Lymph Node Yield in Lung Cancer Resection is Associated With Demographic and Institutional Factors.

INTRODUCTION: Lymphadenectomy is routinely performed during surgical resection of nonsmall cell lung cancer (NSCLC). Lymph node yield and number of nodal stations sampled are important prognostic markers viewed as surrogates of surgical quality. The purpose of this study was to identify factors associated with these quality metrics after resection of NSCLC. MATERIALS AND METHODS: We identified NSCLC patients undergoing resection at a single institution from 2010 to 2021. Cases were matched to detailed pathologist reports, which included lymph node yield and number of stations sampled. Demographic and clinical characteristics were analyzed individually using unadjusted linear regression to identify factors associated with lymph node yield and number of stations sampled. Multivariable linear regression analyses were performed to evaluate the same end points, using covariates determined through stepwise-backwards selection. RESULTS: The study cohort included 836 patients. Multivariable regression demonstrated that male sex, history of cardiothoracic surgery, and individual pathologist were independently associated with lymph node yield. Among 18 pathologists, interpathologist coefficients with respect to lymph node yield varied from -5.61 to 11.25. Multivariable regression demonstrated White race and history of cardiothoracic surgery to be independently associated with number of nodal stations sampled, as well as individual surgeon and pathologist. CONCLUSIONS: Lymph node yield and number of nodal stations sampled after NSCLC resection may vary based on patient demographic and clinical characteristics, as well as institutional factors. These factors should be accounted for when using these metrics as markers of surgical quality and prognosis of NSCLC.

Demographics of Anterior Chest Wall Deformity Patients: A Tertiary Children's Hospital Experience.

INTRODUCTION: Anterior chest wall deformities consist of abnormal development of the chest, with the most common congenital deformities being pectus excavatum (PE) and pectus carinatum (PC). Surgical series are common, but less research is present assessing the demographics of all who present for initial evaluation. The purpose of this study is to describe the patient characteristics of those who present for ambulatory surgical evaluation. METHODS: Data were collected from initial patient visits to an established multispecialty chest wall deformities program at a large Children's Hospital from 2017 to 2021. Variables assessed included primary diagnosis, age, sex, race/ethnicity, and whether surgical correction was performed. RESULTS: A total of 1510 children were evaluated: 50.0% (n = 755) with PE, 43.3% (n = 653) with PC, 2.7% (n = 41) with mixed chest wall deformities, 0.7% (n = 10) with Poland syndrome, 1.1% (n = 17) with Currarino-Silverman syndrome, and 2.3% (n = 34) with other anterior chest wall deformities. Males and females presented at mean age of 12.8 (4.2) and 10.9 (5.5) years, respectively (P = 0.001). White children represented 61.1% of the overall population while Hispanic children represented 26.3%. White, non-Hispanic children represented 61.9% and 71.5% and Hispanic children represented 26.0% and 26.3% of the PE and PC populations, respectively. CONCLUSIONS: Most patients seen in an urban chest wall deformities clinic were White, non-Hispanic; however, the proportion of other groups such as Hispanic and Asian is greater in this cohort than previously described. Further research is ongoing to ascertain the extent to which disease predisposition versus access to care play roles in this population.

Genomic and demographic processes differentially influence genetic variation across the human X chromosome.

Many forces influence genetic variation across the genome including mutation, recombination, selection, and demography. Increased mutation and recombination both lead to increases in genetic diversity in a region-specific manner, while complex demographic patterns shape patterns of diversity on a more global scale. While these processes act across the entire genome, the X chromosome is particularly interesting because it contains several distinct regions that are subject to different combinations and strengths of these forces: the pseudoautosomal regions (PARs) and the X-transposed region (XTR). The X chromosome thus can serve as a unique model for studying how genetic and demographic forces act in different contexts to shape patterns of observed variation. We therefore sought to explore diversity, divergence, and linkage disequilibrium in each region of the X chromosome using genomic data from 26 human populations. Across populations, we find that both diversity and substitution rate are consistently elevated in PAR1 and the XTR compared to the rest of the X chromosome. In contrast, linkage disequilibrium is lowest in PAR1, consistent with the high recombination rate in this region, and highest in the region of the X chromosome that does not recombine in males. However, linkage disequilibrium in the XTR is intermediate between PAR1 and the autosomes, and much lower than the non-recombining X. Finally, in addition to these global patterns, we also observed variation in ratios of X versus autosomal diversity consistent with population-specific evolutionary history as well. While our results were generally consistent with previous work, two unexpected observations emerged. First, our results suggest that the XTR does not behave like the rest of the recombining X and may need to be evaluated separately in future studies. Second, the different regions of the X chromosome appear to exhibit unique patterns of linked selection across different human populations. Together, our results highlight profound regional differences across the X chromosome, simultaneously making it an ideal system for exploring the action of evolutionary forces as well as necessitating its careful consideration and treatment in genomic analyses.

