Literature DB >> 4056253

Improving the ability of peak expiratory flow rates to predict asthma.

D L Harm, H Kotses, T L Creer.   

Abstract

A major problem in the behavioral management of childhood asthma concerns recognition of the early signs of impending episode. An objective measure commonly used to aid recognition of early warning signs is the peak expiratory flow rate (PEFR). This study examined the ability of PEFRs to predict asthma within a 12-hour period; the prediction method used was based on prior and conditional posterior probabilities. Twenty-five children with asthma recorded their PEFR twice daily, and also recorded the date and time of their asthma episodes. Conditional posterior probabilities and the ratio of hits to misses were computed for each subject at successively lower flow rates. The average improvement in predictability from the prior probability to the highest posterior probability was 491%. The ratio of hits to misses and the number of episodes predicted, however, decreased as the posterior probability increased. Selection of the PEFR at lower posterior probabilities resulted in fewer prediction errors and led to prediction of a higher number of episodes than selection of the PEFR at the highest posterior probability.

Entities:  

Mesh:

Year:  1985        PMID: 4056253     DOI: 10.1016/0091-6749(85)90672-4

Source DB:  PubMed          Journal:  J Allergy Clin Immunol        ISSN: 0091-6749            Impact factor:   10.793


  3 in total

1.  Long-term effects of biofeedback-induced facial relaxation on measures of asthma severity in children.

Authors:  H Kotses; A Harver; J Segreto; K D Glaus; T L Creer; G A Young
Journal:  Biofeedback Self Regul       Date:  1991-03

2.  A multivariate model for predicting respiratory status in patients with chronic obstructive pulmonary disease.

Authors:  G H Murata; C O Kapsner; D J Lium; H K Busby
Journal:  J Gen Intern Med       Date:  1998-07       Impact factor: 5.128

3.  Predicting asthma exacerbations employing remotely monitored adherence.

Authors:  Isabelle Killane; Imran Sulaiman; Elaine MacHale; Aoife Breathnach; Terence E Taylor; Martin S Holmes; Richard B Reilly; Richard W Costello
Journal:  Healthc Technol Lett       Date:  2016-03-23
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.