Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as asthma endotypes. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies

Causal Bandits without prior knowledge using separating sets

The Causal Bandit is a variant of the classic Bandit problem where an agent must identify the best action in a sequential decision-making process, where the reward distribution of the actions displays a non-trivial dependence structure that is governed by a causal model. All methods proposed for this problem thus far in the literature rely on exact prior knowledge of the full causal. We formulate new causal bandit algorithms that no longer necessarily rely on prior causal knowledge. Instead, they utilize an estimator based on separating sets, which we can find using simple conditional independence tests or causal discovery methods. We show that, for discrete i.i.d. data, this estimator is unbiased, and has variance which is upper bounded by that of the sample mean. We develop algorithms based on Thompson Sampling and UCB for discrete and Gaussian models respectively and show increased performance on simulation data as well as on a bandit drawing from real-world protein signaling data

Clinical prediction models to support the diagnosis of asthma in primary care: a systematic review protocol

Substantial over-diagnosis and under-diagnosis of asthma in adults and children has recently been reported. As asthma is mostly diagnosed in non-specialist settings, a clinical prediction model (CPM) to aid the diagnosis of asthma in primary care may help improve diagnostic accuracy. We aim to systematically identify, describe, compare, and synthesise existing CPMs designed to support the diagnosis of asthma in children and adults presenting with symptoms suggestive of the disease, in primary care settings or equivalent populations. We will systematically search Medline, Embase and CINAHL from 1 January 1990 to present. Any CPM derived for use in a primary care population will be included. Equivalent populations in countries without a developed primary care service will also be included. The probability of asthma diagnosis will be the primary outcome. We will include CPMs designed for use in clinical practice to aid the diagnostic decision making of a healthcare professional during the assessment of an individual with symptoms suggestive of asthma. We will include derivation studies, and external model validation studies. Two reviewers will independently screen titles/abstracts and full texts for eligibility and extract data from included papers. The CHARMS checklist (or PROBAST if available) will be used to assess risk of bias within each study. Results will be summarised by narrative synthesis with meta-analyses completed if possible. This systematic review will provide comprehensive information about existing CPMs for the diagnosis of asthma in primary care and will inform the development of a future diagnostic model.<br/

Asthma Phenotypes in Childhood

INTRODUCTION: Asthma is no longer thought of as a single disease, but rather a collection of varying symptoms expressing different disease patterns. One of the ongoing challenges is understanding the underlying pathophysiological mechanisms that may be responsible for the varying responses to treatment. Areas Covered: This review provides an overview of our current understanding of the asthma phenotype concept in childhood and describes key findings from both conventional and data-driven methods. Expert Commentary: With the vast amounts of data generated from cohorts, there is hope that we can elucidate distinct pathophysiological mechanisms, or endotypes. In return, this would lead to better patient stratification and disease management, thereby providing true personalised medicine

Evolution of IgE responses to multiple allergen components throughout childhood

BACKGROUND: There is a paucity of information about longitudinal patterns of IgE responses to allergenic proteins (components) from multiple sources. OBJECTIVE: To investigate temporal patterns of component-specific IgE responses from infancy to adolescence, and their relationship with allergic diseases. METHODS: In a population-based birth cohort, we measured IgE to 112 components at 6 follow-ups during childhood. We used a Bayesian method to discover cross-sectional sensitization patterns and their longitudinal trajectories, and related these patterns to asthma and rhinitis in adolescence. RESULTS: We identified one sensitization cluster at age one, 3 at age three, 4 at ages five and eight, 5 at age 11, and six at age 16 years. "Broad" cluster was the only cluster present at every follow-up, comprising of components from multiple sources. "Dust mite" cluster formed at age three and remained unchanged to adolescence. At age three, a single-component "Grass" cluster emerged, which at age five absorbed additional grass components and Fel d 1 to form the "Grass/cat" cluster. Two new clusters formed at age 11: "Cat" cluster and "PR-10/profilin" (which divided at age 16 into "PR-10" and "Profilin"). The strongest contemporaneous associate of asthma at age 16 years was sensitization to "Dust mite" cluster (OR [95% CI]: 2.6 [1.2-6.1], P<0.05), but the strongest early-life predictor of subsequent asthma was sensitization to "Grass/cat" cluster (3.5 [1.6-7.4], P<0.01). CONCLUSIONS: We describe the architecture of the evolution of IgE responses to multiple allergen components throughout childhood, which may facilitate development of better diagnostic and prognostic biomarkers for allergic diseases

Joint modeling of parentally reported and physician-confirmed wheeze identifies children with persistent troublesome wheezing

