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Development of a Nomogram for Peak Nasal Inspiratory Flow Among Indian Children: A Hospital-Based Observational Study
Samya Mitra1, Nihar R Mishra1, Ritesh Singh2
1Pediatrics, All India Institute of Medical Sciences (AIIMS), Kalyani, IND.
Objective:
This study aimed to develop a nomogram for the peak nasal inspiratory flow (PNIF) meter among Indian children and to determine the cutoff value of peak nasal inspiratory flow to detect allergic rhinitis and the blocker variety, as well as to look for differences in PNIF value among age groups.
Methods:
A cross-sectional study was conducted in the pediatric outpatient department of a tertiary hospital among children aged six to 17 years. The PNIF data were obtained along with demographic variables. Children were diagnosed with allergic rhinitis, with or without blockage symptoms, according to the Allergic Rhinitis and its Impact on Asthma (ARIA) classification. A total of 573 children were included after applying the exclusion criteria. Data analysis was done using SPSS Statistics version 25 (IBM Corp., Armonk, NY, USA) and Dxt version 1.0 (Biostatistics Resource and Training Centre, Christian Medical College Vellore, TN, IND).
Results:
The mean PNIF value of all age groups was 67.95 L/min (standard deviation 13.46). The PNIF has a statistically significant but weak correlation with age and a statistically significant difference between age groups. Cutoff values for both allergic rhinitis and blocker varieties were 65 L/min, with varying sensitivity and specificity across age groups. Multiple linear regression analysis derived the equation for PNIF = 53.061 + (1.689 × age) + (1.312 × gender) + (-0.015 × BMI).
Conclusion:
The PNIF with set cutoff values can be used to diagnose allergic rhinitis and the blocker variety in Indian children. It can be used as a diagnostic tool to determine allergic rhinitis with modest diagnostic accuracy in the six to nine-year and 13 to 17-year age groups. For children more than 10 years of age, PNIF demonstrates clinical utility in determining the obstructive nasal phenotype.
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