A theory of demographic optimality in forests.

Carbon uptake by the land is a key determinant of future climate change. Unfortunately, Dynamic Global Vegetation Models have many unknown internal parameters which leads to significant uncertainty in projections of the future land carbon sink. By contrast, observed forest inventories in both Amazonia and the USA show strikingly common tree-size distributions, pointing to a simpler modelling paradigm. The curvature of these size-distributions is related to the ratio of mortality to growth in Demographic Equilibrium Theory (DET). We extend DET to include recruitment limited by competitive exclusion from existing trees. From this, we find simultaneous maxima of tree density and biomass in terms of respectively the ratio of mortality to growth and the proportion of primary productivity allocated to reproduction, an idea we call Demographic Optimality (DO). Combining DO with the ratio of mortality to growth common to the US and Amazon forests, results in the prediction that about an eighth of productivity should be allocated to reproduction, which is broadly consistent with observations. Another prediction of the model is that seed mortality should decrease with increasing seed size, such that the advantage of having many small seeds is nullified by the higher seed mortality. Demographic Optimality is therefore consistent with the common shape of tree-size distributions seen in very different forests, and an allocation to reproduction that is independent of seed size.

Identifying dyslexia in school pupils from eye movement and demographic data using artificial intelligence.

This paper represents our research results in the pursuit of the following objectives: (i) to introduce a novel multi-sources data set to tackle the shortcomings of the previous data sets, (ii) to propose a robust artificial intelligence-based solution to identify dyslexia in primary school pupils, (iii) to investigate our psycholinguistic knowledge by studying the importance of the features in identifying dyslexia by our best AI model. In order to achieve the first objective, we collected and annotated a new set of eye-movement-during-reading data. Furthermore, we collected demographic data, including the measure of non-verbal intelligence, to form our three data sources. Our data set is the largest eye-movement data set globally. Unlike the previously introduced binary-class data sets, it contains (A) three class labels and (B) reading speed. Concerning the second objective, we formulated the task of dyslexia prediction as regression and classification problems and scrutinized the performance of 12 classifications and eight regressions approaches. We exploited the Bayesian optimization method to fine-tune the hyperparameters of the models: and reported the average and the standard deviation of our evaluation metrics in a stratified ten-fold cross-validation. Our studies showed that multi-layer perceptron, random forest, gradient boosting, and k-nearest neighbor form the group having the most acceptable results. Moreover, we showed that although separately using each data source did not lead to accurate results, their combination led to a reliable solution. We also determined the importance of the features of our best classifier: our findings showed that the IQ, gender, and age are the top three important features; we also showed that fixation along the y-axis is more important than other fixation data. Dyslexia detection, eye fixation, eye movement, demographic, classification, regression, artificial intelligence.

Uncertainty in the association between socio-demographic characteristics and mental health.

