Likelihood Ratio Test Research Articles

Poor access to breastfeeding counseling services and associated factors among lactating mothers who had optimal antenatal care follow-up in Sub-saharan Africa: a multilevel analysis of the recent Demographic and Health Survey

BackgroundInadequate access to services for breastfeeding counseling results in poor breastfeeding practices and adverse health consequences. Although poor access to breastfeeding counseling services is a major challenge, its magnitude and determinantes are not well studied in developing countries. Therefore, this study assessed the magnitude and determinants of poor access to breastfeeding counseling services among lactating mothers who had optimal antenatal care follow-up in Sub-Saharan Africa.MethodsData from the recent Demographic and Health Surveys, involving a total of 289,929 women, were used for analysis. The determinants of poor access to breastfeeding counseling services were examined using a multilevel mixed-effects logistic regression model. Significant factors associated with poor access to breastfeeding counseling services were declared significant at p-values < 0.05. The adjusted odds ratio and confidence interval were used to interpret the results. A model with the lowest deviance and highest log likelihood ratio was selected as the best-fit model.ResultsIn Sub-Saharan Africa, nearly one in two women with optimal antenatal care follow-up had poor access to breastfeeding counseling services. Maternal age (AOR = 1.18, 95% CI: 1.02, 1.38), maternal education (AOR = 1.128, 95% CI: 1.22, 1.35), distance to health facility (AOR = 1.17, 95% CI: 1.13, 1.21), media exposure (AOR = 1.12, 95% CI: 1.08, 1.17), wealth index (AOR = 1.05, 95% CI: 1.00, 1.10), place of delivery (AOR = 4.31, 95% CI: 4.11, 4.52), PNC (AOR = 3.92, 95% CI: 3.78, 4.07), mode of delivery (AOR = 1.88, 95% CI: 1.76, 2.02), birth interval (AOR = 1.12, 95% CI: 1.07, 1.17), residence (AOR = 1.14, 95% CI: 1.09, 1.18), community poverty (AOR = 1.09, 95% CI: 1.03, 1.15), community institutional delivery (AOR = 1.06, 95% CI: 1.01, 1.12), country category (AOR = 2.23, 95% CI: 2.10, 2.37), had higher odds of poor access to breastfeeding counseling services.ConclusionsPoor access to breastfeeding counseling services among lactating mothers was found to be high. Both individual and community-level factors were determinants of poor access to breastfeeding counseling services. The Ministry of Health in Sub-Saharan Africa should give attention to those women who have not had a postnatal check-up and give birth at home while designing policies and strategies.

Spatial variation and associated factors of home delivery among reproductive age group women in Ethiopia, evidence from Performance Monitoring for Action Ethiopia Survey 2019, spatial and multilevel logistic regression analysis

