Predicting Severe Asthma Exacerbations in Children.
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ABSTRACT:
SUBMITTER: Puranik S
PROVIDER: S-EPMC5387707 | biostudies-literature | 2017 Apr
REPOSITORIES: biostudies-literature
Publications
Predicting Severe Asthma Exacerbations in Children.
Puranik Sandeep S Forno Erick E Bush Andrew A Celedón Juan C JC
American journal of respiratory and critical care medicine 20170401 7
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Project description:ObjectivePrevious machine learning approaches fail to consider race and ethnicity and social determinants of health (SDOH) to predict childhood asthma exacerbations. A predictive model for asthma exacerbations in children is developed to explore the importance of race and ethnicity, rural-urban commuting area (RUCA) codes, the Child Opportunity Index (COI), and other ICD-10 SDOH in predicting asthma outcomes.MethodsInsurance and coverage claims data from the Arkansas All-Payer Claims Database were used to capture risk factors. We identified a cohort of 22,631 children with asthma aged 5-18 years with 2 years of continuous Medicaid enrollment and at least one asthma diagnosis in 2018. The goal was to predict asthma-related hospitalizations and asthma-related emergency department (ED) visits in 2019. The analytic sample was 59% age 5-11 years, 39% White, 33% Black, and 6% Hispanic. Conditional random forest models were used to train the model.ResultsThe model yielded an area under the curve (AUC) of 72%, sensitivity of 55% and specificity of 78% in the OOB samples and AUC of 73%, sensitivity of 58% and specificity of 77% in the training samples. Consistent with previous literature, asthma-related hospitalization or ED visits in the previous year (2018) were the two most important variables in predicting hospital or ED use in the following year (2019), followed by the total number of reliever and controller medications.ConclusionsPredictive models for asthma-related exacerbation achieved moderate accuracy, but race and ethnicity, ICD-10 SDOH, RUCA codes, and COI measures were not important in improving model accuracy.
| S-EPMC11195303 | biostudies-literature
Project description:RationaleVitamin D insufficiency (a serum 25(OH)D <30 ng/ml) has been associated with severe asthma exacerbations, but this could be explained by underlying racial ancestry or disease severity. Little is known about vitamin D and asthma in Puerto Ricans.ObjectivesTo examine whether vitamin D insufficiency is associated with severe asthma exacerbations in Puerto Rican children, independently of racial ancestry, atopy, and time outdoors.MethodsA cross-sectional study was conducted of 560 children ages 6-14 years with (n = 287) and without (n = 273) asthma in San Juan, Puerto Rico. We measured plasma vitamin D and estimated the percentage of African racial ancestry among participants using genome-wide genotypic data. We tested whether vitamin D insufficiency is associated with severe asthma exacerbations, lung function, or atopy (greater than or equal to one positive IgE to allergens) using logistic or linear regression. Multivariate models were adjusted for African ancestry, time outdoors, atopy, and other covariates.Measurements and main resultsVitamin D insufficiency was common in children with (44%) and without (47%) asthma. In multivariate analyses, vitamin D insufficiency was associated with higher odds of greater than or equal to one severe asthma exacerbation in the prior year (odds ratio [OR], 2.6; 95% confidence interval [CI], 1.5-4.9; P = 0.001) and atopy, and a lower FEV(1)/FVC in cases. After stratification by atopy, the magnitude of the association between vitamin D insufficiency and severe exacerbations was greater in nonatopic (OR, 6.2; 95% CI, 2-21.6; P = 0.002) than in atopic (OR, 2; 95% CI, 1-4.1; P = 0.04) cases.ConclusionsVitamin D insufficiency is associated with severe asthma exacerbations in Puerto Rican children, independently of racial ancestry, atopy, or markers of disease severity or control.
| S-EPMC3406083 | biostudies-literature
Project description:BackgroundIn the USA, genetically admixed populations have the highest asthma prevalence and severe asthma exacerbations rates. This could be explained not only by environmental factors but also by genetic variants that exert ethnic-specific effects. However, no admixture mapping has been performed for severe asthma exacerbations.ObjectiveWe sought to identify genetic variants associated with severe asthma exacerbations in Hispanic/Latino subgroups by means of admixture mapping analyses and fine mapping, and to assess their transferability to other populations and potential functional roles.MethodsWe performed an admixture mapping in 1124 Puerto Rican and 625 Mexican American children with asthma. Fine-mapping of the significant peaks was performed via allelic testing of common and rare variants. We performed replication across Hispanic/Latino subgroups, and the transferability to non-Hispanic/Latino populations was assessed in 1001 African Americans, 1250 Singaporeans and 941 Europeans with asthma. The effects of the variants on gene expression and DNA methylation from whole blood were also evaluated in participants with asthma and in silico with data obtained through public databases.ResultsGenomewide significant associations of Indigenous American ancestry with severe asthma exacerbations were found at 5q32 in Mexican Americans as well as at 13q13-q13.2 and 3p13 in Puerto Ricans. The single nucleotide polymorphism (SNP) rs1144986 (C5orf46) showed consistent effects for severe asthma exacerbations across Hispanic/Latino subgroups, but it was not validated in non-Hispanics/Latinos. This SNP was associated with DPYSL3 DNA methylation and SCGB3A2 gene expression levels.ConclusionsAdmixture mapping study of asthma exacerbations revealed a novel locus that exhibited Hispanic/Latino-specific effects and regulated DPYSL3 and SCGB3A2.
