Spirometry Case Study

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INTRODUCTION Evaluation of pulmonary function by spirometry is the most important tool for clinical assessment of respiratory functions.[1,2] For maintaining the reliability of pulmonary function evaluation, population‑specific reference values are required.[3,4] There is a significant difference in these values due to heritable, environmental, and ethnic differences of the studied population.[5,6] Smoking has been linked to a number of respiratory diseases including chronic obstructive pulmonary disease, lung cancer or cancers of the airways, and bronchial asthma. Smoking is the main cause of lung cancer which is considered the first leading cause of cancer death in men and the second to understand how low their lung function is. Hence, comparing…show more content…
Subjects rested for 15 min before measurements and were briefed about the procedure. After appropriate placement of mouthpiece and nose clip, a powerful, quick, forced expiration was performed following maximum forced inhalation. By doing at least three technically appropriate measurements, the highest value was recorded as the baseline value. All volumes were reported in body temperature and pressure saturated.[15] All tests were done by an experienced technician. Lung age calculation Spirometry determines the lung age (another way to look at the effect of smoking on lung function),[9] which is computed by matching an individual’s FEV1 value with the age at which that FEV1 value is considered normal based on predicted values. If a 6‑foot, a 47‑year‑old man has an FEV1 of 2.2, for example, his lung age is 72 because 2.2 is the FEVI measurement considered normal for a 72‑year‑old man of that height. Calculating a patient’s lung age can be a motivator in smoking cessation.[9] Calculation of lung age was based on estimates developed by Morris and Temple.[9] Lung age (men) =2.87 × height (in…show more content…
Nonsmokers were defined as participants who had not smoked at all or who had smoked fewer than 100 cigarettes during their lifetime.[18] Statistical analysis of data SPSS version 22 (SPSS Software Inc., Chicago, IL, USA) was used for data analysis. The data were presented as a mean ± standard deviation. The normality test was performed using Kolmogorov–Smirnov test. Independent t‑test was applied to compare the measured general characteristics and respiratory values between control and smokers. Pearson’s correlation test was used to determine the relationship between the pulmonary functions and lung age and study variables. The relationship between pulmonary functions and lung age (as dependent variables) and other variables (as the independent variables) was analyzed using the linear regression analysis. Stepwise multiple regression analysis in the whole study sample to assess the effect of smoking as a predictor determining lung age values was used. Level of significance was set at P < 0.05. RESULTS General characteristics of the

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