Questionnaires are among the most basic and widespread tools to assess the mental health of a population in epidemiological and public health studies. Their most obvious advantage (firsthand self-report) is also the source of their main problems: the raw data requires interpretation, and are a snapshot of the specific sample's status at a given time. Efforts to deal with both issues created a bi-dimensional space defined by two orthogonal axes, in which most of the quantitative mental health research can be located. Methods aimed to assure that mental health diagnoses are solidly grounded on existing raw data are part of the individual validity axis. Tools allowing the generalization of the results across the entire population compose the collective validity axis. This paper raises a different question. Since one goal of mental health assessments is to obtain results that can be generalized to some extent, an important question is how robust is a questionnaire result when applied to a different population or to the same population at a different time. In this case, there is deep uncertainty, without any a priori probabilistic information. The main claim of this paper is that this task requires the development of a new robustness to deep uncertainty axis, defining a three-dimensional research space. We demonstrate the analysis of deep uncertainty using the concept of robustness in info-gap decision theory. Based on data from questionnaires collected before and during the Covid-19 pandemic, we first locate a mental health assessment in the space defined by the individual validity axis and the collective validity axis. Then we develop a model of info-gap robustness to uncertainty in mental health assessment, showing how the robustness to deep uncertainty axis interacts with the other two axes, highlighting the contributions and the limitations of this approach. The ability to measure robustness to deep uncertainty in the mental health realm is important particularly in troubled and changing times. In this paper, we provide the basic methodological building blocks of the suggested approach using the outbreak of Covid-19 as a recent example.

[Socio-demographic and clinical-psychological characteristics of patients with residual schizophrenia and directions of their psychosocial rehabilitation]. / Sotsial'no-demograficheskie i kliniko-psikhologicheskie osobennosti patsientov s ostatochnoi shizofreniei i napravleniya ikh psikhosotsial'noi reabilitatsii.

OBJECTIVE: To analyze the socio-demographic, clinical and psychological characteristics of patients with residual schizophrenia, to identify variants of residual states and to determine measures for psychosocial rehabilitation on this basis. MATERIAL AND METHODS: At the time of investigation, 91 patients with the diagnosis of residual schizophrenia (F20.5xx according to ICD-10) were under dispensary supervision in the psychoneurological dispensary No. 18 of Moscow. A study of the medical records of all these patients was carried out. Twenty-three patients consented to face-to-face examination. The Positive and negative syndrome scale (PANSS), the Symptom Checklist-90-Revised (SCL-90-R), the Brief Assessment of Cognitive Functions in Schizophrenia (BACS) and the author's questionnaire concerning the opinion of psychiatrists on the clinical and social characteristics of patients with residual schizophrenia were used. Mathematical and statistical methods implemented in the STATISTICA 12.1 software and the Excel office suite were used. The method of stochastic nesting of neighbors («T-distributed Stochastic Neighbor Embedding¼, t-SNE) implemented in the Python program to cluster cases and identify variants of residual states was used. RESULTS: The patients with residual schizophrenia belonged to the cohort of elderly patients (mean age 66.3±13.28 years) with a predominance of females (62.22%). At the time of examination, the course of the schizophrenic process had a negative impact on the social life and professional activities of patients, which led to disability of 74.72% patients and 91.55% of them had disability due to a mental disorder. The analysis showed that patients with residual schizophrenia was a heterogeneous group with a predominant presence of negative symptoms in the clinical picture (the composite score on the PANSS negative subscale was17.79±6.67). Three variants of residual states were identified using clustering by the t-SNE method of individual PANSS indicators. Deficiency symptoms with features of pseudoorganic syndrome prevailed in the first variant. In the second variant, patients had mild positive symptoms, mainly in the form of paranoia and residual delirium, as well as a psychopathic syndrome. The third, small group, included patients with the most favorable variant of remission, having a fairly high level of social adaptation, mainly with personality changes. CONCLUSION: The obtained data were correlated with the results of a psychological examination. It was revealed that patients with residual schizophrenia were not sufficiently included in the process of psychosocial treatment and rehabilitation. Taking into account the identified variants of residual states, the directions of possible psychosocial interventions were determined.

Comprehensive Health Insurance and access to maternal healthcare services among Peruvian women: a cross-sectional study using the 2021 national demographic survey.