IntroductionHome birth is described as a delivery that takes place at home without the presence of a skilled birth attendant. In 2017, nearly 295,000 mothers died from various pregnancy and childbirth-related problems, accounting for approximately 810 maternal deaths per day. Therefore, this study aims to investigate the spatial distributions of home birth and associated factors in Ethiopia using the Performance Monitoring for Action Survey (PMAS) 2019) to get information that helps to take geographic-based interventions and can assist health planners and policymakers in developing particular measures to reduce home deliveries.MethodIn PMA-ET 2019, a community-based cross-sectional study was conducted in collaboration with Addis Ababa University, Johns Hopkins University, and the Federal Ministry of Health from September 2019 to December 2019, in Ethiopia. A multi-stage cluster sampling procedure was employed to draw from the stratified 2019 PMAS sample. A weighted total of 5,796 women were included in this study. ArcGIS version 10.7 software was used to visualize the spatial analysis. In addition, STATA version 14 of the statistical software was used for multilevel analysis The Bernoulli model was applied using Kulldorff's SaTScan version 9.6 software to identify significant purely spatial clusters for home delivery in Ethiopia. Intra-class Correlation Coefficient (ICC), Likelihood Ratio (LR) test, Median Odds Ratio (MOR), and deviance (−2LLR) values were used for model comparison and fitness. Adjusted Odds Ratios (AOR) with a 95% Confidence Interval (CI) and p-value &amp;lt;0.05 in the multilevel logistic model were used to declare significant factors associated with home delivery.ResultThe spatial distribution of home delivery was non-random in Ethiopia. Statistically significant high hotspots of home delivery were found in Somali, Afar, Sidama, most of South Nation Nationality and People Region (SNNP), most parts of Amhara, south west Ethiopia, and Oromia region. In the multilevel logistic regression model; Women from the lowest wealth quintile were 1.68 times [AOR = 1.68; 95% CI: 1.31, 2.15] higher odds of giving birth at home as compared to their counterparts. Regarding maternal educational status, mothers who had no education, primary education, and secondary education had 9.91 times [AOR = 9.91, 95% CI: 5.44, 18.04], 6.62 times [AOR = 6.62, 95% CI: 3.65, 12.00] and 2.99 times [AOR = 2.99, 95% CI: 1.59, 5.63] higher odds of giving birth at home compared to mothers who attained higher education, respectively. In addition, community-level factors were significantly associated with home delivery, women who had high community-level poverty were 1.76 times [AOR = 1.76; 95% CI: 1.14, 2.72] higher odds of home delivery compared to women who had low community-level poverty.ConclusionHome delivery was statistically found to be a significantly high hot spot in Somalia, Afar, Sidama, most of the South Nation Nationality and People area (SNNP), most of Amhara, southwest Ethiopia, and the Oromia region of Ethiopia. Significant factors associated with home delivery in Ethiopia were women with lower levels of education, poor wealth, living in rural areas, high levels of community poverty, divorced or separated widowed marital status, and older maternal ages. Therefore, health institutions, health professionals, National and regional policymakers health planners community leaders and all concerned should give priority to the identified hot spot clusters to design an effective intervention program to reduce home delivery.

Jackknife empirical likelihood ratio test for testing the equality of semivariance

Jackknife empirical likelihood ratio test for testing the equality of semivariance

Cross entropy and log likelihood ratio cost as performance measures for multi-conclusion categorical outcomes scales.

The inconclusive category in forensics reporting is the appropriate response in many cases, but it poses challenges in estimating an "error rate". We discuss the use of a class of information-theoretic measures related to cross entropy as an alternative set of metrics that allows for performance evaluation of results presented using multi-category reporting scales. This paper shows how this class of performance metrics, and in particular the log likelihood ratio cost, which is already in use with likelihood ratio forensic reporting methods and in machine learning communities, can be readily adapted for use with the widely used multiple category conclusions scales. Bayesian credible intervals on these metrics can be estimated using numerical methods. The application of these metrics to published test results is shown. It is demonstrated, using these test results, that reducing the number of categories used in a proficiency test from five or six to three increases the cross entropy, indicating that the higher number of categories was justified, as it they increased the level of agreement with ground truth.

Radiographic biomarkers on grayscale gradient transition zone improve differentiation of deep caries/reversible pulpitis and chronic pulpitis through diagnostic model analysis.

To explore the effectiveness of radiographic biomarkers on transition area (TA)-the grayscale gradient zone from carious lesion to normal dentine on radiographs-for identifying deep caries/reversible pulpitis and chronic pulpitis via diagnostic model analysis. This retrospective study included 392 caries cases. Canny edge detection was used to define the TA region. Texture parameters were extracted from the carious lesions (S1) and TA region (S2) by MaZda software on radiographs. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to select biomarkers. Diagnostic models were fitted and model performance was furtherly evaluated by internal and external validation, decision curve analysis was applied to evaluate clinical benefits. TA-based biomarkers (e.g., TA thickness, TA ratio, S2-S(5,-5) contrast and S2-WavEnLL-s-4) were significantly associated with the diagnosis of deep caries/reversible pulpitis versus chronic pulpitis, model performance significantly improved when adding the above biomarkers (likelihood-ratio test; p < 0.05, with an increase of AUC from 0.67 (reference model) to 0.89), and these results were maintained in a small external validation cohort. Clinical benefit was greater with the application of TA-based biomarkers. TA-based biomarkers are proven to be an effective tool in differentiating deep caries/reversible pulpitis and chronic pulpitis, preoperative diagnosis was improved with the above biomarkers compared to the reference model.

