Takshan/R1 huggingface dataset:
Video capsule endoscopy in pediatric patients with Crohn's disease: a single-center experience of 180 procedures.

Background: Video capsule endoscopy (VCE) is a noninvasive method enabling excellent visualization of the small bowel (SB) mucosa. The aim of this study was to examine the impact and safety of VCE performed in children and adolescents with suspected or established Crohn's disease (CD). Methods: A total of 180 VCE examinations in 169 consecutive patients conducted in 2003-14 in a single center were retrospectively analyzed. The median age was 13 years (range 3-17 years) and indications for VCE were suspected (125 cases, 69%) and established (55 cases, 31%) CD. VCE was performed with a PillCam SB (Given Imaging, Yokneam, Israel) VCE system with 8-12 h of registration without bowel preparation. Results: A total of 154 of 180 (86%) patients swallowed the capsule and 26 (14%) had the capsule endoscopically placed in the duodenum. Patency capsule examination was performed in 71 cases prior to VCE to exclude SB obstruction. VCE detected findings consistent with SB CD in 71 (40%) examinations and 17 (9%) procedures showed minor changes not diagnostic for CD. A total of 92 (51%) examinations displayed normal SB mucosa. The capsule did not reach the colon within the recording time in 30 (17%) procedures and were defined as incomplete examinations. A change in diagnosis or therapy was recommended in 56 (31%) patients based on VCE results. Capsule retention occurred in one patient. Conclusions: VCE is a safe method in children with suspected or established CD. VCE often leads to a definitive diagnosis and has a significant impact on the clinical management of pediatric patients with CD.
Rising global burden of breast cancer: the case of sub-Saharan Africa (with emphasis on Nigeria) and implications for regional development: a review.

BACKGROUND: Despite mortality from breast cancer in Africa being higher than in high income countries, breast cancer has not been extensively studied in the region. The aim of this paper was to highlight the rising burden of breast cancer with an emphasis on sub-Saharan Africa as well as trends, characteristics, controversies and their implications for regional development. METHODOLOGY: A review of published studies and documents was conducted in Medline, Scopus, Pubmed and Google using combinations of key words-breast neoplasm, breast cancer, cancer, incidence, mortality, Africa, Nigeria. Graphical and frequency analyses were carried out on some of the incidence and mortality figures retrieved from published papers and the GLOBOCAN website. FINDINGS: Globally, about 25% and 15% of all new cancer cases and cancer deaths respectively among females were due to breast cancer. Africa currently had the highest age-standardized breast cancer mortality rate globally, with the highest incidence rates being recorded within the sub-Saharan African sub-region. Incidence trends such as inherently aggressive tumour and younger age profile had been subject to controversies. Certain factors such as westernized diet, urbanization and possibly increasing awareness had been implicated, though their specific contributions were yet to be fully established. CONCLUSION: Unless urgent action is taken, breast cancer will compound sub-Saharan Africa's disease burden, increase poverty and gender inequality as well as reverse the current global gains against maternal and neonatal mortality.
Association between afterhours admission to the intensive care unit, strained capacity, and mortality: a retrospective cohort study.

BACKGROUND: Admission to the intensive care unit (ICU) outside daytime hours has been shown to be variably associated with increased morbidity and mortality. We aimed to describe the characteristics and outcomes of patients admitted to the ICU afterhours (22:00-06:59 h) in a large Canadian health region. We further hypothesized that the association between afterhours admission and mortality would be modified by indicators of strained ICU capacity. METHODS: This is a population-based cohort study of 12,265 adults admitted to nine ICUs in Alberta from June 2012 to December 2014. We used a path-analysis modeling strategy and mixed-effects multivariate regression analysis to evaluate direct and integrated associations (mediated through Acute Physiology and Chronic Health Evaluation (APACHE) II score) between afterhours admission (22:00-06:59 h) and ICU mortality. Further analysis examined the effects of strained ICU capacity and varied definitions of afterhours and weekend admissions. ICU occupancy ≥ 90% or clustering of admissions (≥ 0.15, defined as number of admissions 2 h before or after the index admission, divided by the number of ICU beds) were used as indicators of strained capacity. RESULTS: Of 12,265 admissions, 34.7% (n = 4251) occurred afterhours. The proportion of afterhours admissions varied amongst ICUs (range 26.7-37.8%). Patients admitted afterhours were younger (median (IQR) 58 (44-70) vs 60 (47-70) years, p < 0.0001), more likely to have a medical diagnosis (75.9% vs 72.1%, p < 0.0001), and had higher APACHE II scores (20.9 (8.6) vs 19.9 (8.3), p < 0.0001). Crude ICU mortality was greater for those admitted afterhours (15.9% vs 14.1%, p = 0.007), but following multivariate adjustment there was no direct or integrated effect on ICU mortality (odds ratio (OR) 1.024; 95% confidence interval (CI) 0.923-1.135, p = 0.658). Furthermore, direct and integrated analysis showed no association of afterhours admission and hospital mortality (p = 0.90) or hospital length of stay (LOS) (p = 0.27), although ICU LOS was shorter (p = 0.049). Early-morning admission (00:00-06:59 h) with ICU occupancy ≥ 90% was associated with short-term (≤ 7 days) and all-cause ICU mortality. CONCLUSIONS: One-third of critically ill patients are admitted to the ICU afterhours. Afterhours ICU admission was not associated with greater mortality risk in most circumstances but was sensitive to strained ICU capacity.
Summarizing performance for genome scale measurement of miRNA: reference samples and metrics.

