Akademik Veri Yönetim Sistemi
FEBS2025, İstanbul, Türkiye, 5 - 09 Temmuz 2025, cilt.15, sa.2, ss.479-480, (Tam Metin Bildiri)
Reference intervals (RIs) are crucial for the accurate interpretation of laboratory test results. The Clinical Laboratory Standards Institute (CLSI) recommends that each laboratory establish its own reference intervals based on the population it serves. Data mining techniques have made indirect methods more advantageous. The International Federation of Clinical Chemistry (IFCC) also supports the use of indirect reference interval. However, since the Endocrine Society recently withdrew its endorsement of specific thresholds of vitamin D [25(OH)D] for the general population, there is no universal consensus among the scientific community regarding optimal cutoff levels. Therefore, establishing RI for 25(OH)D has great importance. In this study 25(OH)D reference intervals were calculated using refineR and data collection preprocessing, model selection, and analysis processes were examined in detail. The derived reference intervals aim to provide a stronger foundation for clinical interpretation. This study analyzed 25(OH)D results that were routinely requested in our laboratory between January 1, 2022 and January 1, 2025. Test results were obtained from the Laboratory Information System. After filtering results for 24036 individuals were obtained. The median 25(OH)D concentration was 12.9 ng/mL (IQR: 8.91-18.8). According to the 2011 Endocrine Society criteria deficiency (≤20 ng/mL) was observed in 78.9%, insufficiency (21-29 ng/mL) in 16%, and sufficiency (≥30 ng/mL) in 5%. RI was calculated based on gender, age group, test request unit, and season. The manufacturer’s reference interval was 7.4-44 ng/mL. Reference intervals determined using refineR (Unit: ng/mL): Women: 4.55-31.1, Men: 4.7-31.7, 18-40 years: 4.41-28, 41-65 years: 4.7-31.3, 66-80 years: 7.26-37.3, Winter: 4.62- 26.2, Summer: 4.47-32.9, Autumn:5.45-34.7, Spring:4.58-24.8. This study shows that the reference interval provided by the manufacturer may not fully reflect the actual distribution of the population.