Whilst data-driven approaches have provided a framework for unearthing a structure within large datasets, there is a risk of assuming that the results represent the “truth,” in particular when this assumption is based on a reliance on objective statistical criteria, such as the Bayesian information criterion (BIC), Akaike information criterion (AIC), etc. Similarly, several inflammatory phenotypes (46) such as eosinophilic asthma, neutrophilic asthma, pauci-granulocytic asthma (24, 47–50), and Th2-high asthma (51), and trigger-induced asthma phenotypes such as cigarette smoke-induced asthma (52), air pollution-induced asthma (53), and exercise-induced asthma (54) have been identified in different populations. After asthma: redefining airways diseases. Figure 1. Albeit pediatric asthma is a multifactorial disease, accumulating evidence suggests that exposure to a diverse environmental microbiome in early life has a protective effect against childhood asthma , . See also: sub-topics. J Am Med Inform Assoc. Asthma Classifications Schedule an Appointment Based on the results of your visit with an asthma specialist, your asthma will be classified in one of the following categories … Ann Allergy Asthma Immunol. doi: 10.1016/S2213-2600(18)30100-0, 29. Custovic A, Belgrave D, Lin L, Bakhsoliani E, Telcian AG, Solari R, et al. Symptoms of a cough, wheeze, chest tightness or difficulty breathing three to six times a week, Nighttime symptoms three to four times a month. Simpson JL, Scott R, Boyle MJ, Gibson PG. Big data analytics to improve cardiovascular care: promise and challenges. A thorough review of the implementation of data-driven methods for phenotype discovery in pediatric asthma has been conducted recently, with a particular focus on childhood wheezing illness and different “wheezing phenotypes” at a population level (11, 12). For the clinical community, the proliferation of machine learning techniques and their associated language inventory of “new” terms [hidden Markov models (34), random forest (42), Bayesian networks (42), latent variable modeling (42), clustering (22), etc.,] are complex to comprehend, even by the statistically literate. By incorporating the longitudinal structure of data, the latter has enabled investigators to capture the multidimensionality of the disease and to characterize phenotypic heterogeneity across the life-course (28). Diagnosis of asthma in symptomatic children based on measures of lung function: an analysis of data from a population-based birth cohort study. Expert Panel Report 3: Guidelines for the Diagnosis and Over the last few decades, latent modeling approaches [reviewed in (9, 11, 12)] have been extensively used to identify longitudinal trajectories of childhood wheeze (10, 17, 33, 34), atopy (34–37), and asthma (11, 12, 19), and to evaluate their associations with early life risk factors. Vital Signs: Asthma in Children – United States, 2001-2016Free continuing education (CE) activity that describes trends and demographic differences in health outcomes and healthcare use for childhood asthma, based on a CDC analysis of asthma data from the 2001-2016 National Health Interview Survey for children 17 years and younger.This activity is intended for pediatricians, pulmonologists, public health officials, nurses, and other clinicians caring for patients with child… 3 | Investment and impact fund 2020/21: guidance 2. As an example, an individual may have a 0.5 probability of belonging to “phenotype 1,” 0.30 probability of belonging to “phenotype 2,” and 0.20 probability of being in “phenotype 3,” yet such classification would assign a person into “phenotype 1,” ignoring the underlying uncertainty in class assignment. It is a common practice to then assign individuals to one of the latent classes according to the maximum posterior probability for an individual belonging to a particular class. Through resources such as evidence-based strategy documents for asthma management, and events such as the annual celebration of World Asthma Day, GINA is working to improve the lives of people with asthma … This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). Rigorous scientific assessment, reproducibility and transparency of models are increasingly challenging with the availability of diverse programming languages (R, Python, Stata, MATLAB, Infer.Net, MPlus, etc.,). An automated chart review. The classification … doi: 10.1164/rccm.200903-0392OC, 52. For example, by employing machine learning, a recent study has described an architecture of multiple cytokine responses by human blood mononuclear cells to rhinovirus stimulation comprising six response profiles, and observed major differences in trajectories of asthma, allergic sensitization