Dyslipidemia in Juvenile Dermatomyositis.

This study investigates the prevalence of dyslipidemia and its association with disease activity in children with Juvenile Dermatomyositis (JDM). A retrospective chart review of 142 JDM patients who had fasting lipid profiles was conducted. Clinical, and laboratory indicators of disease activity at the time of lipid assessment were obtained. JDM patients displayed a high prevalence (72%) of abnormal or borderline fasting lipid profiles, particularly involving HDL and triglycerides. Treatment-naïve patients exhibited the most significant dyslipidemia, with significantly lower median HDL levels compared to those on medication (30 vs. 49 mg/dL, p < 0.0001). HDL levels inversely correlated with various disease activity measures, including disease activity score (DAS) total (r= -0.38, p < 0.001), DAS muscle weakness (r= -0.5, p < 0.001), DAS skin (r= -0.25, p = 0.003), neopterin (r= -0.41, p < 0.001), ESR (r= -0.25, p = 0.006), and vWF Ag (r= -0.21, p = 0.02). In conclusion, JDM patients have a high prevalence of dyslipidemia, especially low HDL and elevated triglycerides. The severity of dyslipidemia (low HDL) correlates with disease activity, with treatment-naïve patients demonstrating the lowest HDL levels. These findings suggest the importance of annual lipid profile monitoring in JDM patients, potentially followed by early interventions such as dietary adjustments and exercise programs.

Effects of Housing Systems on Production Performance, Egg Quality, Tonic Immobility and Feather Score in Laying Hens.

BACKGROUND: This study was designed to investigate the effects of different housing systems on production performance, egg quality and welfare in laying hens. METHODS: One hundred and twenty 42-week-old "Atak S" laying hens, purchased from a manufacturing company, were randomly assigned to 4 housing systems: conventional cages, furnished cages, deep-litter system and free-range. Each system housed 30 hens, which were kept in these systems for 6 weeks. Parameters regarding production performance, egg quality, plumage condition scores and tonic immobility were assessed at the end of the housing period. RESULTS: Egg production and egg mass were lower in cage-free rearing systems than in caged systems. Mean egg weight in free-range hens, and albumen height and Haugh unit in deep-litter hens, were lower than in other housing systems. Eggshell weight in hens housed in furnished cages was greater than in free-range hens, while eggshell strength was better compared to that of hens in conventional cages. The housing system did not impact fearfulness; however, the deep-litter housing increased the sensitivity to touch or capture. Whole body and regional plumage condition scores of free-range hens elicited more favourable results than those kept in conventional cages. Because the plumage condition indicates welfare, the results proved the superiority of free-range over conventional rearing regarding welfare. CONCLUSIONS: Concerning the parameters, such as egg production, animal welfare and fear level, overall data revealed the pros and cons of all housing systems investigated. We consider that this study's findings might contribute to the researchers and breeders seeking alternative housing for laying hens.

Latent Variable Forests for Latent Variable Score Estimation.

We develop a latent variable forest (LV Forest) algorithm for the estimation of latent variable scores with one or more latent variables. LV Forest estimates unbiased latent variable scores based on confirmatory factor analysis (CFA) models with ordinal and/or numerical response variables. Through parametric model restrictions paired with a nonparametric tree-based machine learning approach, LV Forest estimates latent variable scores using models that are unbiased with respect to relevant subgroups in the population. This way, estimated latent variable scores are interpretable with respect to systematic influences of covariates without being biased by these variables. By building a tree ensemble, LV Forest takes parameter heterogeneity in latent variable modeling into account to capture subgroups with both good model fit and stable parameter estimates. We apply LV Forest to simulated data with heterogeneous model parameters as well as to real large-scale survey data. We show that LV Forest improves the accuracy of score estimation if parameter heterogeneity is present.

Particulates Matter: The Influence of Cumulative Local Air Pollution Exposure on Sixth-Grade Academic Achievement in California.