BACKGROUND: The government-subsidized health insurance scheme Seguro Integral de Salud ("SIS") was introduced in Peru initially to provide coverage to uninsured and poor pregnant women and children under five years old and was later extended to cover all uninsured members of the population following the Peruvian Plan Esencial de Aseguramiento Universal - "PEAS" (Essential UHC Package). Our study aimed to analyze the extent to which the introduction of SIS has increased equity in access and quality by comparing the utilization of maternal healthcare services among women with different insurance coverages. METHODS: Relying on the 2021 round of the nationally-representative survey "ENDES" (Encuesta Nacional Demográfica y de Salud Familiar), we analyzed data for 19,181 women aged 15-49 with a history of pregnancy in the five years preceding the survey date. We used a series of logistic regressions to explore the association between health insurance coverage (defined as No Insurance, SIS, or Standard Insurance) and a series of outcome variables measuring access to and quality of all services along the available maternal healthcare continuum. RESULTS: Only 46.5% of women across all insurance schemes reported having accessed effective ANC prevention. Findings from the adjusted logistic regression confirmed that insured women were more likely to have accessed ANC services compared with uninsured women. Our findings indicate that women in the "SIS" group were more likely to have accessed six ANC visits (aOR = 1.40; 95% CI 1.14-1.73) as well as effective ANC prevention (aOR = 1.32; 95% CI 1.17-1.48), ANC education (aOR = 1.59; 95% CI 1.41-1.80) and ANC screening (aOR = 1.46; 95% CI 1.27-1.69) during pregnancy, compared with women in the "Standard Insurance" group [aOR = 1.35 (95% CI 1.13-1.62), 1.22 (95% CI 1.04-1.42), 1.34 (95% CI 1.18-1.51) and 1.31(95% CI 1.15-1.49)] respectively. In addition, women in the "Standard Insurance" group were more likely to have received skilled attendance at birth (aOR = 2.17, 95% CI 1.33-3.55) compared with the women in the "SIS" insurance group (aOR = 2.12; 95% CI 1.41-3.17). CONCLUSIONS: Our findings indicate the persistence of inequities in access to maternal healthcare services that manifest themselves not only in the reduced utilization among the uninsured, but also in the lower quality of service coverage that uninsured women received compared with women insured under "Standard Insurance" or "SIS". Further policy reforms are needed both to expand insurance coverage and to ensure that all women receive the same access to care irrespective of their specific insurance coverage.

Study on incentive factors and incentive effect differences of teachers in universities and colleges under the view of demographic variables.

The purpose of this study is to explore the factors of University Teachers' motivation and the differences among the factors under different background variables. Based on a great deal of literatures, this paper classifies the incentive content of teachers in universities and colleges into two aspects: internal incentive and external incentive. Through constructing the incentive structure equation model, this paper analyzes and summarizes the influence factors of the incentive of teachers in universities and colleges from two aspects: internal incentive and external incentive, and finds that external incentive is divided into salary and welfare, organizational environment, career development, and internal incentive is divided into work achievement, individual value, as well as innovation incentive. On this basis, we find that there are significant differences in incentive level based on the characteristics of demographics. Among them, there are significant differences in the factors, including marital status and external incentive. There are significant differences in salary and welfare, organizational environment, work achievement and individual value among different ages. There are significant differences in career development of whether undertaking part-time administrative posts. There are significant differences in salary and welfare, organizational environment and career development among different teaching ages. There are significant differences in organizational environment and career development between different titles. There are significant differences in salary and welfare, organizational environment and incentive between different educational backgrounds, and there are significant differences in innovation incentive between different school types.

Tracking 20 years of forest demographics in east Texas, USA, using national forest inventory data.

Forest resource reporting techniques primarily use the two most recent measurements for understanding forest change. Multiple remeasurements now exist within the US national forest inventory (NFI), providing an opportunity to examine long-term forest demographics. We leverage two decades of remeasurements to quantify live-dead wood demographics which can better inform estimates of resource changes in forest ecosystems. Our overall objective is to identify opportunities and gaps in tracking 20 years of forest demographics within the US NFI using east Texas as a pilot study region given its diversity of tree species, prevalence of managed conditions, frequency of disturbances, and relatively rapid change driven by a warm, humid climate. We examine growth and mortality rates, identify transitions to downed dead wood/litter and removal via harvest, and describe implications of these processes focusing on key species groups (i.e., loblolly pine, post oak, and water oak) and size classes (i.e., saplings, small and large trees). Growth and mortality rates fluctuated differently over time by species and stem sizes in response to large-scale disturbances, namely the 2011 drought in Texas. Tree-fall rates were highest in saplings and snag-fall rates trended higher in smaller trees. For removal rates, different stem sizes generally followed similar patterns within each species group. Forest demographics from the field-based US NFI are informative for identifying diffuse lagged mortality, species- and size-specific effects, and management effects. Moreover, researchers continually seek to employ ancillary data and develop new statistical methods to enhance understanding of forest resource changes from field-based inventories.

