title: Reporting peak expiratory flow in older persons.
abstract: BACKGROUND
  Peak expiratory flow ("peak flow") predicts important outcomes in older persons. Nevertheless, its clinical application is uncertain because prior strategies for reporting peak flow may not be valid. We thus determined the frequency distribution of peak flow by the conventional strategy of percent predicted (%predicted) and by an alternative method termed standardized residual (SR) percentile, and evaluated how these two metrics relate to health status in older persons.
  
  
  METHODS
  Participants included 754 community-dwelling persons aged >/= 70 years. Data included chronic conditions, frailty indicators, and peak flow.
  
  
  RESULTS
  Mean age was 78.4 years, with 63.7% reporting a smoking history, 17.4% chronic lung disease, and 77.1% having one or more frailty indicators. Peak flow >/= 80 %predicted was recorded in 67.5% of participants, whereas peak flow >/= 80th SR percentile was only noted in 15.9%. A graded relationship was observed between peak flow and health status, but %predicted yielded health risk at peak flows currently considered normal (80-100 %predicted), whereas SR percentile conferred health risk only at severely reduced peak flows (< 50th SR percentile).
  
  
  CONCLUSIONS
  Peak flow expressed as SR percentile attains a frequency distribution more consistent with the characteristics of our elderly cohort, and establishes health risk at more appropriate levels of reduced peak flow. These findings establish the need for longitudinal studies based on SR percentile to further evaluate the use of peak flow as a risk assessment tool in older persons and to determine if pulmonary function, in general, is better reported in older persons as SR percentile, rather than as %predicted.
authors.affiliation: Department of Internal Medicine, Yale University School of Medicine, 333 Cedar Street, P.O. Box 208025, New Haven, CT 06250-8025, USA. carlos.fragoso@ynhh.org
authors.forename: Carlos A
authors.initials: CA
authors.lastname: Vaz Fragoso
authors.forename: Evelyne A
authors.initials: EA
authors.lastname: Gahbauer
authors.forename: Peter H
authors.initials: PH
authors.lastname: Van Ness
authors.forename: Thomas M
authors.initials: TM
authors.lastname: Gill
mesh_terms: D000367:Age Factors; D000368:Aged; D000465:Algorithms; D002908:Chronic Disease; D015331:Cohort Studies; D005260:Female; D016330:Frail Elderly; D015577:Geriatric Assessment; D006304:Health Status; D006801:Humans; D008297:Male; D010366:Peak Expiratory Flow Rate; D011237:Predictive Value of Tests; D018570:Risk Assessment