Allergy Asthma Respir Dis.  2016 Sep;4(5):328-339. 10.4168/aard.2016.4.5.328.

The development of patient-tailored asthma prediction model for the alarm system

• Yun HS
• Rah WJ
• Choi YJ
• Kim JH
• Oh JW
• Kim HH
• Chang YS
• Yoo KH
• Sohn KT

• KMID: 2391922
• DOI: http://doi.org/10.4168/aard.2016.4.5.328

Abstract

PURPOSE
The increased incidence of asthma due to rising allergic diseases requires the prevention of worsening asthma. It is necessary to develop a patient-tailored asthma prediction model.
METHODS
We developed causative factors for the asthma forecast system: infant and young children (0-2 years), preschool children (3-6 years), school children and adolescents (7-18 years), adults (19-64 years), old aged adult (>64 years). We used the Emergency Department code data which charged the short-acting bronchodilator (Salbutamol sulfate) from Health Insurance Review and Assessment Service for the development of asthma prediction models. Three kinds of statistical models (multiple regression models, logistic regression models, and decision tree models) were applied to 40 study groups (4 seasons, 2 sex, and 5 age groups) separately.
RESULTS
The 3 kinds of models were compared based on model assessment measures. Estimated logistic regression models or decision tree models were recommended as binary forecast models. To improve the predictability, a threshold was used to generate binary forecasts.
CONCLUSION
We suggest the binary forecast models as a patient-tailored asthma prediction system for this category. It may be needed the extended study duration and long-term data analysis for asthmatic patients for the further improvement of asthma prediction models.

Keyword

Asthma; Asthma alarm system

MeSH Terms

Adolescent
Adult
Asthma*
Child
Child, Preschool
Decision Trees
Emergency Service, Hospital
Humans
Incidence
Infant
Insurance, Health
Logistic Models
Models, Statistical
Seasons
Statistics as Topic

Figure

• 

  Fig. 1 Box plot showing distribution of patients with asthma by sex and age group. M, man subject; W, woman subject. M1 and W1: 0–2 years old, M2 and W2: 3–6 years old, M3 and W3: 7–18 years old, M4 and W4: 19–64 years old, M5 and W5: 65 years old.

• 

  Fig. 2 Histogram showing distribution of patients with asthma by sex and age group. M, man subject; W, woman subject. M1 and W1: 0–2 years old, M2 and W2: 3–6 years old, M3 and W3: 7–18 years old, M4 and W4: 19–64 years old, M5 and W5: 65 years old.

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