and lower respiratory tract infections during childhood between these profiles, suggesting that impaired anti-virus immunity may contribute to the development of a specific phenotype of troublesome childhood asthma (41). Statistical methods such as cluster analysis and latent class analysis (LCA) (11, 24–26), principal component analysis (20, 27), and exploratory factor analysis (21), have been widely applied to discover homogeneous subtypes of asthma. Belgrave D, Henderson J, Simpson A, Buchan I, Bishop C, Custovic A. Disaggregating asthma: big investigation versus big data. Collectively, these findings highlight how the use of umbrella term “asthma” masks the complexity of disease heterogenity, and that the derivation of more precise and internally-homogenous phenotypes may be useful for providing more accurate assessment of underlying pathophysiology. Am J Respir Crit Care Med. Factor analysis in the Genetics of Asthma International Network family study identifies five major quantitative asthma phenotypes. doi: 10.1016/j.jpeds.2013.11.037, 45. Moore WC, Meyers DA, Wenzel SE, Teague WG, Li H, Li X, et al. (2010) 36:48–56. Enjoy and learn! Lung function trajectories from pre-school age to adulthood and their associations with early life factors: a retrospective analysis of three population-based birth cohort studies. Big data in healthcare refers to the large volumes of data accumulated from numerous sources, patients and populations that can no longer be easily handled by traditional statistical analysis methods due to its complexity. Mild Intermittent Asthma… doi: 10.1016/S2213-2600(18)30099-7, 39. Lancet (2018) 391:350–400. J Pediatr. Allergic rhinitis is a common disorder that is strongly linked to asthma and conjunctivitis. 27. All patients and visitors are required to wear a mask. Copyright © 2018 Oksel, Haider, Fontanella, Frainay and Custovic. One such approach is latent class trajectory modeling, a class of probabilistic models in which repeated measurements of observable symptoms are modeled to identify homogeneous sub-populations within the larger heterogeneous population. Semic-Jusufagic A, Belgrave D, Pickles A, Telcian AG, Bakhsoliani E, Sykes A, et al. As these probabilities collectively measure specific individual's likelihood of belonging to each of the classes discovered by a model, a class (or “phenotype”) membership is not fixed, and all individuals are assigned a non-zero probability of belonging to each class. doi: 10.1016/j.jaci.2016.11.003, 10. Thorax (2015) 70:799–801. Analgesia for women with asthma. Received: 08 June 2018; Accepted: 29 August 2018; Published: 20 September 2018. J Allergy Clin Immunol. ), are extensively used in medical research. Zeng QT, Goryachev S, Weiss S, Sordo M, Murphy SN, Lazarus R. Extracting principal diagnosis, co-morbidity and smoking status for asthma research: evaluation of a natural language processing system. View all The promise of data-driven “revolution” to support clinical decision making will not be fulfilled by technological and methodological advances alone, but by a fundamental change in medical culture, and the advancement of a team science approach (5). (2013) 9:921–36. (2015) 112:5485–90. All Rights Reserved. Anderson GP. (2005) 6:224. doi: 10.1186/gb-2005-6-7-224, 66. (2006) 6:30. doi: 10.1186/1472-6947-6-30, 70. Front. 69. In 2018, 11.9 million, or 48.2 percent of those ever diagnosed with asthma by a health professional and still had asthma had at least one asthma attack. Community challenges in biomedical text mining over 10 years: success, failure and the future. (2008) 177:1358–63. It is usually a long-standing condition that often goes undetected in the primary … In the longer-term, findings from large-scale data have the potential for the development of non-invasive and quick diagnostic assessments for use in clinics (57, 60). 1.4.1 Offer women with asthma the same options for pain relief during labour as women without asthma, including: Entonox (50% nitrous oxide plus 50% oxygen) intravenous and intramuscular opioids. Expert Rev Clin Immunol. This may facilitate more meaningful and robust disease classification through, for example, a more informed choice of prognostic indicators, and inform the clinical decision-making process. Patient cohorts contain data which complement the information from birth cohorts, and bringing together these data assets may be essential to disaggregate asthma. Hilvering B, Vijverberg S, Houben L, Schweizer R, Lammers J-W, Koenderman L. The identification of asthma phenotypes by categorical PCA: combinatorial analysis of clinical parameters and dysfunctional blood eosinophils. J Allergy Clin Immunol. Factors predicting persistence of early wheezing through