| S-EPMC9957797 | biostudies-literature
Project description:PurposeMinimizing the future risk of asthma exacerbation (AE) is one of the main goals of asthma management. We investigated prognostic factors for risk of severe AE (SAE) in a real-world clinical setting.MethodsThis is an observational study evaluating subjects who were diagnosed with asthma and treated with anti-asthmatic medications from January 1995 to June 2018. Risk factors for SAE were analyzed in 2 treatment periods (during the initial 2 years and the following 3-10 years of treatment) using the big data of electronic medical records.ResultsIn this study, 5,058 adult asthmatics were enrolled; 1,335 (28.64%) experienced ≥ 1 SAE during the initial 2 years of treatment. Female sex, higher peripheral eosinophil/basophil counts, and lower levels of forced expiratory volume in 1 second (FEV1; %) were factors predicting the risk of SAEs (P < 0.001 for all). Higher serum total immunoglobulin E levels increased the risk of SAEs among the patients having ≤ 2 SAEs (P = 0.025). Patients with more frequent SAEs during the initial 2 years of treatment had significantly higher risks of SAEs during the following years of treatment (P < 0.001, for all) (patients with ≥ 4 SAEs, odds ratio [OR], 29.147; those with 3 SAEs, OR, 14.819; those with 2 SAEs, OR, 9.867; those with 1 SAE, OR, 5.116), had higher maintenance doses of systemic steroids, and showed more gradual decline in FEV1 (%) and FEV1/forced vital capacity levels maintained during the following years of treatment (P < 0.001 for all).ConclusionsAsthmatics having risk factors for SAEs (female sex, higher peripheral eosinophil/basophil counts, and lower FEV1) should be strictly monitored to prevent future risk and improve clinical outcomes.
| S-EPMC7984950 | biostudies-literature
Project description: Not available
| S-EPMC5760478 | biostudies-literature
Project description:BackgroundMaternal depression has been linked to health care use for asthma in cross-sectional or short-term follow-up studies of school-aged children.ObjectiveTo examine whether increased or persistent maternal depressive symptoms over approximately 5 years are associated with severe asthma exacerbations or worse lung function in youth.MethodsA prospective study of 386 youth living in Puerto Rico, aged 6 to 14 years at a baseline visit and 9 to 20 years at a second visit, was performed. Our exposure of interest was change in persistence of maternal depressive symptoms, assessed at both visits using the Center for Epidemiologic Studies Depression Scale (CESD). Our outcomes of interest were change in percent predicted forced expiratory volume in 1 second (FEV1) and FEV1/forced vital capacity (FVC) between the first and second visits in all subjects, and ≥1 severe asthma exacerbation in the year before the second visit in subjects with asthma.ResultsIn a multivariable analysis, each 1-point increment in the CESD score was associated with decrements of 0.15% in percent predicted FEV1 (95% confidence interval [CI] = -0.28% to -0.01%; P = .03) and 0.10% in percent predicted FEV1/FVC (95% CI = -0.20% to 0.001%; P = .05) between visits, as well as with 1.03 times increased odds of ≥1 severe asthma exacerbation at the second visit (95% CI for odds ratio = 0.99 to 1.06, P = .09). In a multivariable analysis, the presence of maternal depressive symptoms (a CESD score ≥21 points) at the second visit or at both visits was significantly associated with 3.17 to 3.52 times increased odds of ≥1 severe asthma exacerbation in the year before the second visit.ConclusionsIncreasing or persistent maternal depressive symptoms over approximately 5 years are associated with worse lung function measures and severe asthma exacerbations among Puerto Rican youth, a high-risk population.
