Methods/Design: This is to be a randomized, multicentre, open-label clinical trial. A total of 444 smokers over 40 years of age will be recruited by 39 general practitioners from 22 health centers ...

Introduction Grouped together the many different lung conditions are the third largest killer in the UK. The direct cost of lung conditions to the NHS was estimated to be £9.6 billion in 2019, with £1 ...

Your results will be compared to predicted values based on your age, height, gender, and ethnicity. A normal spirometry test typically shows FEV1 and FVC values that are 80% or more of the predicted ...

We determined specific IgE, and lung function using spirometry and body plethysmography according to the ATS criteria. The results were compared with the reference values of the Global Lung Initiative ...

For example, lower FVC values indicate restricted breathing and lower FEV1 readings indicate bronchial obstruction. In healthy people, the FEV1/FVC ratio is 70 to 80 percent. If values are lower than ...

Stage 1: This is when your FEV1 is equal to or greater than the predicted normal and your FEV1/FVC ratio is less than 70%. Your symptoms are likely to be very mild or even unnoticeable. Stage 2 ...

Adopting risk-based lower-limit-of-normal (LLN) spirometry thresholds may reduce the number of false negatives and positives patients receive, according to study findings published in the Annals of ...

The measurements of FEV1, forced vital capacity (FVC), and their ratio are routinely performed in millions of patients every year to diagnose and follow up obstructive and restrictive pulmonary ...

Doctors calculate the results of a spirometry test as a percentage of the “normal” value for someone of your height, age, sex, and race. For example, if your FEV1 is 80%, this means that you ...

International guidelines recommend the use of spirometry indices, specifically the pre- and post-bronchodilator test (BDT) forced expiratory volume in the first second (FEV1), forced vital capacity ...

The objective of this study was to train a supervised ML model to predict TLC values using patient characteristics and data from spirometry. The secondary objective was to investigate whether these ...