childhood and adolescence: a systematic review of the literature. Rebholz-Schuhmann D, Oellrich A, Hoehndorf R. Text-mining solutions for biomedical research: enabling integrative biology. combined spinal–epidural analgesia. Asthma phenotypes identified by latent class analysis in the ISAAC phase II Spain study. Brief Bioinform. However, despite the increasing utilization of (and reliance on) latent class methods to stratify asthma and allergic diseases, there is a striking lack of enquiry into the extent of between-individual variation within the supposedly homogeneous “phenotypes.” Latent class methods use posterior probabilities which provide researchers with an objective basis for assigning individuals to classes (phenotypes) that best typify their pattern of symptom development. Below is a summary of the most recent national guidelines for evaluating these patients, and the Figure shows the BP classification by The Eighth Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC 8) 1 and 2017 American College of Cardiology/American Heart Association (AHA) hypertension guidelines: Peak flow less than 20 to 30 percent variability. Characterization of patients who suffer asthma exacerbations using data extracted from electronic medical records. J Allergy Clin Immunol. However, translating findings from data-driven analyses into meaningful insights and actionable solutions requires approaches and tools which move beyond mining and patterning longitudinal data. Lancet Child Adolesc Health (2017) 1:114–23. Sputum neutrophil counts are associated with more severe asthma phenotypes using cluster analysis. 1 However, researchers have found patterns of symptoms and body processes that make up different types of asthma. To rule out other possible conditions — such as a respiratory infection or chronic obstructive pulmonary disease (COPD) — your doctor will do a physical exam and ask you questions about your signs and symptoms and about any other health problems. Asthma is a globally significant non-communicable disease with major public health consequences for both children and adults, including high morbidity, and mortality in severe cases. J Allergy Clin Immunol. Principal Investigator ... her computing laboratory is involved in methodological and software development in clustering and classification techniques, statistical issues in population biology, systems biology, survival analysis, multi-state models and big data analytics. However, the ratio of wall thickness to luminal diameter was not correlated with clinical features such as smoking history, duration of symptoms, physiologic measures (eg, FEV1), … One way to address the complexity of asthma is to derive asthma phenotypes that differentiate groups of patients presenting with similar combinations of symptoms, and to understand how biological factors shape each of these disease “phenotypes” (5). Henneberger PK, Redlich CA, Callahan DB, Harber P, Lemiere C, Martin J, et al. epidural. Introduction. (2014) 164:815–20. J Allergy Clin Immunol. Several recent studies which used machine learning-based methodologies applied to a large amount of data generated by multiplex arrays measuring IgE to more than 100 individual allergenic proteins suggest that it may be possible to develop better diagnostic algorithms to help practicing physicians differentiate between benign and clinically important allergic sensitisation to help asthma diagnosis (57–59). In 2018/19, the prevalence of obesity in children aged 4-5 was over twice as high in the most deprived areas (12.9%) compared to the least deprived areas (6.4%). (2016) 137:667–79. (2015) 136:1224–31. T-helper type 2–driven inflammation defines major subphenotypes of asthma. The ASA Physical Status Classification System has been in use for over 60 years. Moore WC, Hastie AT, Li X, Li H, Busse WW, Jarjour NN, et al. Pediatr. Application of a time-stratified case-crossover design to explore the effects of air pollution and season on childhood asthma hospitalization in cities of differing urban patterns: big data analytics of government open data. e14. Genes to diseases (G2D) computational method to identify asthma candidate genes. One way of bridging the findings from data-driven analytics into day-to-day clinical practice is by linking identified phenotypes to a specific underlying pathology, and tailoring treatment choices based on pathophysiologic mechanisms. doi: 10.1073/pnas.1421178112, 56. After asthma is diagnosed, the next step is to determine how severe–or intense–your asthma is. (2017) 13:705–13. Proc Natl Acad Sci USA. doi: 10.1016/j.jaci.2015.03.027, 58. BMC Genetics (2005) 6:45. doi: 10.1186/1471-2156-6-45, 64. 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