Diversity and evolution of the MHC class II DRB gene in the Capra sibirica experienced a demographic fluctuation in China.

The major histocompatibility complex (MHC) genes are the most polymorphic genes in vertebrates, and their proteins play a critical role in adaptive immunity for defense against a variety of pathogens. MHC diversity was lost in many species after experiencing a decline in size. To understand the variation and evolution of MHC genes in the Siberian ibex, Capra sibirica, which has undergone a population decline, we analyzed the variation of the second exon of MHC class II DRB genes in samples collected from five geographic localities in Xinjiang, China, that belong to three diverged mitochondrial clades. Consequently, we identified a total of 26 putative functional alleles (PFAs) with 260 bp in length from 43 individuals, and found one (for 27 individuals) to three (for 5 individuals) PFAs per individual, indicating the presence of one or two DRB loci per haploid genome. The Casi-DRB1*16 was the most frequently occurring PFA, Casi-DRB1*22 was found in only seven individuals, 14 PFAs occurred once, 7 PFAs twice, implying high frequency of rare PFAs. Interestingly, more than half (15) of the PFAs were specific to clade I, only two and three PFAs were specific to clades II and III, respectively. So, we assume that the polygamy and sexual segregation nature of this species likely contributed to the allelic diversity of DRB genes. Genetic diversity indices showed that PFAs of clade II were lower in nucleotide, amino acid, and supertype diversity compared to those of the other two clades. The pattern of allele sharing and FST values between the three clades was to some extent in agreement with the pattern observed in mitochondrial DNA divergence. In addition, recombination analyses revealed no evidence for significant signatures of recombination events. Alleles shared by clades III and the other two clades diverged 6 million years ago, and systematic neighbor grids showed Trans-species polymorphism. Together with the PAML and MEME analyses, the results indicated that the DRB gene in C. sibirica evolved under balancing and positive selection. However, by comparison, it can be clearly seen that different populations were under different selective pressures. Our results are valuable in understanding the diversity and evolution of the DRB gene in a mountain living C. sibirica and in making decisions on future long-term protection strategies.

Equity trends for the UHC service coverage sub-index for reproductive, maternal, newborn and child health in Pakistan: evidence from demographic health surveys.

BACKGROUND: Pakistan, the world's sixth most populous country and the second largest in South Asia, is facing challenges related to reproductive, maternal, newborn and child health (RMNCH) that are exacerbated by various inequities. RMNCH coverage indicators such as antenatal care (ANC) and deliveries at health facilities have been improving over time, and the maternal mortality ratio (MMR) is gradually declining but not at the desired rates. Analysing and documenting inequities with reference to key characteristics are useful to unmask the disparities and to amicably implement targeted equity-oriented interventions. METHODS: Pakistan Demographic Health Survey (PDHS) based UHC service coverage tracer indicators were derived for the RMNCH domain at the national and subnational levels for the two rounds of the PDHS in 2012 and 2017. These derivations were subgrouped into wealth quintiles, place of residence, education and mothers' age. Dumbbell charts were created to show the trends and quintile-specific coverage. The UHC service coverage sub-index for RMNCH was constructed to measure the absolute and relative parity indices, such as high to low absolute difference and high to low ratios, to quantify health inequities. The population attributable risk was computed to determine the overall population health improvement that is possible if all regions have the same level of health services as the reference point (national level) across the equity domains. RESULTS: The results indicate an overall improvement in coverage across all indicators over time, but with a higher concentration of data points towards higher coverage among the wealthiest groups, although the poorest quintile continues to have low coverage in all regions. The UHC service coverage sub-index on RMNCH shows that Pakistan has improved from 45 to 63 overall, while Punjab improved from 50 to 59 and Sindh from 43 to 55. The highest improvement is evident in Khyber Pakhtunkhwa (KP) province, which has increased from 31 in 2012 to 51 in 2017. All regions made slow progress in narrowing the gap between the poorest and wealthiest groups, with particularly noteworthy improvements in KP and Sindh, as indicated by the parity ratio. The RMNCH service coverage sub-index gap was the greatest among women aged 15-19 years, those who belonged to the poorest wealth quintile, had no education, and resided in rural areas. CONCLUSIONS: Analysing existing data sources from an equity lens supports evidence-based policies, programs and practices with a focus on disadvantaged subgroups.