The size of myocardial infarction and peri-infarction edema are not major determinants of diastolic impairment after acute myocardial infarction.

To study the relationship between myocardial infarction size (IS), myocardial edema, and diastolic dysfunction after acute myocardial infarction (MI) both in the acute phase, and in the development of diastolic dysfunction in the follow-up setting. A further purpose is to study diastolic function using a mechanistic model as well as conventional parameters. Patients underwent cardiovascular magnetic resonance (CMR) imaging and echocardiography including mechanistic analysis using the parameterized diastolic filling method within 4-7days (acute) and 6months after a first acute anterior MI (n = 74). Linear regression modeling of echocardiographic diastolic parameters using CMR IS with and without inclusion of the myocardium at risk (MAR) and model comparisons with likelihood ratio tests were performed. Diastolic parameters at 6months follow-up were modelled using final IS. For most parameters there was no association with acute IS, except for deceleration time (R2 = 0.24, p < 0.001), left atrial volume index (R2 = 0.13, p = 0.01) and the mechanistic stiffness parameter (R2 = 0.21, p < 0.001). Adding MAR improved only the e' model (adjusted R2 increase: 0.08, p = 0.02). At 6months follow-up, final IS was only associated with viscoelastic energy loss (R2 = 0.22, p = 0.001). In acute MI, both IS and MAR are related to diastolic function but only to a limited extent. At 6months after infarction, increasing IS is related to less viscoelastic energy loss, albeit also to a limited extent. The relationship between IS and diastolic dysfunction seems to be mediated by mechanisms beyond simply the spatial extent of ischemia or infarction.

Articulatory precision from connected speech as a marker of cognitive decline in Alzheimer's disease risk-enriched cohorts.

Mild cognitive impairment (MCI) has been recognized as a possible precursor to Alzheimer's disease (AD). Recent research focusing on connected speech has uncovered various features strongly correlated with MCI due to AD and related dementias. Despite these advancements, the impact of early cognitive decline on articulatory precision has not been thoroughly investigated. This study introduced the phoneme log-likelihood ratio (PLLR) to assess the articulatory precision of speakers across different cognitive status levels and compared its effectiveness to existing well-studied acoustic features. The study utilized speech recordings from a picture description task, which included data from 324 cognitively unimpaired participants with low amyloid-β burden (CU, Aβ()), 47 cognitively unimpaired participants with high amyloid-β burden (CU, Aβ()), 69 participants with MCI, and 20 participants with dementia. Nine acoustic features were extracted from the speech recordings, covering three categories: speech fluency, speech pace, and articulatory precision. Welch's -test and Hedge's were adopted to assess their discriminative ability. A reduction in speech fluency and pace was observed among participants in the MCI and dementia groups. The PLLR shows large effect sizes in distinguishing between cognitively unimpaired participants with low Aβ burden and those diagnosed with MCI or dementia. Additionally, the test-retest reliability experiment indicated moderate repeatability of the features under study. The study reveals PLLR as a sensitive indicator capable of detecting subtle articulatory variations across groups, while also providing further support for the association between reduced articulatory precision and early cognitive decline.

Using red–green–blue vegetation indices to evaluate complex agronomical traits in soybean breeding