We examine the influence of exposure to fine particulate matter (PM 2.5) in ambient air over the previous 6 years on the average standardized test score performance in math, English language arts (ELA), and overall for sixth graders at a sample of California public school districts from 2015 through 2018. Public health research suggests that children exposed to localized air pollution may suffer from cognitive impairment during testing or chronic conditions such as asthma that could influence their academic performance. After controlling for the appropriate confounding variables, our findings indicate that a 1-unit increase (or an equivalent one-third increase in the standard deviation) in the average amount of particulate matter observed over the past 6 years in a school district reduces the average standardized test score by about 4%. In addition, a typical student in a California school district in the two highest quintiles of PM 2.5 exposure (controlling for other causal factors) exhibits standardized test scores closer to the fifth-grade equivalency level than the sixth. These results support the benefits of indoor air pollution mitigation as a likely cost-effective intervention to improve student academic success in primary school.

Why was the study done? Previous researchers found that local air pollution impacts children's development, health, and learning ability and that exposure to fine particulate matter (PM 2.5) in ambient air can harm performance on standardized tests. This paper offers a novel approach by estimating the cumulative impact of average district-wide PM 2.5 exposure over the previous 6 years on California sixth graders' math, English, and overall test scores. What did the researchers do? Our model connects average test scores from California public school districts to PM 2.5 concentrations measured by Census tract within the district. We include district demographic, socioeconomic, and geographic data to increase confidence that the effect is causal and minimize bias from variables correlated with PM 2.5. Data from multiple years enables the detection of long-term effects and allows us to control for district and year-specific effects. We also test the robustness of our findings to adjusted model designs and compare the effect size to prior studies. What did the researchers find? We find that an average school district in California that experiences a 1-unit increase in PM 2.5 concentration, holding other control variables constant, could expect overall grade equivalency for sixth graders to fall by about 4%. Dividing PM 2.5 exposure into five sequential levels, we find an increasingly negative effect that levels off when moving from the lowest to the highest levels. This cumulative effect is larger than prior measures of PM 2.5 impacts only on test day or over the school year. What do the findings mean? California's primary school students have likely experienced a drop in standardized test score performance from sustained exposure to fine particulate matter. The effect size warrants policy consideration, as some paths to pollution mitigation (such as air filters in classrooms) may produce equitable and cost-effective test score gains.

Failure rate of D-dimer testing in patients with high clinical probability of pulmonary embolism: Ancillary analysis of three European studies.

BACKGROUND: In patients with a high clinical probability of pulmonary embolism (PE), the high prevalence can lower the D-dimer negative predictive value and increase the risk of diagnostic failure. It is therefore recommended that these high-risk patients should undergo chest imaging without D-dimer testing although no evidence supports this recommendation. OBJECTIVE: The objective was to evaluate the safety of ruling out PE based on D-dimer testing among patients with a high clinical probability of PE. METHODS: This was a post hoc analysis of three European studies (PROPER, MODIGLIANI, and TRYSPEED). Patients were included if they presented a high clinical probability of PE (according to either the Wells or the revised Geneva score) and underwent D-dimer testing. The D-dimer-based strategy ruled out PE if the D-dimer level was below the age-adjusted threshold (i.e., <500 ng/mL in patients aged less than 50 and age × 10 ng/mL in patients older than 50). The primary endpoint was a thromboembolic event in patients with negative D-dimer either at index visit or at 3-month follow-up. A Bayesian approach estimated the probability that the failure rate of the D-dimer-based strategy was below 2% given observed data. RESULTS: Among the 12,300 patients included in the PROPER, MODIGLIANI, and TRYSPEED studies, 651 patients (median age 68 years, 60% female) had D-dimer testing and a high clinical probability of PE and were included in the study. PE prevalence was 31.3%. Seventy patients had D-dimer levels under the age-adjusted threshold, and none of them had a PE after follow-up (failure rate 0.0% [95% CI 0.0%-6.5%]). Bayesian analysis reported a credible interval of 0.0%-4.1%, with a 76.2% posterior probability of a failure rate below 2%. CONCLUSIONS: In this study, ruling out PE in high-risk patients based on D-dimer below the age-adjusted threshold was safe, with no missed PE. However, the large CI of the primary endpoint precludes a definitive conclusion.

Family income and polygenic scores are independently but not interactively associated with cognitive performance among youth genetically similar to European reference populations.

