Forced Expiratory Volume in 1 Second Percentage Improves the Classification of Severity Among Children With Asthma

Department of Health Policy and Management , Harvard University, Cambridge, Massachusetts, United States
PEDIATRICS (Impact Factor: 5.47). 09/2006; 118(2):e347-55. DOI: 10.1542/peds.2005-2962
Source: PubMed


Spirometry is an important component of the National Asthma Education and Prevention Program guidelines for asthma, yet published data show variable associations between forced expiratory volume in 1 second percentage (FEV1%) predicted, symptoms and health care utilization. The objective of this analysis was to examine the association between FEV1% and future risk of exacerbations among a well-characterized population of children with asthma.
Using data that are available from the Childhood Asthma Management Program, we examined the relationship between prebronchodilator FEV1% and important clinical outcomes. Multiple observations of FEV1 were available for each patient; multivariate regression analysis, using a general estimating equation approach, was used to control for the correlation between repeated measurements among individuals and potential confounders. FEV1% was categorized into 4 levels and as a continuous variable. Outcomes of interest included mean symptom score (0-3), episode-free days, and asthma-related events (oral steroid use, emergency department visits, and hospitalizations) during the ensuing 4-month period. Our analysis was limited to the placebo group (N = 417).
We observed a clear relationship between prebronchodilator FEV1% and important clinical outcomes. In multivariable models that simultaneously controlled for covariates of interest, age at baseline, time, previous event history, and nocturnal awakenings, a significant relationship between FEV1% and asthma symptoms and serious asthma exacerbations (oral steroids, emergency department visits, and hospitalizations) was observed. Compared with children with an FEV1% > or = 100%, children with FEV1% 80% to 99%, 60% to 79%, and < 60% were 1.3, 1.8, and 4.8, respectively, more likely to have a serious asthma exacerbation during the ensuing 4 months. CONCLUSIONS. In children with mild to moderate asthma, FEV1% predicted is independently associated with future asthma symptoms and health care utilization. Previous asthma-related hospitalizations and nocturnal symptoms also were independently associated with risk for future adverse events. FEV1 is an important component of asthma health status and asthma severity classification.

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    • "Based on data published in the Fuhlbrigge study, if a child had a hospitalization due to asthma in the previous 12 months , their probability of having a serious asthma event increased (Table 3, [80]). We calculated this multiplicative factor following the same process described above, with the resulting polynomial equation: "
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    ABSTRACT: Background In the United States, asthma is the most common chronic disease of childhood across all socioeconomic classes and is the most frequent cause of hospitalization among children. Asthma exacerbations have been associated with exposure to residential indoor environmental stressors such as allergens and air pollutants as well as numerous additional factors. Simulation modeling is a valuable tool that can be used to evaluate interventions for complex multifactorial diseases such as asthma but in spite of its flexibility and applicability, modeling applications in either environmental exposures or asthma have been limited to date. Methods We designed a discrete event simulation model to study the effect of environmental factors on asthma exacerbations in school-age children living in low-income multi-family housing. Model outcomes include asthma symptoms, medication use, hospitalizations, and emergency room visits. Environmental factors were linked to percent predicted forced expiratory volume in 1 second (FEV1%), which in turn was linked to risk equations for each outcome. Exposures affecting FEV1% included indoor and outdoor sources of NO2 and PM2.5, cockroach allergen, and dampness as a proxy for mold. Results Model design parameters and equations are described in detail. We evaluated the model by simulating 50,000 children over 10 years and showed that pollutant concentrations and health outcome rates are comparable to values reported in the literature. In an application example, we simulated what would happen if the kitchen and bathroom exhaust fans were improved for the entire cohort, and showed reductions in pollutant concentrations and healthcare utilization rates. Conclusions We describe the design and evaluation of a discrete event simulation model of pediatric asthma for children living in low-income multi-family housing. Our model simulates the effect of environmental factors (combustion pollutants and allergens), medication compliance, seasonality, and medical history on asthma outcomes (symptom-days, medication use, hospitalizations, and emergency room visits). The model can be used to evaluate building interventions and green building construction practices on pollutant concentrations, energy savings, and asthma healthcare utilization costs, and demonstrates the value of a simulation approach for studying complex diseases such as asthma.
    Environmental Health 09/2012; 11(1):66. DOI:10.1186/1476-069X-11-66 · 3.37 Impact Factor
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    • "The ability to predict severe asthma exacerbations would therefore have direct prognostic significance and might form the basis for the development of novel therapeutic interventions. Severe asthma exacerbations have been associated with several clinical factors including the forced expiratory volume in one second as a percent of predicted (FEV1%), oral corticosteroid usage [9,19], age [20], and sex [21]. However, these factors by themselves are limited in their ability to successfully predict severe asthma exacerbations [21,22]. "
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    BMC Medical Genetics 06/2011; 12(1):90. DOI:10.1186/1471-2350-12-90 · 2.08 Impact Factor
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    Journal of managed care pharmacy: JMCP 01/2008; 14(1):41-9. · 2.71 Impact Factor
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