Literature DB >> 25158051

Development and initial testing of Asthma Predictive Index for a retrospective study: an exploratory study.

Chung-Il Wi1, Miguel A Park, Young J Juhn.   

Abstract

OBJECTIVE: Asthma Predictive Index (API) has been used for predicting asthma in prospective or cross-sectional studies, not for a retrospective study. We aim to develop and validate API for a retrospective study.
METHODS: This is a cross-sectional study based on a convenience sample of children who participated in a previous retrospective cohort study. API was operationalized by two or more wheezing episodes in a year during the first 3 years of life PLUS one of the major or two of the minor criteria of the original API. We assessed validity of retrospective API against Predetermined Asthma Criteria (PAC) which has been extensively used in clinical studies for asthma. We assessed criterion validity by measuring kappa and agreement rate between API and PAC and construct validity by determining associations of API with known risk factors for asthma.
RESULTS: Of the eligible 105 children, 55 (52.4%) were male, 90 (85.7%) Caucasians, and the mean age (±SD) was 5.8 years (±1.5). API criteria was met by 15 (14.3%), compared to 33 (31.4%) by PAC, respectively. The agreement rate and kappa between API and definite asthma of PAC were 89.5% and 0.66 (p < 0.01). Atopic conditions, lower parental education, no history of breastfeeding and family history of asthma were significantly associated with risk of asthma by API.
CONCLUSIONS: Application of API to a retrospective study for ascertaining asthma status is suitable. Our study findings need to be replicated by future studies with a larger sample size.

Entities:  

Keywords:  Asthma ascertainment; Predetermined asthma criteria; asthma predictive index; retrospective study; wheezing

Mesh:

Substances:

Year:  2014        PMID: 25158051      PMCID: PMC4589246          DOI: 10.3109/02770903.2014.952438

Source DB:  PubMed          Journal:  J Asthma        ISSN: 0277-0903            Impact factor:   2.515


  42 in total

1.  Interobserver variability in medical record review: an epidemiological study of asthma.

Authors:  C M Beard; J W Yunginger; C E Reed; E J O'Connell; M D Silverstein
Journal:  J Clin Epidemiol       Date:  1992-09       Impact factor: 6.437

2.  Cigarette smoking among adults--United States, 2003.

Authors: 
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2005-05-27       Impact factor: 17.586

3.  History of the Rochester Epidemiology Project.

Authors:  L J Melton
Journal:  Mayo Clin Proc       Date:  1996-03       Impact factor: 7.616

4.  Eosinophilic inflammation in asthma.

Authors:  J Bousquet; P Chanez; J Y Lacoste; G Barnéon; N Ghavanian; I Enander; P Venge; S Ahlstedt; J Simony-Lafontaine; P Godard
Journal:  N Engl J Med       Date:  1990-10-11       Impact factor: 91.245

5.  Asthma as a risk factor for invasive pneumococcal disease.

Authors:  Thomas R Talbot; Tina V Hartert; Ed Mitchel; Natasha B Halasa; Patrick G Arbogast; Katherine A Poehling; William Schaffner; Allen S Craig; Marie R Griffin
Journal:  N Engl J Med       Date:  2005-05-19       Impact factor: 91.245

6.  Effect of thromboxane A2-receptor antagonist on bradykinin-induced bronchoconstriction in asthma.

Authors:  K Rajakulasingam; S L Johnston; J Ducey; W Ritter; P H Howarth; S T Holgate
Journal:  J Appl Physiol (1985)       Date:  1996-06

7.  Atopic characteristics of children with recurrent wheezing at high risk for the development of childhood asthma.

Authors:  Theresa W Guilbert; Wayne J Morgan; Robert S Zeiger; Leonard B Bacharier; Susan J Boehmer; Marzena Krawiec; Gary Larsen; Robert F Lemanske; Andrew Liu; David T Mauger; Chris Sorkness; Stanley J Szefler; Robert C Strunk; Lynn M Taussig; Fernando D Martinez
Journal:  J Allergy Clin Immunol       Date:  2004-12       Impact factor: 10.793

8.  Asthma and wheezing in the first six years of life. The Group Health Medical Associates.

Authors:  F D Martinez; A L Wright; L M Taussig; C J Holberg; M Halonen; W J Morgan
Journal:  N Engl J Med       Date:  1995-01-19       Impact factor: 91.245

9.  Potential influence of migration bias in birth cohort studies.

Authors:  S K Katusic; R C Colligan; W J Barbaresi; D J Schaid; S J Jacobsen
Journal:  Mayo Clin Proc       Date:  1998-11       Impact factor: 7.616

10.  A community-based study of the epidemiology of asthma. Incidence rates, 1964-1983.

Authors:  J W Yunginger; C E Reed; E J O'Connell; L J Melton; W M O'Fallon; M D Silverstein
Journal:  Am Rev Respir Dis       Date:  1992-10
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