A study on the correlation between clinical features, spirometry and ABG in acute exacerbation of obstructive lung diseases

Abstract

Background: Obstructive lung diseases are those characterized by limitation of expiration of air from lungs, which may occur due to narrowing of airways or damage to the lungs. They include COPD, bronchial asthma, bronchiectasis and cystic fibrosis. These illnesses are punctuated by “exacerbations”, which are acute episodes of worsening of symptoms including cough, breathlessness and increased sputum production. The degree of airflow impairment may be assessed using bedside spirometry, especially the measures of expiratory function like forced expiratory volume in one second (FEV1), forced vital capacity (FVC) and the ratio FEV1/FVC. The impairment in gas exchange resulting from obstructive pathology can be assessed using arterial blood gas analysis (ABG). Our study aims to employ ABG and spirometry to assess the degree of impairment in 50 patients admitted with acute exacerbation of obstructive lung diseases in our tertiary care hospital in rural South India. The present study also aims to identify any correlation between clinical features and values of ABG and spirometry, to assess if FEV1 values can help predict requirement of ABG, if ABG values can predict onset of respiratory failure before overt symptoms appear, and to identify if change in pH levels with pCO2 can be used as a predictive marker for respiratory failure. Methods: We studied clinical features and ABG values and spirometry values on admission and on discharge in 50 patients admitted to Rajah Muthiah Medical college between September 2019 – October 2021. Results: An admission pH of less than 7.20, a pCO2 of more than 60 and a pO2 of less than 60 and FEV1 of less than 68% of normal are the major factors associated with respiratory failure. Conclusions: There is a correlation between FEV1 and pCO2 [p value 0.09] in determining severity of acute exacerbation of obstructive lung disease. Combining spirometric criteria with clinical criteria increases specificity and overall accuracy in predicting respiratory failure.