AbstractHigh‐throughput phenotyping is an emerging tool that allows access to identify simple and complex traits, accelerating genetic discoveries and selection. Vegetation indices strongly correlate with several economic crop traits, allowing plant breeders to detect variation in breeding populations. Thus, this study used red–green–blue (RGB) vegetation indices to evaluate the influence of the stink bug complex (Euschistus heros, Piezodorus guildinii, Nezara viridula, Dichelops melacanthus, and Edessa meditabunda) on the agronomical traits of soybean (Glycine max) lineages. For instance, two experiments were conducted to assess soybean resistance to the stink bug complex, (1) with and (2) without pesticide control. An unmanned aerial vehicle coupled with an RGB camera acquired aerial photography over the field during the R5 stage. Four vegetation indices and canopy were estimated from the orthomosaic, and the genotypes were evaluated based on agronomical traits. Linear mixed models were used to estimate the variance and significance test of each trait using the likelihood ratio test, and the principal component analysis was performed to verify the multivariate pattern among genotypes. The results showed significant genotypic effects for most traits with high broad‐sense heritability for agronomical traits and moderate for vegetation indices. Significant correlations using best linear unbiased predictions were observed among the agronomical traits with the vegetation indices and canopy coverage, which can be used as a tool for the indirect selection of soybean lineages in the breeding pipeline.

A Likelihood Ratio Test for Hybridization Under the Multispecies Coalescent

Several methods have been developed to carry out a statistical test for hybridization at the species level, including the ABBA-BABA test and HyDe. Here, we propose a new method for detecting hybridization and quantifying the extent of hybridization. Our test computes the likelihood of a species tree that is possibly subject to hybridization using site pattern frequencies from genomic-scale datasets under the multispecies coalescent. To do this, we extend the calculation of the likelihood for site pattern frequency data for the 4-taxon symmetric and asymmetric species trees proposed in Chifman and Kubatko (2015) by incorporating an inheritance parameter, resulting in efficient computation of the likelihood under a scenario of hybridization. We use this likelihood computation to construct a likelihood ratio test that a given species is a hybrid of two parental species. Simulations demonstrate that our test is more powerful than existing tests of hybridization, including HyDe, and that it achieves the desired type I error rate. We apply the method to two empirical data sets, one for which hybridization is believed to have occurred and one for which previous methods have failed to detect hybridization.

Development and Validation of the RSClinN+ Tool to Predict Prognosis and Chemotherapy Benefit for Hormone Receptor–Positive, Node-Positive Breast Cancer

PURPOSE Clinicopathological factors and the 21-gene Oncotype DX Breast Recurrence Score (RS) test both influence prognosis. Our goal was to develop a new tool, RSClinN+, to individualize recurrence risk and chemotherapy benefit predictions by menopausal status for patients with HR+/human epidermal growth factor receptor 2–negative, lymph node–positive breast cancer by integrating the RS result with clinicopathological factors (grade, tumor size, age). METHODS We used patient-level data from 5,283 patients treated with chemoendocrine therapy (CET) versus endocrine therapy alone (ET) in the S1007 (N = 4,916) and S8814 (N = 367) trials to develop the tool. Cox proportional hazards regression models stratified by trial were used to estimate 5-year invasive disease-free survival for pre- and postmenopausal woman, respectively. The integrated RSClinN+ model was compared with RS alone and clinicopathological models using likelihood ratio tests. Absolute CET benefit was estimated as the difference between ET and CET risk estimates. Validation of RSClinN+ was performed in 592 patients with node-positive disease in the Clalit Health Services registry. RESULTS RSClinN+ provides better prognostic information than RS model alone (premenopausal P = .034; postmenopausal P &lt; .001) or clinicopathological model alone (premenopausal P = .002; postmenopausal, P &lt; .001). In postmenopausal women, RS showed interaction with CET benefit ( P = .016), with RSClinN+ absolute CET benefit ranging from &lt;0.1% to 21.5% over RS ranges 0-50. In premenopausal patients with RS ≤25, there was no significant interaction between RS and CET benefit. In external validation, RSClinN+ risk estimates were prognostic (hazard ratio, 1.75 [95% CI, 1.38 to 2.20]) and concordant with observed risk (Lin's concordance, 0.92). CONCLUSION RSClinN+ provides improved estimates of prognosis and absolute CET benefit for individual patients compared with RS or with clinical data alone and could be used in patient counseling.

