RESUMO
Background: Chronic obstructive pulmonary disease (COPD) case-finding aims to detect airflow obstruction in symptomatic smokers and ex-smokers. We used a clinical algorithm including smoking, symptoms, and spirometry to classify smokers into COPD risk phenotypes. In addition, we evaluated the acceptability and effectiveness of including smoking cessation advice in the case-finding intervention. Methods: Smoking, symptoms, and spirometry abnormalities (airflow obstruction: forced expiratory volume in 1 second [FEV1] to forced vital capacity [FVC] <0.7 or preserved-ratio spirometry (FEV1<80% of predicted value and FEV1/FVC ratio ≥ 0.7)] were assessed in a group of 864 smokers aged ≥ 30 years. The combination of these parameters allowed the identification of 4 phenotypes: Phenotype A (no symptoms, normal spirometry; reference), Phenotype B (symptoms; normal spirometry; possible COPD), Phenotype C (no symptoms; abnormal spirometry; possible COPD), and Phenotype D (symptoms; abnormal spirometry; probable COPD). We assessed phenotype differences in clinical variables and modeled the trend from phenotype A to phenotype D. Smoking cessation advice based on spirometry was provided. Follow-up was done by telephone 3 months later. Results: Using smokers without symptoms or abnormal spirometry (phenotype A; n=212 [24.5%]) as a reference, smokers were classified into possible COPD (phenotype B;n=332 [38.4%]; and C: n=81 [9.4%]) and probable COPD (phenotype D: n=239 [27.2%]). The trend from baseline phenotype A to probable COPD phenotype D was significant for the number of cigarettes/day and the number of years of smoking (p=0.0001). At follow-up, 58 (7.7%) of the respondents (n=749) reported that they had quit smoking. Conclusions: Our clinical algorithm allowed us to classify smokers into COPD phenotypes whose manifestations were associated with smoking intensity and to significantly increase the number of smokers screened for COPD. Smoking cessation advice was well accepted, resulting in a low but clinically significant quit rate.
RESUMO
BACKGROUND: Different case finding approaches have been used to identify early COPD. The objective of this study was to assess the feasibility and the yield of opportunistic early COPD case finding in visitors to a large medical centre. PATIENTS AND METHODS: From May 2014 to June 2017, we consecutively recruited adults aged ≥ 18 years visiting the Shaare Zedek Medical Center, in Jerusalem. Our 3-step intervention included: a) pre-screening for symptoms with the 5-item "Could it be COPD?" questionnaire (score= 0-5 pts); b) pre-BD spirometry; and c) referral to a caregiver. Airflow obstruction was defined by a FEV1/FVC < 0.7. Spirometry results were used as an incentive to promote smoking cessation and quit rates were verified by phone survey 3 months after the intervention. RESULTS: A total of 1001 subjects (956 smokers; 45 ex-smokers) were recruited. Mean (SD) age was 48.3 years (13.5). Airflow obstruction was detected in 180 (18%) subjects of whom 142 (78.9%) were unaware of it, including 27 subjects with severe (50% ≥ FEV1 ≤ 30% predicted) (n=25) or very severe (FEV1 < 30% predicted) (n=2) obstruction. Multiple logistic regression analysis found that age, BMI, cigarette smoking (p.y.) and a "Could it be COPD?" questionnaire score ≥ 3 points correctly classified 83.3% of cases of airflow obstruction. At follow-up, 54.5% of participants reported smoking as usual, 30.9% reduced smoking [mean (SD) = 10.1 ± 7.8 cigarettes/day], 7.4% increased smoking [mean (SD) = 9.2 ± 6.3 cigarettes/day] and 7.2% claimed smoking cessation. Among obstructed subjects, 38.7% had visited a physician because of COPD, while 20.7% were taking a new respiratory medication. CONCLUSION: Early COPD case finding was feasible and effective in identifying undiagnosed airflow obstruction among visitors to a medical centre. Smoking cessation counselling based on spirometry promoted a small but clinically meaningful cessation rate.