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Updated: Sep 22, 2026

Murine Model of Allergen Induced Asthma
Published on: May 14, 2012
Forecasting asthmatic wheezing using temperature velocity
Insights
Predicting pediatric asthma emergency visits is possible using temperature change. This model, focusing on temperature velocity, explains significant daily and weekly variations, aiding in emergency department planning and potential prevention strategies.
Area of Science:
- Environmental Health
- Pediatric Pulmonology
- Biostatistics
Background:
- Pediatric asthma exacerbations frequently lead to emergency department visits.
- Predictive models for asthma-related emergency visits are crucial for resource allocation and patient management.
Purpose of the Study:
- To develop and validate a predictive model for pediatric asthmatic wheezing emergency department visits.
- To investigate the role of temperature change, specifically temperature velocity, as a predictor.
Main Methods:
- Analysis of 9,425 pediatric asthma emergency visits from 1982-1983.
- Construction of a statistical model using temperature velocity and seasonal temperature change.
- Evaluation of other environmental factors like CO, barometric pressure, and humidity.
Main Results:
- The model significantly predicted daily (R2=35%) and weekly (R2=49%) variations in asthma emergency visits.
- Temperature velocity was a highly significant predictor (P<0.0001).
- Other factors like CO, pressure, and humidity showed statistical significance but limited clinical impact.
Conclusions:
- Temperature velocity is a powerful predictor of pediatric asthma emergency visits.
- Improved predictive models can aid in emergency department staffing and proactive patient care.
- Utilizing seasonal patterns and temperature changes can enhance asthma management strategies.
Abstract:
A model was constructed to predict pediatric asthmatic wheezing visits to the emergency department. All wheezing visits to the Children's Hospital of Philadelphia Emergency Department were analyzed for 1982 and 1983, for ages two to 18. Nine thousand four hundred twenty-five visits fit the study requirements, 27% of the total number of emergency department visits for all causes. The a priori hypothesis used to construct the model was that temperature change, not absolute temperature, would be a good predictor of emergency department visits. Although not attempting to prove a cause-and-effect relationship, by studying temperature velocity (the rate of change of temperature) and the direction of change of temperature (a seasonal variable reflecting rising or falling temperature), a model was created that was highly significant (P less than 0.0001) and could explain 35% of the daily variation in asthmatic emergency department visits (R2 = 35%, r = 0.59). When weekly emergency department visits were analyzed, the model could explain 49% of the variation in the number of emergency department visits (R2 = 49%, r = 0.70). Carbon monoxide, barometric pressure, and relative humidity were also statistically significant predictors but were clinically insignificant, explaining only a few percentage points of the total variation. By taking advantage of the seasonal pattern of wheezing through the use of temperature velocity, predictive models for asthmatic wheezing can be greatly improved. They may also aid in planning emergency department staffing, and even help prevent emergency department visits by premedication or lifestyle change during high-risk periods.
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