Impact of speed on injury severity in single-vehicle run-off-road crashes: Insights from partially temporal constrained modeling approach

Single-vehicle run-off-road crashes accounts for approximately 35% of all the traffic fatalities in the U.S during the period of 2019–2021. This paper explores the association between driving speed and injury severity outcomes of single-vehicle run-off-road crashes. The single-vehicle run-off-road crash data from 2019 to 2021 on Interstate freeways in Florida are utilized, and categorized into periods of pre-, during-, and post-COVID-19 pandemic. The partially constrained temporal and temporal unconstrained random parameters logit models are developed considering three injury severity outcomes: no injury, minor injury and serious injury/fatality. Multiple variables in terms of driver, vehicle, roadway, environmental, crash, and temporal attributes are observed to significantly affect the injury severity. Moreover, temporal instability and transferability issues are validated through likelihood ratio test and out-of-sample prediction. In the partially constrained models, numerous variables such as indicators of new vehicle, male driver, and restraint-protected driving consistently yield identical parameter values across all periods, whereas various variables clearly illustrate the distinct differences across the three periods and three speed intervals. The marginal effects in the unconstrained models also display the obvious differences across three periods and three speed intervals. Moreover, the findings corroborate the increased risk outcomes linked to larger speed differences and the COVID-19 pandemic period. These results provide better understanding of the risk mechanisms underlying run-off-road crashes and furnish valuable direction for the formulation of effective safety interventions.

Estimation of five parameter bivariate modified Weibull singular distribution

Recently, El-Bassiouny et al. (El-Bassiouny, Shahen, and Abouhawwash 2018) proposed the flexible Marshall-Olkin type bivariate modified Weibull distribution (BMWD) and obtained the maximum likelihood estimates (MLEs) of the five unknown parameters of the BMWD by solving five non-linear equations. The MLEs of parameters cannot be obtained in closed form. In this paper, we discuss about the computation of the MLEs using the efficient EM algorithm, which reduces the problem to a two-dimensional (2-D) optimization problem. The proposed EM algorithm performs better than the standard existing optimization algorithms, e.g. optim and nlm. The bivariate goodness-of-fit (GoF) test is discussed based on statistically equivalence blocks (SEBs). Some nonstandard likelihood ratio (LR) tests are considered for testing the relative GoF to the BMWD. An extensive simulation study is carried out. The EM algorithm performs quite well. A real-life data set is analyzed for illustrative purposes.

Association between cardiometabolic index and kidney stones in US diabetic patients: NHANES 2007-2018.

The cardiometabolic index (CMI), encompassing obesity and lipid metrics, is potentially linked to kidney stone prevalence in diabetic patients. However, studies on this association are sparse. This research evaluates CMI's impact on kidney stone occurrence in this group. Utilizing data from the 2007-2018 National Health and Nutrition Examination Survey, we explored the relationship between CMI and kidney stones in diabetic patients through multivariate logistic regression, generalized additive models, and smoothed curve fitting. Robustness checks included subgroup analyses and propensity score matching (PSM). This study comprised 2714 participants in total, where the prevalence of kidney stones was found to be 16.82%. Using weighted multivariate logistic regression and fully adjusted models, it was revealed that elevated CMI levels are positively associated with an increased likelihood of developing kidney stones (OR = 1.17, 95% CI: 1.06, 1.30). Smooth curve fitting demonstrated that there was no non-linear relationship between CMI and kidney stones (log-likelihood ratio test P = 0.236). Subgroup analyses and interactions indicated that the association between CMI and kidney stone prevalence was notably stronger in individuals who were living with a partner /married and had a poverty income ratio (PIR) of 1.5 to less than 3.5 (P for interaction < 0.05). propensity score matching (PSM) further verified the robustness of our results. Elevated CMI correlates with greater kidney stone prevalence in diabetic individuals, particularly those married or living with a partner and within certain economic statuses. This study supports the hypothesis linking CMI and kidney stones in U.S. diabetic population, suggesting a target demographic for preventive strategies.