Coping strategies in postpartum women: exploring the influence of demographic and maternity factors.

BACKGROUND: Postpartum depression is a frequent mental health issue that affects many women due to this stressful phase. The aim of the study is to gain insight into the coping strategies employed by postpartum women and to explore how these strategies are influenced by various demographic and maternity factors. METHODS: The study adopted a quantitative, cross-sectional design. Data were collected from 239 postpartum women receiving care at a Gynecology and Obstetrics Clinic using self-reported tools, which include the Brief COPE survey and the socio-demographics and obstetric/maternal history form from October 2022 to April 2023. RESULTS: The study findings indicate that individuals aged over 40 tend to use more emotional-focused coping compared to those aged 21-30 (p = 0.002) and 31-40. Additionally, both genders of children were associated with more emotional-focused coping (p = 0.007) compared to only having boys. Cesarean section delivery (p = 0.001) was associated with more avoidant-focused coping than normal vaginal delivery. Avoidant-focused coping was significantly predicted by problem-focused coping (p < 0.001), emotional-focused coping (p = 0.034), age (p = 0.003), and gender of children (only boys, p < 0.001; both boys and girls, p = 0.019). Furthermore, problem-focused coping was significantly predicted by age (p = 0.004), gender of children (male child, p = 0.002; both boy and girl: p = 0.014), and avoidant-focused coping (p < 0.001). CONCLUSIONS: The study examined how postpartum women cope with the challenges of motherhood and how this relates to their demographic and maternity factors. The results suggest that healthcare professionals should promote effective coping strategies and discourage avoidance-oriented approaches in postpartum interventions.

Molecular phylogeography and historical demography of a widespread herbaceous species from eastern North America, Podophyllum peltatum.

PREMISE: Glacial/interglacial cycles and topographic complexity are both considered to have shaped today's diverse phylogeographic patterns of taxa from unglaciated eastern North America (ENA). However, few studies have focused on the phylogeography and population dynamics of wide-ranging ENA herbaceous species occurring in forest understory habitat. We examined the phylogeographic pattern and evolutionary history of Podophyllum peltatum L., a widely distributed herb inhabiting deciduous forests of ENA. METHODS: Using chloroplast DNA (cpDNA) sequences and nuclear microsatellite loci, we investigated the population structure and genetic diversity of the species. Molecular dating, demographic history analyses, and ecological niche modeling were also performed to illustrate the phylogeographic patterns. RESULTS: Our cpDNA results identified three main groups that are largely congruent with boundaries along the Appalachian Mountains and the Mississippi River, two major geographic barriers in ENA. Populations located to the east of the Appalachians and along the central Appalachians exhibited relatively higher levels of genetic diversity. Extant lineages may have diverged during the late Miocene, and range expansions of different groups may have happened during the Pleistocene glacial/interglacial cycles. CONCLUSIONS: Our findings indicate that geographic barriers may have started to facilitate the population divergence in P. peltatum before the Pleistocene. Persistence in multiple refugia, including areas around the central Appalachians during the Quaternary glacial period, and subsequent expansions under hospitable climatic condition, especially westward expansion, are likely responsible for the species' contemporary genetic structure and phylogeographic pattern.

Risk-stratification machine learning model using demographic factors, gynaecological symptoms and ß-catenin for endometrial hyperplasia and carcinoma: a cross-sectional study.

