Forest, GPBoost, and Spline. To the best of our knowledge and based on a comprehensive review of the existing literature, our study stands as the pioneering in the utilization of these advanced methodologies for the in-depth analysis of Near-Earth Asteroid (NEA) data. According to the findings, the accuracies of the models range from 0.89 to 0.99. The GPBoost model has the highest performance, while the marginal model has the poorest one.

Analysis of Tax Risk Management and Control in Port Machinery Manufacturing Industry--Taking Enterprise S as an Example

Port machinery manufacturing has a long history in China and plays an important role in promoting the country's economic progress. Advanced port machinery not only enhances the ability of ports to handle goods, but also effectively cuts down on logistics expenses, thus solidly supporting the country's economic pulse. Against this background, preventing and dealing with the VAT tax risks faced by the port machinery manufacturing industry and improving tax compliance of taxpayers have become key issues. In this paper, a port machinery manufacturing enterprise in the stage of product upgrading and transformation is selected as the research object, and 2020 is taken as the benchmark, focusing on the tax situation of the enterprise in 2021 and 2022. In the case study of this enterprise, this paper adopts a tax-related risk model and longitudinal data analysis within the enterprise to identify in-depth the value-added tax (VAT) and corporate income tax (CIT) risks of the port machinery manufacturing enterprise, as well as the tax-related risks of the enterprise's investment and merger and acquisition business, so as to control the enterprise's tax risks and promote the sustainable development of the enterprise.