STUDY OBJECTIVES: To develop simple clinical tools predictive of acute asthma care and to identify modifiable risk factors. DESIGN: Prospective cohort study. SETTING: A large health maintenance organization (430,000 members). PATIENTS/PARTICIPANTS: Adult members (18 to 55 years old) with asthma. INTERVENTIONS: Data from a questionnaire, skin-prick testing for inhalant allergens, and spirometry were collected at the baseline visit. Acute care utilization data were obtained from administrative databases for a subsequent 30-month period. METHODS: This two-phase study first identified and performed a split-sample validation on three clinical tools to determine their predictive ability by employing data from a questionnaire, questionnaire plus spirometry, and questionnaire plus spirometry and skin-prick testing. Second, it identified modifiable independent risk factors. MEASUREMENTS AND RESULTS: The 554 study participants generated 173 episodes of acute care over 1,258 person-years of follow-up (0.14 episodes per person per year). Of these, 101 participants had at least one episode, and one third of this group had two or more episodes. Clinical scoring into risk groups was done by reverse stepwise regression analyses. Using relative risks (RRs) as a guide, high-risk, moderate-risk, and low-risk groups were identified. The high-risk groups, 13 to 21% of the validation sample, had a 7- to 11-fold increased risk for hospital care compared to the low-risk groups. The moderate-risk groups, 46 to 50% of the validation sample, had a twofold- to fourfold-increased risk. FEV(1) was the most significant predictor (RR, 4.33). Of the four potentially modifiable risk factors identified, current cigarette smoke exposure (RR, 1.6) and ownership and skin-prick test positivity to cat or dog (RR, 1.5) were the most significant. CONCLUSIONS: These models stratify asthma patients at risk for acute care. Patients with lower FEV(1) values are at significantly higher risk, underscoring the importance of spirometry in asthma care.
STUDY OBJECTIVES: To develop simple clinical tools predictive of acute asthma care and to identify modifiable risk factors. DESIGN: Prospective cohort study. SETTING: A large health maintenance organization (430,000 members). PATIENTS/PARTICIPANTS: Adult members (18 to 55 years old) with asthma. INTERVENTIONS: Data from a questionnaire, skin-prick testing for inhalant allergens, and spirometry were collected at the baseline visit. Acute care utilization data were obtained from administrative databases for a subsequent 30-month period. METHODS: This two-phase study first identified and performed a split-sample validation on three clinical tools to determine their predictive ability by employing data from a questionnaire, questionnaire plus spirometry, and questionnaire plus spirometry and skin-prick testing. Second, it identified modifiable independent risk factors. MEASUREMENTS AND RESULTS: The 554 study participants generated 173 episodes of acute care over 1,258 person-years of follow-up (0.14 episodes per person per year). Of these, 101 participants had at least one episode, and one third of this group had two or more episodes. Clinical scoring into risk groups was done by reverse stepwise regression analyses. Using relative risks (RRs) as a guide, high-risk, moderate-risk, and low-risk groups were identified. The high-risk groups, 13 to 21% of the validation sample, had a 7- to 11-fold increased risk for hospital care compared to the low-risk groups. The moderate-risk groups, 46 to 50% of the validation sample, had a twofold- to fourfold-increased risk. FEV(1) was the most significant predictor (RR, 4.33). Of the four potentially modifiable risk factors identified, current cigarette smoke exposure (RR, 1.6) and ownership and skin-prick test positivity to cat or dog (RR, 1.5) were the most significant. CONCLUSIONS: These models stratify asthmapatients at risk for acute care. Patients with lower FEV(1) values are at significantly higher risk, underscoring the importance of spirometry in asthma care.
Authors: Natalia Hernandez-Pacheco; Carlos Flores; Sam S Oh; Esteban G Burchard; Maria Pino-Yanes Journal: Curr Allergy Asthma Rep Date: 2016-07 Impact factor: 4.806
Authors: Wilson Quezada; Eun Soo Kwak; Joan Reibman; Linda Rogers; John Mastronarde; William G Teague; Christine Wei; Janet T Holbrook; Emily DiMango Journal: Ann Allergy Asthma Immunol Date: 2015-12-19 Impact factor: 6.347
Authors: David G Mummy; Katherine J Carey; Michael D Evans; Loren C Denlinger; Mark L Schiebler; Ronald L Sorkness; Nizar N Jarjour; Sean B Fain Journal: J Allergy Clin Immunol Date: 2020-03-13 Impact factor: 10.793