Decoding the fatty liver-hyperuricemia link in the obese and nonobese hypertensive patients: insights from a cohort study

Metabolic-dysfunction-associated fatty liver disease (MAFLD) and serum uric acid are closely related to cardiovascular and cerebrovascular diseases. However, the causal association between MAFLD and serum uric acid remains unclear. A total of 3417 patients without hyperuricemia were included in the final analysis. MAFLD was defined as fatty liver index (FLI) ≥ 30. Multivariate Cox regression analysis was used to explore the association between FLI and new-onset hyperuricemia. Restricted cubic splines and threshold saturation effect analysis were used to detect nonlinear associations. The mean age was 62.8 ± 8.3 year, and 68.5% were women. A total of 738 (21.6%) hypertensive patients developed new-onset hyperuricemia, 388 (11.4%) new-onset hyperuricemia10 and 190 (5.6%) new-onset hyperuricemia20 during the 4-year midday follow-up period. In the fully adjusted model, compared with the Q1 (FLI ≤ 8.5) group, the risk of hyperuricemia increased by 56% (HR: 1.56; 95% CI: 1.02, 2.38) in the Q4 (FLI > 39.4) group, new-onset hyperuricemia10 increased by 108% (HR: 2.08; 95% CI: 1.15, 3.78), and new-onset hyperuricemia20 increased by 156% (HR: 2.56; 95% CI: 1.11, 5.94), respectively. Saturation effects showed a nonlinear association between FLI and new-onset hyperuricemia (p for log likelihood ratio test < 0.05). Subgroup analysis and stratified analysis showed that there had a significantly higher risk of new-onset hyperuricemia in the patients with normal body mass index (< 24 kg/m2) (p for interaction: 0.018) and non-central obesity (p for interaction: 0.024). MAFLD is an independent risk factor for hyperuricemia in hypertensive patients, especially in patients with normal body mass index and non-central obesity.

Prevalence and determinants of termination of pregnancy among reproductive-age women who had a short preceding birth interval in Sub-Saharan Africa: a multilevel analysis.

Termination of pregnancy is one of the biggest five causes of maternal mortality in countries with low and middle incomes. Although termination of pregnancy is hazardous, its prevalence and determinates are not well studied in developing countries. Therefore, this study aims to assess the prevalence and determinants of termination of pregnancy among reproductive-age women who had a short preceding birth interval in Sub-Saharan Africa. Data from the most recent Demographic and Health Surveys, which covered 21 Sub-Saharan African countries from 2015 to 2022, were used for secondary data analysis. The study used a total of 283,785 women. Stata 14 was used to analyze the data. The determinants of termination of pregnancy were determined using a multilevel mixed-effects logistic regression model. Significant factors associated with termination of pregnancy were declared significant at p-values < 0.05. The result was interpreted using the confidence interval and adjusted odds ratio. The best-fit model was determined to be the one with the highest log likelihood ratio and the lowest deviance. In Sub-Saharan Africa, one in ten women with short birth intervals experienced pregnancy termination. Individual factors, including the sex of the preceding birth (AOR = 1.21, 95% CI: 1.05, 1.40), maternal age (AOR = 1.57, 95% CI: 1.27, 1.95), pregnancy complications (AOR = 1.28, 95% CI: 1.09, 1.49), No ANC visits (AOR = 2.29, 95% CI: 1.26, 4.14), previous cesarean section delivery (AOR = 1.74, 95% CI: 1.32, 2.30), <6 months of breastfeeding (AOR = 1.56, 95% CI: 1.35, 1.81), traditional contraception usage (AOR = 1.67, 95% CI: 1.13, 2.46), poor wealth status (AOR = 1.50, 95% CI: 1.22, 1.85), and community-level factors such as urban residence (AOR = 1.31, 95% CI: 1.06, 1.62) had higher odds of pregnancy termination. This study concludes that termination of pregnancy rates among women with short preceding birth interval is high. The study identified that both individual and community-level variables were determinants of termination of pregnancy. Therefore, the ministries of health in Sub-Saharan African countries should give attention to those women who underutilize antenatal care services and to women from urban areas while designing policies and strategies targeting reducing termination of pregnancy rates.