| S-EPMC7946650 | biostudies-literature
Project description:IntroductionAlthough clinical, functional, and biomarker data predict asthma exacerbations, newer approaches providing high accuracy of prognosis are needed for real-world decision-making in asthma. Machine learning (ML) leverages mathematical and statistical methods to detect patterns for future disease events across large datasets from electronic health records (EHR). This study conducted training and fine-tuning of ML algorithms for the real-world prediction of asthma exacerbations in patients with physician-diagnosed asthma.MethodsAdults with ≥ 2 ICD9/10 asthma codes within 1 year and at least 30 days apart were identified from the Optum Panther EHR database between 2016 and 2023. An emergency department (ED), urgent care, or inpatient visit for asthma, while on systemic administration of corticosteroids, was considered an exacerbation. To predict factors associated with exacerbations in a 6-month study period, clinical information from patients was retrieved in the preceding 6-month baseline period. Clinical information included demographics, lab results, diagnoses, medications, immunizations, and allergies. Three models built using Extreme Gradient Boosting (XGBoost), Long Short-Term Memory (LSTM), and Transformers algorithms were trained and tested on independent datasets. Predictions were explained using the SHAP (SHapley Additive exPlanations) library.ResultsOf 1,331,934 patients with asthma, 16,279 (1.2%) experienced ≥ 1 exacerbation. XGBoost was the best predictive algorithm (area under the curve [AUC] = 0.964). Factors associated with exacerbations included a prior history of exacerbation, prednisone usage, high-dose albuterol usage, and elevated troponin I. Reduced probability of exacerbations was associated with receiving inhaled albuterol, vitamins, aspirin, statins, furosemide, and influenza vaccination.ConclusionThis ML-based study on asthma in the real world confirmed previously known features associated with increased exacerbation risk for asthma, while uncovering not entirely understood features associated with reduced risk of asthma exacerbations. These findings are hypothesis-generating and should contribute to ongoing discussion of the strengths and limitations of ML and other supervised learning models in patient risk stratification.
| S-EPMC11782383 | biostudies-literature
Project description:This Letter investigated the efficacy of a decision-support system, designed for respiratory medicine, at predicting asthma exacerbations in a multi-site longitudinal randomised control trial. Adherence to inhaler medication was acquired over 3 months from patients with asthma employing a dose counter and a remote monitoring adherence device which recorded participant's inhaler use: n = 184 (23,656 audio files), 61% women, age (mean ± sd) 49.3 ± 16.4. Data on occurrence of exacerbations was collected at three clinical visits, 1 month apart. The relative risk of an asthma exacerbation for those with good and poor adherence was examined employing a univariate and multivariate modified Poisson regression approach; adjusting for age, gender and body mass index. For all months dose counter adherence was significantly (p < 0.01) higher than remote monitoring adherence. Overall, those with poor adherence had a 1.38 ± 0.34 and 1.42 ± 0.39 (remotely monitored) and 1.25 ± 0.32 and 1.18 ± 0.31 (dose counter) higher relative risk of an exacerbation in model 1 and model 2, respectively. However, this was not found to be statistically significantly different. Remotely monitored adherence holds important clinical information and future research should focus on refining adherence and exacerbation measures. Decision-support systems based on remote monitoring may enhance patient-physician communication, possibly reducing preventable adverse events.
| S-EPMC4814807 | biostudies-literature
Project description:Asthma exacerbations are common in asthmatic children, even among those with good disease control. Asthma attacks result in the children and their parents missing school and work days; limit the patient's social and physical activities; and lead to emergency department visits, hospital admissions, or even fatal events. Thus, the prompt identification of asthmatic children at risk for exacerbation is crucial, as it may allow for proactive measures that could prevent these episodes. Children prone to asthma exacerbation are a heterogeneous group; various demographic factors such as younger age, ethnic group, low family income, clinical parameters (history of an exacerbation in the past 12 months, poor asthma control, poor adherence to treatment, comorbidities), Th2 inflammation, and environmental exposures (pollutants, stress, viral and bacterial pathogens) determine the risk of a future exacerbation and should be carefully considered. This paper aims to review the existing evidence regarding the predictors of asthma exacerbations in children and offer practical monitoring guidance for promptly recognizing patients at risk.
| S-EPMC10820562 | biostudies-literature
Project description:Severe asthma exacerbations are a major cause of school absences and healthcare costs in children, particularly those in high-risk racial/ethnic groups.To identify susceptibility genes for severe asthma exacerbations in Latino children and adolescents, we conducted a meta-analysis of genome-wide association studies (GWAS) in 4010 Latino youth with asthma in four independent cohorts, including 1693 Puerto Ricans, 1019 Costa Ricans, 640 Mexicans, 256 Brazilians and 402 members of other Latino subgroups. We then conducted methylation quantitative trait locus, expression quantitative trait locus and expression quantitative trait methylation analyses to assess whether the top single nucleotide polymorphism (SNP) in the meta-analysis is linked to DNA methylation and gene expression in nasal (airway) epithelium in separate cohorts of Puerto Rican and Dutch children and adolescents.In the meta-analysis of GWAS, an SNP in FLJ22447 (rs2253681) was significantly associated with 1.55 increased odds of severe asthma exacerbation (95% CI 1.34-1.79, p=6.3×10-9). This SNP was significantly associated with DNA methylation of a CpG site (cg25024579) at the FLJ22447 locus, which was in turn associated with increased expression of KCNJ2-AS1 in nasal airway epithelium from Puerto Rican children and adolescents (β=0.10, p=2.18×10-7).SNP rs2253681 was significantly associated with both DNA methylation of a cis-CpG in FLJ22447 and severe asthma exacerbations in Latino youth. This may be partly explained by changes in airway epithelial expression of a gene recently implicated in atopic asthma in Puerto Rican children and adolescents (KCNJ2-AS1).
| S-EPMC8026735 | biostudies-literature