BACKGROUND: The potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we evaluated the utility of a set of total RNA samples, designed with between-sample differences in the relative abundance of miRNAs, as process controls. RESULTS: Three pure total human RNA samples (brain, liver, and placenta) and two different mixtures of these components were evaluated as measurement assurance control samples on multiple measurement systems at multiple sites and over multiple rounds. In silico modeling of mixtures provided benchmark values for comparison with physical mixtures. Biomarker development laboratories using next-generation sequencing (NGS) or genome-scale hybridization assays participated in the study and returned data from the samples using their routine workflows. Multiplexed and single assay reverse-transcription PCR (RT-PCR) was used to confirm in silico predicted sample differences. Data visualizations and summary metrics for genome-scale miRNA profiling assessment were developed using this dataset, and a range of performance was observed. These metrics have been incorporated into an online data analysis pipeline and provide a convenient dashboard view of results from experiments following the described design. The website also serves as a repository for the accumulation of performance values providing new participants in the project an opportunity to learn what may be achievable with similar measurement processes. CONCLUSIONS: The set of reference samples used in this study provides benchmark values suitable for assessing genome-scale miRNA profiling processes. Incorporation of these metrics into an online resource allows laboratories to periodically evaluate their performance and assess any changes introduced into their measurement process.
Using mixtures of biological samples as process controls for RNA-sequencing experiments.

BACKGROUND: Genome-scale "-omics" measurements are challenging to benchmark due to the enormous variety of unique biological molecules involved. Mixtures of previously-characterized samples can be used to benchmark repeatability and reproducibility using component proportions as truth for the measurement. We describe and evaluate experiments characterizing the performance of RNA-sequencing (RNA-Seq) measurements, and discuss cases where mixtures can serve as effective process controls. RESULTS: We apply a linear model to total RNA mixture samples in RNA-seq experiments. This model provides a context for performance benchmarking. The parameters of the model fit to experimental results can be evaluated to assess bias and variability of the measurement of a mixture. A linear model describes the behavior of mixture expression measures and provides a context for performance benchmarking. Residuals from fitting the model to experimental data can be used as a metric for evaluating the effect that an individual step in an experimental process has on the linear response function and precision of the underlying measurement while identifying signals affected by interference from other sources. Effective benchmarking requires well-defined mixtures, which for RNA-Seq requires knowledge of the post-enrichment 'target RNA' content of the individual total RNA components. We demonstrate and evaluate an experimental method suitable for use in genome-scale process control and lay out a method utilizing spike-in controls to determine enriched RNA content of total RNA in samples. CONCLUSIONS: Genome-scale process controls can be derived from mixtures. These controls relate prior knowledge of individual components to a complex mixture, allowing assessment of measurement performance. The target RNA fraction accounts for differential selection of RNA out of variable total RNA samples. Spike-in controls can be utilized to measure this relationship between target RNA content and input total RNA. Our mixture analysis method also enables estimation of the proportions of an unknown mixture, even when component-specific markers are not previously known, whenever pure components are measured alongside the mixture.
Predictive ability of genomic selection models in a multi-population perennial ryegrass training set using genotyping-by-sequencing.

KEY MESSAGE: Genomic prediction models for multi-year dry matter yield, via genotyping-by-sequencing in a composite training set, demonstrate potential for genetic gain improvement through within-half sibling family selection. Perennial ryegrass (Lolium perenne L.) is a key source of nutrition for ruminant livestock in temperate environments worldwide. Higher seasonal and annual yield of herbage dry matter (DMY) is a principal breeding objective but the historical realised rate of genetic gain for DMY is modest. Genomic selection was investigated as a tool to enhance the rate of genetic gain. Genotyping-by-sequencing (GBS) was undertaken in a multi-population (MP) training set of five populations, phenotyped as half-sibling (HS) families in five environments over 2 years for mean herbage accumulation (HA), a measure of DMY potential. GBS using the ApeKI enzyme yielded 1.02 million single-nucleotide polymorphism (SNP) markers from a training set of n = 517. MP-based genomic prediction models for HA were effective in all five populations, cross-validation-predictive ability (PA) ranging from 0.07 to 0.43, by trait and target population, and 0.40-0.52 for days-to-heading. Best linear unbiased predictor (BLUP)-based prediction methods, including GBLUP with either a standard or a recently developed (KGD) relatedness estimation, were marginally superior or equal to ridge regression and random forest computational approaches. PA was principally an outcome of SNP modelling genetic relationships between training and validation sets, which may limit application for long-term genomic selection, due to PA decay. However, simulation using data from the training experiment indicated a twofold increase in genetic gain for HA, when applying a prediction model with moderate PA in a single selection cycle, by combining among-HS family selection, based on phenotype, with within-HS family selection using genomic prediction.
The social biography of antibiotic use in smallholder dairy farms in India.