Emotional Intelligence May Be Associated with Some Forms of Creative Potential

The current study examined the relationship between creative potential, estimated with tests of divergent thinking (DT), and emotional intelligence (EI). Previous research has hinted at a relationship, but the EI–DT relationship may differ as a function of the tasks and the specific components of EI. With this in mind, the present investigation compared two DT tests (Social Games vs. Titles Games) and examined whether or not the Interpersonal and Intrapersonal subscales of EI were more associated with DT than the Adaptability and Stress Management EI subscales. The youth version of the Bar-On Emotional Quotient Inventory (EQ-i: YV) was used to measure EI. The measure of EI and the two DT tests were administered to 244 male and female gifted (N = 125) and nongifted (N = 119) high school students in Saudi Arabia. The first objective was to examine whether the EI–DT relationship differs based on the nature of the task of the two DT tests used in the current study (Social Games vs. Titles Games). The second objective was to test whether the Interpersonal and Intrapersonal subscales of EI are more associated with DT than the Adaptability and Stress Management EI subscales. Canonical correlation analysis showed that the relationship between the Social Games test and EI was stronger than the relationship between the Titles Games test and EI. Two path analyses were run: one for the total sample and the second for the gifted sample. The likelihood ratio test showed that the Social Games test was more associated with EQ-i subscales than the Titles Games test for both samples. As expected, the Inter- and the Intrapersonal subscales of the EQ-i were more highly related to Social Games fluency and originality scores compared with the Stress Management and Adaptability subscales. Limitations and future directions are discussed.

Spatiotemporal analysis of roadway terrains impact on large truck driver injury severity outcomes using random parameters with heterogeneity in means and variances approach

This study employs a partially temporally constrained modeling approach to examine spatiotemporal variations in driver injury severity in single-vehicle large truck crashes across different terrains in California, allowing for a nuanced understanding of how specific factors influencing injury outcomes may change over time. Utilizing crash data from January 1st, 2015, to December 31st, 2017, obtained from the Highway Safety Information System, this study categorizes terrains as flat, rolling, and mountainous terrain and employs a random parameter multinomial logit model with heterogeneity in means and variance to account for potential heterogeneity in crash injury outcomes. This approach helps understand how different terrains influence injury severities while allowing for parameter variability across observations. The analysis is further enriched by likelihood ratio tests to verify the stability and temporal transferability of the model estimates across different terrains and years. Notably, the study identifies truck overturning as the first and second event in a crash as a consistent parameter influencing injury severity across all years, emphasizing its importance regardless of terrain or time in single-vehicle large truck crashes. Furthermore, this study takes into account a wide range of variables, including driver characteristics, crash attributes, roadway characteristics, vehicle features, and environmental and temporal aspects. The findings highlight the importance of terrain-specific elements in traffic safety assessments and the need for focused measures to reduce serious injuries in truck crashes. The out-of-sample simulation revealed a significant increase in minor and severe injuries when flat terrain parameters were replaced with those from rolling or mountainous terrains. This research not only contributes to the existing literature by detailing the dynamics of injury severity in single-vehicle large truck crashes but also announces the utility of partially temporally constrained models in enhancing traffic safety management strategies.

Social determinants of health and variability in treatment for patients with early-stage Non-Small Cell Lung Cancer.

In non-small cell lung cancer (NSCLC), social determinants of health (SDOHs) influence treatment, but SDOHs with geographic precision are infrequently used in real-world research due to privacy considerations. This research aims to characterize the influence of census-tract level SDOHs on treatment for stage I and IIa NSCLC. Patients diagnosed between 1/1/17 and 9/30/22 with stages I and IIa NSCLC in the Syapse Learning Health Network had their addresses geocoded and linked to five census tract-level indicators of SDOH (social vulnerability index (SVI), percent (%) housing burden, % broadband internet access, primary care shortage area, and rurality). Clinical and demographic characteristics were ascertained from medical records. Nested multinomial logistic regression models estimated associations between SDOHs and initial treatment using two-sided Wald tests. The collective statistical significance of SDOHs was assessed with a likelihood ratio test (LRT) comparing nested models. Descriptive statistics described time-to-treatment-initiation. Among 3595 patients, 58% were initially treated with surgery, 29% with radiation, and 12% with "other." Two SDOH variables were associated with increased relative risk ratios (RRR) for radiation therapy compared to surgery: living in primary care shortage areas (RRR 1.61, 95% CI: (1.23-2.10)) and living in non-metropolitan areas (RRR 1.45 (1.02-2.07)). The LRT suggested that the five SDOH variables collectively improved the treatment model. Further, patients in areas with high SVI, low internet access, and high housing-burden initiated treatment later. When using precise estimates of geospatial SDOHs, these measures were associated with treatment, and should be considered in analyses of cancer outcomes.