Cognitive abilities are heritable and influenced by socioeconomic status (SES). It is critical to understand the association between SES and cognition beyond genetic propensity to inform potential benefits of SES-based interventions and to determine if such associations vary across (i) cognitive domains, (ii) facets of SES, and/or (iii) genetic propensity for different aspects of cognition. We examined the contributions of neighborhood socioeconomic advantage, family income, and polygenic scores (PGS) for domains of cognition (i.e., general cognitive ability, executive function, learning and memory, fluid reasoning) in a sample of children (ages 9-10; n = 5549) most genetically similar to reference populations from Europe. With some variability across cognitive outcomes, family income and PGS were independently significantly associated with cognitive performance. Within-sibling analyses revealed that cognitive PGS associations were predominantly driven by between-family effects suggestive of non-direct genetic mechanisms. These findings provide evidence that SES and genetic propensity to cognition have unique associations with cognitive performance in middle childhood. These results underscore the importance of environmental factors and genetic influences in the development of cognitive abilities and caution against overinterpreting associations with PGS of cognitive and educational outcomes as predominantly direct genetic effects.

Influence of Diabetes Mellitus on Neurological Recovery in Older Patients With Cervical Spinal Cord Injury Without Bone Injury: A Retrospective Multicenter Study.

STUDY DESIGN: Retrospective study. OBJECTIVES: To investigate the impact of diabetes mellitus on neurological recovery and determine the relationship between moderate-severe diabetes and neurological recovery in patients with cervical spinal cord injury (CSCI) without bone injury. METHODS: A retrospective study was conducted on 389 consecutive patients aged ≥65 years with CSCI without bone injury across 33 medical institutes. The patients were divided into a nondiabetic group (n = 270) and a diabetic group (n = 119). Neurological outcomes were compared between the two groups through propensity score matching. The impact of moderate-severe diabetes (defined as hemoglobin A1c ≥ 7.0% or requiring insulin treatment) on neurological recovery was evaluated through multiple linear regression analysis. RESULTS: Propensity score matching revealed no significant differences between the diabetic and nondiabetic groups in terms of American Spinal Injury Association (ASIA) impairment scale grade and mean total ASIA motor scores (AMS) at 6 months post-injury. Multiple linear regression analysis indicated that age on admission (B = -0.34; 95% confidence interval [CI], -0.59 to -0.08; P = 0.01), dementia (B = -16.50; 95% CI, -24.99 to -8.01; P < 0.01), and baseline total AMS (B = -0.62; 95% CI, -0.72 to -0.51; P < 0.01) were negative predictors of neurological recovery at 6 months post-injury. The presence of moderate-severe diabetes did not influence neurological recovery at 6 months post-injury. CONCLUSIONS: Diabetic patients with CSCI without bone injury achieved improvements in neurological function comparable to those of nondiabetic patients. Moderate-severe diabetes did not affect neurological recovery in patients with CSCI without bone injury.

Causal relationships between diseases mined from the literature improve the use of polygenic risk scores.

MOTIVATION: Identifying causal relations between diseases allows for the study of shared pathways, biological mechanisms, and inter-disease risks. Such causal relations can facilitate the identification of potential disease precursors and candidates for drug re-purposing. However, computational methods often lack access to these causal relations. Few approaches have been developed to automatically extract causal relationships between diseases from unstructured text, but they are often only focused on a small number of diseases, lack validation of the extracted causal relations, or do not make their data available. RESULTS: We automatically mined statements asserting a causal relation between diseases from the scientific literature by leveraging lexical patterns. Following automated mining of causal relations, we mapped the diseases to the International Classification of Diseases (ICD) identifiers to allow the direct application to clinical data. We provide quantitative and qualitative measures to evaluate the mined causal relations and compare to UK Biobank (UKB) diagnosis data as a completely independent data source. The validated causal associations were used to create a directed acyclic graph that can be used by causal inference frameworks. We demonstrate the utility of our causal network by performing causal inference using the do-calculus, using relations within the graph to construct and improve polygenic risk scores, and disentangle the pleiotropic effects of variants. AVAILABILITY AND IMPLEMENTATION: The data is available through https://github.com/bio-ontology-research-group/causal-relations-between-diseases. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Impact of deceased-donor characteristics on early graft function: outcome of kidney donor pairs accepted for transplantation.

