"Breath of Difference: Comparing Global Lung Function Prediction Models for Indian Children"

Use of these equations results in misinterpretation & misdiagnosis which will affect the selection of treatment strategies and ultimately affect patient recovery & rehabilitation. Hence, the study was designed to establish reference values and prediction equations for lung function in children living in Maharashtra India and compare PFT parameters over different age groups & in subjects from different regions of India and other countries.

An observational cross-sectional study with a multistage cluster randomized sampling method was carried out. The study was conducted as per standardized STROBE guidelines. Standing Height, weight, age, BMI & body surface area were documented. PFT was performed as per ATS guidelines at BTPS. Simple regression & multivariate regression analysis was done by using IBM SPSS statistical software. Models were analyzed with diagnostic F test & significance by ANNOVA. 

There is a significant relation between the anthropometric indices lung function parameters in the children living in India. There are regional differences in lung function in children in India. The prediction of lung function by using anthropometric parameters as a predictor in children living in Maharashtra are different than the lung function prediction equations published nationally & internationally. There is a difference in lung function between children living in Maharashtra & children of other states of India, and other countries, hence one equation cannot be used for all populations. Boys have higher lung function parameter values than girls. North Indian children have higher PFT parameter values than Indian & Asian children. Caucasian children have higher PFT parameter values than Indian & Asian children.

Variations in lung function across the country & world can be explained by anthropometric, genetic, environmental, and nutritional status in children. All the anthropometric parameters correlate well with the lung function parameter.  Weight has the highest correlation with most of the PFT parameters in growing child. Age, height, body size & weight go hand in hand in growing children, hence individual effects of anthropometric parameters can’t be differentiated. Hence, Multivariate regression models are recommended for prediction of lung function. Growth patterns are different in boys & girls hence separate prediction equations are recommended.

These equations can prevent misdiagnosis, miss-interpretation & wrong categorization of lung disease in children.  This study challenges the existing practice of use of Caucasian equations for PFT interpretation in Indian children. This study discourages the use of adult equations to pediatric population.. These pediatric models will provide accurate prediction equations for spirometric interpretation for accurate diagnosis / early diagnosis. This study endorse the need to establish local prediction equations.