Background Previous studies have suggested the presence of different childhood wheeze phenotypes through statistical modeling based on parentally reported wheezing. Objective We sought to investigate whether joint modeling of observations from both medical records and parental reports helps to more accurately define wheezing disorders during childhood and whether incorporating information from medical records better characterizes severity. Methods In a population-based birth cohort (n = 1184), we analyzed data from 2 sources (parentally reported current wheeze at 4 follow-ups and physician-confirmed wheeze from medical records in each year from birth to age 8 years) to determine classes of children who differ in wheeze trajectories. We tested the validity of these classes by examining their relationships with objective outcomes (lung function, airway hyperreactivity, and atopy), asthma medication, and severe exacerbations. Results Longitudinal latent class modeling identified a 5-class model that best described the data. We assigned classes as follows: no wheezing (53.3%), transient early wheeze (13.7%), late-onset wheeze (16.7%), persistent controlled wheeze (13.1%), and persistent troublesome wheeze (PTW; 3.2%). Longitudinal trajectories of atopy and lung function differed significantly between classes. Patients in the PTW class had diminished lung function and more hyperreactive airways compared with all other classes. We observed striking differences in exacerbations, hospitalizations, and unscheduled visits, all of which were markedly higher in patients in the PTW class compared with those in the other classes. For example, the risk of exacerbation was much higher in patients in the PTW class compared with patients with persistent controlled wheeze (odds ratio [OR], 3.58; 95% CI, 1.27-10.09), late-onset wheeze (OR, 15.92; 95% CI, 5.61-45.15), and transient early wheeze (OR, 12.24; 95% CI, 4.28-35.03). Conclusion We identified a novel group of children with persistent troublesome wheezing, who have markedly different outcomes compared with persistent wheezers with controlled disease

The 2018 Strategic Defence Statement: Ten Different Views from Massey Scholars

To view the Strategic Defence Policy Statement 2018 please go here http://www.nzdf.mil.nz/corporate-documents/strategic-defence-policy-statement-2018.htmfals

Suboptimal geographic accessibility to comprehensive HIV care in the US: regional and urban–rural differences

Achieving US state and municipal benchmarks to end the HIV epidemic and promote health equity requires access to comprehensive HIV care. However, this care may not be geographically accessible for all people living with HIV (PLHIV). We estimated county-level drive time and suboptimal geographic accessibility to HIV care across the contiguous US, assessing regional and urban–rural differences. We integrated publicly available data from four federal databases to identify and geocode sites providing comprehensive HIV care in 2015, defined as the co-located provision of core HIV medical care and support services. Leveraging street network, US Census and HIV surveillance data (2014), we used geographic analysis to estimate the fastest one-way drive time between the population-weighted county centroid and the nearest site providing HIV care for counties reporting at least five diagnosed HIV cases. We summarized HIV care sites, county-level drive time, population-weighted drive time and suboptimal geographic accessibility to HIV care, by US region and county rurality (2013). Geographic accessibility to HIV care was suboptimal if drive time was \u3e30 min, a common threshold for primary care accessibility in the general US population. Tests of statistical significance were not performed, since the analysis is population-based. We identified 671 HIV care sites across the US, with 95% in urban counties. Nationwide, the median county-level drive time to HIV care is 69 min (interquartile range (IQR) 66 min). The median county-level drive time to HIV care for rural counties (90 min, IQR 61) is over twice that of urban counties (40 min, IQR 48), with the greatest urban–rural differences in the West. Nationally, population-weighted drive time, an approximation of individual-level drive time, is over five times longer in rural counties than in urban counties. Geographic access to HIV care is suboptimal for over 170,000 people diagnosed with HIV (19%), with over half of these individuals from the South and disproportionately the rural South. Nationally, approximately 80,000 (9%) drive over an hour to receive HIV care. Suboptimal geographic accessibility to HIV care is an important structural barrier in the US, particularly for rural residents living with HIV in the South and West. Targeted policies and interventions to address this challenge should become a priority

Risk aversion in a performativity culture – what can we learn from teachers’ curriculum decision making in history?

Using the notion of risk aversion, this study explores the decisions teachers make when constructing a curriculum. Adopting a qualitative, grounded approach, this study used semi-structured interviews with nine history teachers to examine the decisions they were making during a period of considerable curriculum change in England. Five key categories were identified, which were then defined as risk averse or high risk. The findings show that teachers largely adopt a low risk approach when constructing a curriculum. In particular choice of content, pedagogical and assessment approaches are affected. Also, changes to the curriculum in high stakes examination courses have a major distorting impact on the curriculum choices for the phase of schooling prior to the examination course. This study would suggest that teachers generally aim to maximise examination outcomes through adopting a low risk approach to curriculum change. However, according to the literature, these low risk approaches appear unlikely to improve examination outcomes, whilst at the same time narrowing students’ experience of the curriculum

Intergenerational Communication – an interdisciplinary mapping review of research between 1996 and 2017

Concerns have been raised regarding the limited opportunities for intergenerational communication both outside and within the family. This “mapping review” draws together empirical literature in the topic published since 1996. Three hundred and twenty-four published studies met inclusion criteria, based on abstract review. The contents of each study were subjected to thematic analysis and nine broad themes emerged. These were (1) Dynamics of relationships, (2) Health & Well-being, (3) Learning & Literacy, (4) Attitudes, (5) Culture, (6) Digital, (7) Space, (8) Professional Development, and (9) Gender & Sexual Orientation. Studies commonly intersected disciplinary research areas. There was a marked rise across three key academic journals since 2007. An emergent finding was that a third of the studies relate to programs addressing intergenerational interventions, but many of these were primarily descriptive and failed to specify a primary outcome. Review implications and future research directions are discussed