Introduction: The impact of deceased donor characteristics on kidney transplant outcomes is controversial. Correspondingly, the predictive performance of deceased donor scores remains moderate, and many transplant centers lack validated criteria for graft acceptance decisions. To better dissect donor-related risk from recipient and periprocedural variables, we analyzed outcomes of kidney donor pairs transplanted in different individuals. Methods: This study explored (a)symmetry of early outcomes of 328 cadaveric kidney transplant recipients from 164 donor pairs transplanted at three Eurotransplant centers. The primary discriminatory factor was (a)symmetry of partner graft function, defined as early graft loss or impaired graft function [estimated glomerular filtration rate (eGFR) <30 mL/min] 3 months after transplantation. We reasoned that a relevant impact of donor factors would result in a high concordance rate of limited graft function or failure. Results: The observed number of symmetric graft failure after transplantation was less than statistically expected (3 months: 1 versus 2, p = 0.89; and 12 months: 3 versus 5, p = 0.26). However, we found a trend toward an impaired 5-year graft survival of grafts with good function 3 months after transplantation but a failed or impaired partner graft compared to symmetrically well-functioning grafts (p = 0.09). Subsequently, we explored the impact of individual donor and recipient variables on early transplant outcomes. Generalized estimating equations after feature selection with LassoGEE bootstrap selected donor age, donor body mass index, and donor eGFR as the relevant risk factors. Discussion: Our findings indicate that donor factors impact early outcomes in kidney transplantation but may have a limited role in long-term graft survival, once a graft has been accepted for transplantation. Utilizing donor-based clinical scores has the potential to aid clinicians in acceptance decisions, giving them an estimate of individual posttransplant outcomes. However, the ultimate decision for acceptance should rest with clinicians, who must consider the complex interplay of donor factors, as well as recipient and periprocedural characteristics.

Characterization and Z-score Calculation of Cardiac MRI parameters in patients after the Fontan operation. A Fontan Outcome Registry using CMR Examinations (FORCE) study.

BACKGROUND: Cardiac magnetic resonance (CMR) offers valuable hemodynamic insights post-Fontan, but is limited by the absence of normative single ventricle data. The Fontan Outcomes Registry using CMR Examinations (FORCE) is a large international Fontan-specific CMR registry. This study used FORCE registry data to evaluate expected CMR ventricular size/function and create Fontan-specific z-scores adjusting for ventricular morphology (VM) in healthier Fontan patients. METHODS: "Healthier" Fontan patients were defined as patients free of adverse outcomes, who are New York Heart Association Class I, have mild or less valve disease, and <30% aortopulmonary collateral burden. General linear modeling was performed on 70% of the dataset to create z-scores for volumes and function. Models were tested using the remainder (30%) of the data. The z-scores were compared between children and adults. The z-scores were also compared between "healthier" Fontan and patients with adverse outcomes (death, listing for transplantation or multiorgan disease). RESULTS: The "healthier" Fontan population included 885 patients (15.0 ± 7.6 years) from 18 institutions with 1,156 CMR examinations. Patients with left ventricle morphology had lower volume, mass and higher ejection fraction (EF) compared to right or mixed (two-ventricles) morphology (p<0.001 for all pairwise comparisons). Gender, BSA and VM were used in z-scores. Of the "healthier" Fontan patients, 647 were children <18 years and 238 were adults. Adults had lower ascending aorta flow (2.9 ± 0.7 vs 3.3 ± 0.8L/min/m2, p<0.001) and ascending aorta flow z-scores (-0.16 ± 1.23 vs 0.05 ± 0.95, 0.02) compared to children. Additionally, there were 1595 patients with adverse outcomes who were older (16.1 ± 9.3 vs 15.0 ± 7.6, p<0.001) and less likely to have LV morphology (35 vs 47%, p<0.001). Patients with adverse outcomes had higher z-scores for ventricular volume and mass and lower z-scores for EF and ascending aorta flow compared to the "healthier" Fontan cohort. CONCLUSION: This is the first study to generate CMR z-scores post-Fontan. Importantly the z-scores were generated and tested in "healthier" Fontan patients and both pediatric and adult Fontan patients. These equations may improve CMR-based risk stratification after the Fontan operation.

Enhancing causal inference in population-based neuroimaging data in children and adolescents.