Osteoprotegerin, Osteopontin, and Osteocalcin Are Associated With Cardiovascular Events in Type 2 Diabetes: Insights From EXSCEL.

To evaluate the association of four bone metabolism biomarkers (osteoprotegerin, osteopontin, sclerostin, and osteocalcin) with cardiovascular events in people with type 2 diabetes (T2D). The Exenatide Study of Cardiovascular Event Lowering (EXSCEL) was a randomized clinical trial evaluating the cardiovascular (CV) safety and efficacy of once-weekly exenatide for patients with T2D. Candidate biomarker data were selected from proteomic profiling performed at baseline and 12 months after randomization samples by SomaScan assay in 5,473 trial participants. The primary composite outcome was the first occurrence of CV death, nonfatal myocardial infarction, or nonfatal stroke (major cardiovascular events [MACE]). Cox proportional hazards models controlling for confounders were used for time-to-event analyses to calculate hazard ratios (HRs) with 95% CI for a 1 SD increase in the biomarker concentrations. The primary outcome occurred in 813 participants (14.9%). Higher levels of osteoprotegerin (HR 1.11; 95% CI 1.03-1.20; P = 0.0047) and osteopontin (HR 1.10; 95% CI 1.02-1.18; P = 0.0095) were associated with an increased risk of MACE. The addition of osteoprotegerin and osteopontin to a clinical predictive model containing traditional CV risk factors provided minimal incremental value for MACE prediction (C-index 0.629 vs. 0.638; likelihood ratio test P < 0.001). Osteocalcin and sclerostin were not associated with MACE. Osteocalcin had a nonlinear association with all-cause death and with CV death. Higher levels of osteoprotegerin and osteopontin are associated with an increased risk of CV events in people with T2D, supporting the hypothesis that pathways involved in bone metabolism play a role in CV disease.

L-shaped association of plasma low-density lipoprotein cholesterol with atrial fibrillation recurrence after catheter ablation: a prospective cohort study

The association between plasma low-density lipoprotein cholesterol (LDL-C) and atrial fibrillation (AF) recurrence after catheter ablation remains unclear. We aimed to assess the relationship between preprocedural LDL-C and the AF recurrence in patients undergoing catheter ablation. The cohort study consecutively included AF patients who underwent de novo catheter ablation between April 2021 and January 2023 in the Second Affiliated Hospital of Nanchang University in Jiangxi Province, China. Patients were divided into quartiles based on their baseline fasting LDL-C level (Q1-Q4). Multivariable Cox proportional hazards models were used to evaluate the relationship between LDL-C and AF recurrence. Our analysis included the use of a generalized additive model and smooth curve fitting (penalized spline method), and two-piecewise Cox proportional hazards models, to address the nonlinearity between preprocedural LDL-C and AF recurrence. A total of 482 AF patients with de novo catheter ablation were enrolled, with a median follow-up period of 15.00 months, AF recurrence occurred in 96 (19.92%) patients. The relationship between preprocedural LDL-C and AF recurrence after ablation presented as an L-shape, and the inflection point for the curve was found at the LDL-C level of 3.20 mmol/L (Log likelihood ratio P = 0.031). The hazard ratios (HR) [(95% confidence intervals (CI)] for AF recurrence were 0.50 (0.33–0.74) and 2.11 (0.76–5.89) to the left and right of the inflection point, respectively. Lower LDL-C level is associated with increased AF recurrence risk after catheter ablation were consistent across all subgroups.