BACKGROUND: Demographic features, suggestive gynaecological symptoms, and immunohistochemical expression of endometrial ß-catenin have a prognostic capacity for endometrial hyperplasia and carcinoma. This study assessed the interaction of all variables and developed risk stratification for endometrial hyperplasia and carcinoma. METHODS: This cross-sectional study was conducted from January 2023 to July 2023 at two teaching hospitals in Makassar Indonesia. Patients (< 70 years old) with suggestive symptoms of endometrial hyperplasia or carcinoma or being referred with disease code N.85 who underwent curettage and/or surgery for pathology assessment except those receiving radiotherapy, or chemotherapy, presence of another carcinoma, coagulation disorder, and history of anti-inflammatory drug use and unreadable samples. Demographic, and clinical symptoms were collected from medical records. Immunohistochemistry staining using mouse-monoclonal antibodies determined the ß-catenin expression (percentage, intensity, and H-score) in endometrial tissues. Ordinal and Binary Logistic regression identified the potential predictors to be included in neural networks and decision tree models of histopathological grading according to the World Health Organization/WHO grading classification. RESULTS: Abdominal enlargement was associated with worse pathological grading (adjusted odds ratio/aOR 6.7 95% CI 1.8-24.8). Increasing age (aOR 1.1 95% CI 1.03-1.2) and uterus bleeding (aOR 5.3 95% CI 1.3-21.6) were associated with carcinoma but not with %ß-catenin and H-Score. However, adjusted by vaginal bleeding and body mass index, lower %ß-catenin (aOR 1.03 95% 1.01-1.05) was associated with non-atypical hyperplasia, as well as H-Score (aOR 1.01 95% CI 1.01-1.02). Neural networks and Decision tree risk stratification showed a sensitivity of 80-94.8% and a specificity of 40.6-60% in differentiating non-atypical from atypical and carcinoma. A cutoff of 55% ß-catenin area and H-Score of 110, along with other predictors could distinguish non-atypical samples from atypical and carcinoma. CONCLUSION: Risk stratification based on demographics, clinical symptoms, and ß-catenin possesses a good performance in differentiating non-atypical hyperplasia with later stages.

Influence of demographic factors on the occurrence of motion artefacts in HR-pQCT.

The study shows a high incidence of motion artefacts in a central European population and a significant increase of those artefacts with higher age. These findings may impact on the design and conduct of future in vivo HR-pQCT studies or at least help to estimate the potential number of drop outs due to unusable image quality. PURPOSE: Motion artefacts in high-resolution peripheral quantitative computed tomography (HR-pQCT) are challenging, as they introduce error into the resulting measurement data. The aim of this study was to assess the general occurrence of motion artefacts in healthy distal radius and to evaluate the influence of demographic factors. METHODS: The retrospective study is based on 525 distal radius second-generation HR-pQCT scans of 95 patients. All stacks were evaluated by two experienced observers and graded according to the visual grading scale recommended by the manufacturer, ranging from grade 1 (no visible motion artefacts) to grade 5 (severe motion artefacts). Correlations between demographic factors and image quality were evaluated using a linear mixed effects model analysis. RESULTS: The average visual grading was 2.7 (SD ± 0.7). Age and severity of motion artefacts significantly correlated (p = 0.026). Patients aged 65 years or above had an average image quality between grades 1 and 3 in 72.7% of cases, while patients younger than 65 had an average image quality between grades 1 and 3 in 91.9% of cases. Gender, smoking behaviour, and handedness had no significant influence on motion artefacts. CONCLUSION: This study showed a high incidence of motion artefacts in a representative central European population, but also a significant increase of motion artefacts with higher age. This could impact further study designs by planning for a sufficiently large and if possible a more selective study population to gain a representative amount of high-quality image data.

[Epilepsy and inequality: demographic description and analysis of the difficulty in accessing advanced resources in a population in a small health area]. / Epilepsia y desigualdad: descripción demográfica y análisis de la dificultad para el acceso a recursos avanzados en una población de un área de salud pequeña.