Recent years have seen the increasing availability of large, population-based, longitudinal neuroimaging datasets, providing unprecedented capacity to examine brain-behavior relationships in the neurodevelopmental context. However, the ability of these datasets to deliver causal insights into brain-behavior relationships relies on the application of purpose-built analysis methods to counter the biases that otherwise preclude causal inference from observational data. Here we introduce these approaches (i.e., propensity score-based methods, the 'G-methods', targeted maximum likelihood estimation, and causal mediation analysis) and conduct a review to determine the extent to which they have been applied thus far in the field of developmental cognitive neuroscience. We identify just eight relevant studies, most of which employ propensity score-based methods. Many approaches are entirely absent from the literature, particularly those that promote causal inference in settings with complex, multi-wave data and repeated neuroimaging assessments. Causality is central to an etiological understanding of the relationship between the brain and behavior, as well as for identifying targets for prevention and intervention. Careful application of methods for causal inference may help the field of developmental cognitive neuroscience approach these goals.

Workup and Management of Premenopausal Osteoporosis.

The diagnosis and management of premenopausal low bone mass or osteoporosis is challenging as its relationship to low bone mass and risk of fracture is less defined. Premenopausal or perimenopausal women with low bone density or a history of fragility fractures should undergo a thorough evaluation of causes that predispose them to bone loss. Identification of these underlying risk factors such as estrogen deficiency or malabsorptive disorders offers a treatment strategy to reverse bone loss. This is a review of the diagnostic approach and subsequent management strategies of premenopausal low bone mass or osteoporosis.

The Utility of Immuno-Nutritional Scores in Patients with Testicular Germ Cell Tumors.

BACKGROUND: Hemoglobin, Albumin, Lymphocyte, and Platelet Score (HALP) is an accessible score that is easily reproducible from routine laboratory testing while also reflecting patients' immune-nutritional status. Along with other immuno-nutritional scores, such as the Prognostic Nutrition Index (PNI), HALP has been associated with a number of clinical and pathological features. The goal of our study was to evaluate the prognostic utility of HALP and PNI scores in testicular germ cell cancer (GCT) patients. METHODS: This case-only study included 203 testicular GCT patients who were classified according to the disease stage and HALP and PNI cut-offs. Complete blood count and albumin concentration were routinely determined. RESULTS: The values of HALP and PNI significantly differed among different clinical stages (p < 0.05). Moreover, they clearly exposed a significantly higher risk of advanced clinical stage development for those testicular GCT patients with lower values of HALP and PNI (p < 0.05). Finally, lower score levels were associated with larger tumor size (p < 0.05). CONCLUSION: Our investigation could provide evidence that specific immune-nutritional scores can help distinguish individuals diagnosed with testicular GCT who are more likely to be identified with advanced disease stages.

Timing of food pieces introduction and neurodevelopment: findings from a nationwide birth cohort.

BACKGROUND: While complementary feeding can be challenging, little emphasis has been placed on the introduction to food texture/pieces, especially in terms of neurodevelopmental outcomes. This study aims to determine the association between the timing of introduction to food pieces during infancy and neurodevelopment in early childhood. We hypothesized that late introduction to food texture/pieces relates to unfavorable neurodevelopmental outcomes. METHODS: Families (n = 18329) were recruited from the general population during the nationwide ELFE (Étude Longitudinale Française depuis l'Enfance) birth cohort in France, and 8511 were selected for a complete case analysis. Age at introduction to food pieces was determined based on repeated assessments during the first year. A range of neurodevelopmental outcomes among children were assessed using validated instruments, i.e. composite scores at 1 and 3.5 years, and a score for language acquisition at 2 years. Risk for developmental delay at 3.5 years was defined based on a developmental quotient (DQ) below 90 according to the child's chronological age and the respective composite score at this age. We used linear regression modelling to evaluate associations between age at introduction to food pieces and the standardised neurodevelopmental scores, while logistic regression models were used in the analyses according to the risk for developmental delay. RESULTS: Our findings highlight consistent associations between late introduction to food pieces (i.e., after 10 months, compared to early (before 8 months)) and lower estimates of standardised neurodevelopmental scores at ages 1, 2 and 3.5 years (-0.35 [-0.40; -0.30], -0.15 [-0.20; -0.10] and - 0.18 [-0.23; -0.13], respectively). Infants introduced to pieces late were also more likely to be at risk for developmental delay according to DQ < 90 (OR [95%CI] = 1.62 [1.36; 1.94]). CONCLUSIONS: This study shows that late introduction to food pieces (> 10 months) is related to lower neurodevelopmental scores. Given the challenges that complementary feeding may pose, concerted efforts are required to enhance our understanding of the sensory aspects of early diets and to ultimately provide guidance.

