Indirect determination of hemoglobin A2 reference intervals in Pakistani infants using data mining.

BACKGROUND

Reference intervals (RIs) are crucial for distinguishing healthy from sick individuals and vary across age groups. Hemoglobinopathies are common in Pakistan, making the quantification of hemoglobin variants essential for screening. Direct RIs are established by measuring values from a healthy reference population, whereas indirect RIs, use statistical analysis of routine lab data to estimate values, making it feasible in settings where direct data is unavailable. Since Pakistan lacks locally established Hemoglobin A2 RIs for infants, this study aims to fill that gap using an indirect data mining method to improve diagnostic accuracy for hemoglobinopathies.

METHODS

It was a retrospective observational study. Hemoglobin A2 measurements from all patients aged birth to 1 year between January 2015 and December 2022 were retrieved from the laboratory management system at Aga Khan University Hospital. The study population represented the entire geographical distribution of the country. Hemoglobin A2 was measured using the Bio-Rad Variant™ II analyzer. RIs were computed using an indirect KOSMIC algorithm, which assumes non-pathologic samples follow a Gaussian distribution after Box-Cox transformation.

RESULTS

A total of 88,690 specimens were analyzed for HbA2. After excluding patients with multiple specimens, RIs were calculated for 22,713 infants, stratified into five age sub-groups. The 2.5th and 97.5th percentile results showed good agreement with RIs from Mayo Clinic Laboratories.

CONCLUSIONS

This study supports data mining as an alternative method for establishing HbA2 RIs, especially in resource-limited settings. The results are specific to the studied population, instrument, and reagent, and they elucidate the fluctuations in HbA2 synthesis with age. These intervals will enhance clinical decision-making based on HbA2 results.