PURPOSE: To determine factors that influence interpretability rates of screening spirometries obtained in community settings. Widespread spirometric testing has been advocated to diagnose early chronic obstructive pulmonary disease. There is little information on the efficacy of mass screening spirometry performed in community settings.
METHODS: Two cohorts were studied: 1) Cohort P were 1819 subjects presenting to a national pharmacy chain for a “free lung test” to rule out COPD. They were tested by 55 volunteer respiratory care practitioners who had received four hours of training. 2) Cohort S who were 350 subjects presenting to local schools to rule out asthma. They were tested by 7 lay research assistants who had completed 16 hours of a NIOSH spirometry. The spirometry studies were read by independent pulmonologists according to ATS 1994 acceptability and reproducibility criteria.
RESULTS: 36% of Cohort P were male as were 22% of Cohort S. Cohort P had a mean age of 58 compared to 31 in Cohort S. 70% of the studies in Cohort A were interpretable and 90% of studies in Cohort B (p < 0.001). Heavier individuals were more likely to have interpretable spirometries, BMI of 29 kg/m2 versus 27 kg/m2 (p < .001). Binary logistic regression analysis showed subjects tested by personnel who had received 16 hours training and who averaged > 50 studies per person had the highest predictive power for interpretability vs personnel who had 4 hours of training and averaged < 12 studies per person. In Cohort P, female gender and higher BMI were associated with interpretability whereas age and smoking status were not significant. In Cohort S, male gender was the only predictor of interpretability.
CONCLUSION: Large scale screening can be performed successfully in community settings with interpretability rates of greater than 70%. The number hours of training and the number of studies performed per technician appear to be more important than patient characteristics.
CLINICAL IMPLICATIONS: Large scale spirometric screening programs may provide useful data even when performed in non-clinical settings.
DISCLOSURE: David Angulo, None.