Background: Antimicrobial resistance (AMR) has been identified as one of the major threats to global health, food security and development today. While there has been considerable attention about the use and misuse of antibiotics amongst human populations in both research and policy environments, there is no definitive estimate of the extent of misuse of antibiotics in the veterinary sector and its contribution to AMR in humans. In this study, we explored the drivers ofirrational usage of verterinary antibiotics in the dairy farming sector in peri-urban India. Methods and materials: The study was conducted in the peri-urban belts of Ludhiana, Guwahati and Bangalore. A total of 54 interviews (formal and non-formal) were carried out across these three sites. Theme guides were developed to explore different drivers of veterinary antimicrobial use. Data was audio recorded and transcribed. Analysis of the coded data set was carried out using AtlasTi. Version 7. Themes emerged inductively from the set of codes. Results: Findings were presented based on concept of 'levels of analyses'. Emergent themes were categorised as individual, health systems, and policy level drivers. Low level of knowledge related to antibiotics among farmers, active informal service providers, direct marketing of drugs to the farmers and easily available antibiotics, dispensed without appropriate prescriptions contributed to easy access to antibiotics, and were identified to be the possible drivers contributing to the non-prescribed and self-administered use of antibiotics in the dairy farms. Conclusions: Smallholding dairy farmers operated within very small margins of profits. The paucity of formal veterinary services at the community level, coupled with easy availability of antibiotics and the need to ensure profits and minimise losses, promoted non-prescribed antibiotic consumption. It is essential that these local drivers of irrational antibiotic use are understood in order to develop interventions and policies that seek to reduce antibiotic misuse.
A serious game for children with Attention Deficit Hyperactivity Disorder: Who benefits the most?

OBJECTIVE: The aim of the current study was to identify which subgroups of children with Attention Deficit Hyperactivity Disorder (ADHD) benefitted the most from playing a Serious Game (SG) intervention shown in a randomized trial to improve behavioral outcomes. METHOD: Pre-intervention characteristics [i.e., gender, age, intellectual level of functioning, medication use, computer experience, ADHD subtype, severity of inattention problems, severity of hyperactivity/impulsivity problems, comorbid Oppositional Defiant Disorder (ODD) and Conduct Disorder (CD) symptoms] were explored as potential moderators in a Virtual Twins (VT) analysis to identify subgroups for whom the SG intervention was most effective. Primary outcome measures were parent-reported time management, planning/organizing and cooperation skills. RESULTS: Two subgroups were identified. Girls (n = 26) were identified as the subgroup that was most likely to show greater improvements in planning/organizing skills as compared to the estimated treatment effect of the total group of participants. Furthermore, among the boys, those (n = 47) with lower baseline levels of hyperactivity and higher levels of CD symptoms showed more improvements in their planning/organizing skills when they played the SG intervention as compared to the estimated treatment effect of the total group of participants. CONCLUSION: Using a VT analysis two subgroups of children with ADHD, girls, and boys with both higher levels of CD and lower levels of hyperactivity, were identified. These subgroups mostly benefit from playing the SG intervention developed to improve ADHD related behavioral problems. Our results imply that these subgroups have a higher chance of treatment success.
Early improvement of executive test performance during antidepressant treatment predicts treatment outcome in patients with Major Depressive Disorder.