Prevalence of Major Risk Factors and Assessment of 10-Year Risk for Cardiovascular Diseases Among Adults in Yaoundé, Cameroon: A Cross-Sectional Study.

Objective This study aimed to assess the prevalence of major risk factors for cardiovascular disease and the 10-year cardiovascular risk in an adult population residing in Yaoundé, Cameroon. Methodology We conducted a cross-sectional survey in 10 purposively selected neighbourhoods of Yaoundé, involving one adult per household who consented to participate. We collected data on personal and family history, lifestyle and nutritional habits, anthropometric parameters, and blood pressure, and calculated prevalence rates with 95% CI. Results The study involved 411 participants (172 males) with a median age of 28 years (IQR 23-40 years). Prevalence of CVD risk factors in our study population were family history of heart attack (4.4%; 95% CI 2.8-6.8%), stroke (7.5%; 95% CI 5.3-10.5%), harmful alcohol consumption (40.4%; 95% CI 35.8-45.3%), current smoking (5.1%; 95% CI 3.3-7.7%), second-hand smoking (26.6%; 95% CI 22.6-31.1%), low physical activity (66.4; 95% CI 61.7- 70.8%), inadequate fruit/vegetable intake (36.6%; 95% CI 31.4-42.1%), self-reported anxiety (83.5%; 95% CI 79.6-86.8%) and depression (52.3%; 95% CI 47.4-57.1%), overweight (27.0%, 95% CI 22.9 to 31.5%), obesity (25.1%, 95% CI 21.1 to 29.5%), abdominal obesity (65.9%; 95% CI 61.1-70.2%), excess body fat (46.3%; 95% CI 41.4-51.1%), suspected prehypertension (58.3%; 95% CI 51.1-65%) and hypertension (41.8%; 95% CI 35-48.9%). Furthermore, 40% of overall participants had a moderate-to-high 10-year CVD risk. Independent factors such as a personal history of other chronic diseases and parental history of either diabetes or hypertension combined with behaviours like harmful alcohol consumption and mean blood pressure might significantly influence the cardiovascular risk of our study population Conclusion In Yaoundé, Cameroon, many adults have major risk factors for cardiovascular disease, with nearly one-third of young adults at moderate to high risk of developing CVD within the next decade. Thus, it is crucial to implement targeted interventions to mitigate the risk of CVD.

Are Sum Scores a Great Accomplishment of Psychometrics or Intuitive Test Theory?

Sijtsma, Ellis, and Borsboom (Psychometrika, 89:84-117, 2024. https://doi.org/10.1007/s11336-024-09964-7 ) provide a thoughtful treatment in Psychometrika of the value and properties of sum scores and classical test theory at a depth at which few practicing psychometricians are familiar. In this note, I offer comments on their article from the perspective of evidentiary reasoning.

Benefit of dual bronchodilator therapy on exacerbations in former and current smokers with chronic obstructive pulmonary disease in real-world clinical practice: a multicenter validation study (TOReTO).

BACKGROUND: Dual bronchodilator therapy, consisting of a long-acting beta-agonist (LABA) and a long-acting muscarinic antagonist (LAMA), has proven effective for patients with chronic obstructive pulmonary disease (COPD). However, it remains uncertain whether there are efficacy differences between current and former smokers with COPD. This study aims to explore the effectiveness of LABA/LAMA therapies in both these groups. METHODS: The TOReTO trial assessed lung function, symptoms, health status, the occurrence of exacerbations, clinically significant exacerbations, and the use of LABA/LAMA therapies. These therapies include Tio/Olo, umeclidinium/vilanterol (Umec/Vi), and umeclidinium/vilanterol (Umec/Vi) are used in patients with COPD. The study examined the differences in outcomes between current and former smokers. To balance the baseline characteristics, propensity score matching (PSM) was employed. RESULTS: Data from 967 patients were collected. After PSM, the time to the first acute exacerbation in current smokers was analyzed separately for the three treatment groups and was significantly different between them (p = 0.0457). Among, there are differences in the occurrence of acute exacerbation between treatment and smoking status in Umec/Vi (p = 0.0114). There is no significant difference in the treatment of former smokers among the three different groups of LABA/LAMA fixed-dose combinations (p = 0.3079). COPD-related symptoms remained stable throughout the treatment period. There were no significant differences in symptom scores, including CAT and mMRC, among the three groups at the end of the study. CONCLUSIONS: The three fixed-dose combinations of LABA/LAMA showed no difference in reducing exacerbations in former smokers but did show differences in current smokers. This trend has clinical significance, and future research will be conducted to control influencing variables to validate this point. However, due to the non-randomized study design, these findings should be interpreted with caution.