INTRODUCTION: Epilepsy is a very common neurological disease with high morbidity and mortality. Drug-resistant epilepsy (DRE) poses a major therapeutic challenge, even for experts in the field. Despite this, access to advanced resources for this type of patient remains difficult and unequal. The aim of this study is to analyse inequality in a population belonging to a first level hospital. PATIENTS AND METHODS: An analytical observational cross-sectional study was conducted on epileptic patients attending neurology consultations in Area IX of the Murcian Health Service. Demographic, clinical, therapeutic, prognostic and equity variables are described, and significant differences between different subgroups are analysed. RESULTS: The study included 68 patients with a mean age of 42.93 years. Focal epilepsy was the main type (64.7%), and the most commonly used drugs were levetiracetam (33.8%), valproic acid (27.9%) and lamotrigine (22.1%). DRE occurred in 18 patients (26.5% of the total) and only four were under active follow-up in an epilepsy unit, meaning that 71% did not have access to a necessary resource (advanced therapeutic gap). CONCLUSIONS: This study demonstrates that epilepsy inequality continues to be a problem, especially in certain geographical areas, with a lack of access to advanced care for patients who need it most. The solution can be achieved by increasing human and material resources to improve overall patient care, thus strengthening both referral hospitals and epilepsy units.

TITLE: Epilepsia y desigualdad: descripción demográfica y análisis de la dificultad para el acceso a recursos avanzados en una población de un área de salud pequeña.Introducción. La epilepsia es una enfermedad neurológica muy frecuente que implica una elevada morbimortalidad. La epilepsia farmacorresistente (EFR) supone un desafío terapéutico superior, incluso para expertos en la materia. A pesar de ello, el acceso a recursos avanzados para este tipo de pacientes continúa siendo dificultoso y desigual. El objetivo de este estudio es analizar la desigualdad en una población perteneciente a un hospital de primer nivel. Pacientes y métodos. Se llevó a cabo un estudio transversal observacional analítico con pacientes epilépticos que acuden a consultas de neurología del área IX del Servicio Murciano de Salud. Se describen variables demográficas, clínicas, terapéuticas, pronósticas y de equidad, y se analizan diferencias significativas entre distintos subgrupos. Resultados. En el estudio se incluyó a 68 pacientes con una media de edad de 42,93 años. El tipo de epilepsia principal fue la focal (64,7%), y los fármacos más usados fueron el levetiracetam (33,8%), el ácido valproico (27,9%) y la lamotrigina (22,1%). La EFR se dio en 18 pacientes (el 26,5% del total) y sólo cuatro se encontraban en seguimiento activo en una unidad de epilepsia, lo que implica que el 71% no accedía a un recurso necesario (advanced therapeutic gap). Conclusiones. Este estudio demuestra que la desigualdad en la epilepsia continúa siendo un problema, especialmente en ciertas áreas geográficas, con una falta de acceso a atención avanzada en pacientes que más lo necesitan. La solución puede conseguirse aumentando recursos humanos y materiales que mejoren la atención global del paciente, reforzando así tanto los hospitales de referencia como las unidades de epilepsia.

Quantifying online citizen science: Dynamics and demographics of public participation in science.

Citizen scientists around the world are collecting data with their smartphones, performing scientific calculations on their home computers, and analyzing images on online platforms. These online citizen science projects are frequently lauded for their potential to revolutionize the scope and scale of data collection and analysis, improve scientific literacy, and democratize science. Yet, despite the attention online citizen science has attracted, it remains unclear how widespread public participation is, how it has changed over time, and how it is geographically distributed. Importantly, the demographic profile of citizen science participants remains uncertain, and thus to what extent their contributions are helping to democratize science. Here, we present the largest quantitative study of participation in citizen science based on online accounts of more than 14 million participants over two decades. We find that the trend of broad rapid growth in online citizen science participation observed in the early 2000s has since diverged by mode of participation, with consistent growth observed in nature sensing, but a decline seen in crowdsourcing and distributed computing. Most citizen science projects, except for nature sensing, are heavily dominated by men, and the vast majority of participants, male and female, have a background in science. The analysis we present here provides, for the first time, a robust 'baseline' to describe global trends in online citizen science participation. These results highlight current challenges and the future potential of citizen science. Beyond presenting our analysis of the collated data, our work identifies multiple metrics for robust examination of public participation in science and, more generally, online crowds. It also points to the limits of quantitative studies in capturing the personal, societal, and historical significance of citizen science.