Executive dysfunctions frequently occur in patients with Major Depressive Disorder and have been shown to improve during effective antidepressant treatment. However, the time course of improvement and its relationship to treatment outcome is unknown. The aim of the study was to assess the test performance and clinical outcome by repetitive assessments of executive test procedures during antidepressant treatment. Executive test performance was assessed in 209 -patients with Major Depressive Disorder (mean age 39.3 ± 11.4 years) and 84 healthy controls five times in biweekly intervals from baseline to week 8. Patients were treated by a defined treatment algorithm within the early medication change study (EMC trial; ClinicalTrials.gov NCT00974155), controls did not receive any intervention. Cognitive domains were processing speed, cognitive flexibility, phonemic and semantic verbal fluency. Intelligence was assessed at baseline. Depression severity was tested once a week by the Hamilton Depression Rating Scale (HAMD17). 130 patients (62%) showed executive dysfunctions in at least one of four tests at baseline. Linear mixed regression models revealed that the course of depression severity was associated to the course of cognitive flexibility (p = 0.004) and semantic verbal fluency (p = 0.020). Cognitive flexibility and semantic verbal fluency may be candidates easily to apply for therapy response prediction in clinical routine, which should be tested in further prospective studies. TRIAL REGISTRATION: ClinicalTrials.gov NCT00974155 EudraCT: 2008-008280-96.
Cancer-related information needs and treatment decision-making experiences of people with dementia in England: a multiple perspective qualitative study.

OBJECTIVES: Little is known about the cancer experience and support needs of people with dementia. In particular, no evidence currently exists to demonstrate the likely complex decision-making processes for this patient group and the oncology healthcare professionals (HCP) involved in their care. The aim of this study was to explore the cancer-related information needs and decision-making experiences of patients with cancer and comorbid dementia, their informal caregivers and oncology HCPs. DESIGN: Cross-sectional qualitative study. Semistructured interviews were conducted face to face with participants. Interviews were audio recorded and transcribed prior to thematic analysis. SETTING: Patients with a diagnosis of cancer and dementia, their informal caregivers and oncology HCPs involved in their care, all recruited from a regional treatment cancer centre. PARTICIPANTS: Purposeful sample of 10 patients with a diagnosis of cancer-dementia, informal caregivers (n=9) and oncology HCPs (n=12). RESULTS: Four themes were identified: (1) leading to the initial consultation-HCPs require more detailed information on the functional impact of dementia and how it may influence cancer treatment options prior to meeting the patient; (2) communicating clinically relevant information-informal caregivers are relied on to provide patient information, advocate for the patient and support decision-making; (3) adjustments to cancer care-patients with dementia get through treatment with the help of their family and (4) following completion of cancer treatment-there are continuing information needs. Oncology HCPs discussed their need to consult specialists in dementia care to support treatment decision-making. CONCLUSIONS: Although patients with cancer-dementia are involved in their treatment decision-making, informal caregivers are generally crucial in supporting this process. Individual patient needs and circumstances related to their cancer must be considered in the context of dementia prognosis highlighting complexities of decision-making in this population. Oncology teams should strive to involve healthcare staff with dementia expertise as early as possible in the cancer pathway.
Calibration plots for risk prediction models in the presence of competing risks.

A predicted risk of 17% can be called reliable if it can be expected that the event will occur to about 17 of 100 patients who all received a predicted risk of 17%. Statistical models can predict the absolute risk of an event such as cardiovascular death in the presence of competing risks such as death due to other causes. For personalized medicine and patient counseling, it is necessary to check that the model is calibrated in the sense that it provides reliable predictions for all subjects. There are three often encountered practical problems when the aim is to display or test if a risk prediction model is well calibrated. The first is lack of independent validation data, the second is right censoring, and the third is that when the risk scale is continuous, the estimation problem is as difficult as density estimation. To deal with these problems, we propose to estimate calibration curves for competing risks models based on jackknife pseudo-values that are combined with a nearest neighborhood smoother and a cross-validation approach to deal with all three problems.
The association between mental health nursing and hospital admissions for people with serious mental illness: a protocol for a systematic review.

BACKGROUND: Relapse in individuals with severe mental illness (SMI) is a frequent occurrence and can add considerably to the burden of disease. As such, relapse prevention is an essential therapeutic outcome for people with SMI. Mental health nurses (MHNs) are well placed to support individuals with SMI and to prevent relapse; notwithstanding, there has been no synthesis of the evidence to date to determine whether MHNs prevent relapse in this population. METHODS: Electronic databases will be systemically searched for observational studies and clinical trials that report the association between mental health nursing and the hospitalisation of persons living with an SMI. The search will be supplemented by reference checking and a search of the grey literature. The primary outcome of interest will be hospital admission rate. Screening of articles, data extraction and critical appraisal will be undertaken by two reviewers, independently, with a third reviewer consulted should disagreement occur between reviewers. The quality of studies will be assessed using the Risk Of Bias In Non-randomised Studies - of Interventions (ROBINS-I) tool and the Cochrane Collaboration risk of bias tool. Depending on the number of studies and level of heterogeneity, the evidence may be synthesised using meta-analysis or narrative synthesis. DISCUSSION: This review will explore for the first time the clinical potential of mental health nursing in preventing relapse in persons with SMI. The findings of this review will serve to inform future research and education in this area. The evidence may also help inform future policy, including decisions regarding future mental health workforce development and planning. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42017058694 .