Semi-quantitative chemometric models for characterization of mixtures of sugars using infrared spectral data.

Sugars (saccharides) are sweet-tasting carbohydrates that are abundant in foods and play very important roles in living organisms, particularly as sources and stores of energy, and as structural elements in cellular membranes. They are desirable therapeutic targets, as they participate in multiple metabolic processes as fundamental elements. However, the physicochemical characterization of sugars is a challenging task, mostly due to the structural similarity shared by the large diversity of compounds of this family. The need for fast, accurate enough, and cost-effective analytical methods for these substances is of extreme relevance, in particular because of the recently increasing importance of carbohydrates in Medicine and food industry. With this in view, this work focused on the development of chemometric models for semi-quantitative analysis of samples of different types of sugars (glucose, galactose, mannitol, sorbose and fructose) using infrared spectra as data, as an example of application of a novel approach, where the Principal Component Analysis (PCA) score plots are used to estimate the composition (weight-%) of the mixtures of the sugars. In these plots, polygonal geometric shapes emerge in the vectorial space of the most significant principal components, that allow grouping different types of samples on the vertices, edges, faces and interior of the polygons according to the composition of the samples. This approach was applied successfully to mixtures of up to 5 sugars and shown to appropriately extract the compositional information from the hyper-redundant complex spectral data. Thought the method has been applied here to a specific problem, it shall be considered as a general procedure for the semi-quantitative analysis of other types of mixtures and applicable to other types of data reflecting their composition. In fact, the methodology appears as an efficient tool to solve three main general problems: (i) use hyper-redundant (in variables) data, as spectral information, directly and with minimum pre-treatment, to evaluate semi-quantitatively the composition of mixtures; (ii) do this for systems which produce data that can be considered rather similar; and (iii) do it for a number of substances present in the mixtures that might be greater than that usually considered in chemistry, which in general is limited to 3 components. In addition, this work also demonstrates that, similarly to the developed analysis based on the PCA score plots, the Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS) chemometric method can also be used successfully for the qualitative (when used without any previous knowledge of the components present in the samples) or semi-quantitative (when the pure components spectral profiles are provided as references) analyses of mixtures of (at least) up to 5 distinct sugars.

Cost-effectiveness of population-wide genomic screening for Lynch Syndrome and Polygenic Risk Scores to inform Colorectal Cancer screening.

INTRODUCTION: Genomic screening to identify individuals with Lynch Syndrome (LS) and those with a high polygenic risk score (PRS) promises to personalize Colorectal Cancer (CRC) screening. Understanding its clinical and economic impact is needed to inform screening guidelines and reimbursement policies. METHODS: We developed a Markov model to simulate individuals over a lifetime. We compared LS+PRS genomic screening to standard of care (SOC) for a cohort of US adults at age 30. The Markov model included health states of "no CRC", CRC stages (A-D) and death. We estimated incidence, mortality, and discounted economic outcomes of the population under different interventions. RESULTS: Screening 1000 individuals for LS+PRS resulted in 1.36 fewer CRC cases and 0.65 fewer deaths compared to SOC. The incremental cost-effectiveness ratio (ICER) was $124,415 per quality-adjusted life-year (QALY); screening had a 69% probability of being cost-effective using a willingness to pay threshold of $150,000/QALY. Setting the PRS threshold at the 90th percentile of the LS+PRS screening program to define individuals at high risk was most likely to be cost-effective compared to 95th, 85th, and 80th percentiles. CONCLUSION: Population-level LS+PRS screening is marginally cost-effective and a threshold of 90th percentile is more likely to be cost-effective than other thresholds.