Indirect determination of hemoglobin A2 reference intervals in Pakistani infants using data mining
Abstract 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 f...
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2025-01-01
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| Online Access: | https://doi.org/10.1186/s12911-025-02857-4 |
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| author | Muhammad Shariq Shaikh Sibtain Ahmed Saba Farrukh Shahnawaz Bayunus |
| author_facet | Muhammad Shariq Shaikh Sibtain Ahmed Saba Farrukh Shahnawaz Bayunus |
| author_sort | Muhammad Shariq Shaikh |
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| description | Abstract 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. |
| format | Article |
| id | doaj-art-2e0c8e8869dd492bb1b18a0115bc1eaf |
| institution | Kabale University |
| issn | 1472-6947 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
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| series | BMC Medical Informatics and Decision Making |
| spelling | doaj-art-2e0c8e8869dd492bb1b18a0115bc1eaf2025-01-12T12:26:25ZengBMCBMC Medical Informatics and Decision Making1472-69472025-01-012511510.1186/s12911-025-02857-4Indirect determination of hemoglobin A2 reference intervals in Pakistani infants using data miningMuhammad Shariq Shaikh0Sibtain Ahmed1Saba Farrukh2Shahnawaz Bayunus3Department of Pathology and Laboratory Medicine, The Aga Khan University HospitalDepartment of Pathology and Laboratory Medicine, The Aga Khan University HospitalClinical Research Fellow, Leeds Teaching Hospitals NHS TrustDepartment of Pathology and Laboratory Medicine, The Aga Khan University HospitalAbstract 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.https://doi.org/10.1186/s12911-025-02857-4Data miningHemoglobin A2Reference intervalPakistanInfants |
| spellingShingle | Muhammad Shariq Shaikh Sibtain Ahmed Saba Farrukh Shahnawaz Bayunus Indirect determination of hemoglobin A2 reference intervals in Pakistani infants using data mining BMC Medical Informatics and Decision Making Data mining Hemoglobin A2 Reference interval Pakistan Infants |
| title | Indirect determination of hemoglobin A2 reference intervals in Pakistani infants using data mining |
| title_full | Indirect determination of hemoglobin A2 reference intervals in Pakistani infants using data mining |
| title_fullStr | Indirect determination of hemoglobin A2 reference intervals in Pakistani infants using data mining |
| title_full_unstemmed | Indirect determination of hemoglobin A2 reference intervals in Pakistani infants using data mining |
| title_short | Indirect determination of hemoglobin A2 reference intervals in Pakistani infants using data mining |
| title_sort | indirect determination of hemoglobin a2 reference intervals in pakistani infants using data mining |
| topic | Data mining Hemoglobin A2 Reference interval Pakistan Infants |
| url | https://doi.org/10.1186/s12911-025-02857-4 |
| work_keys_str_mv | AT muhammadshariqshaikh indirectdeterminationofhemoglobina2referenceintervalsinpakistaniinfantsusingdatamining AT sibtainahmed indirectdeterminationofhemoglobina2referenceintervalsinpakistaniinfantsusingdatamining AT sabafarrukh indirectdeterminationofhemoglobina2referenceintervalsinpakistaniinfantsusingdatamining AT shahnawazbayunus indirectdeterminationofhemoglobina2referenceintervalsinpakistaniinfantsusingdatamining |