RESUMEN
Background: Acylcarnitine is one of the crucial markers of fatty acid metabolism, and examination of their level in infants can reveal several Inherited Metabolic Disorders (IDM) or Inborn errors of Metabolism (IEM). Because of the great importance of hereditary, metabolic, and other inherited disorders early diagnosis before the appearance of clinical symptoms, this study was carried out to establish a reference range for carnitine analytes and to identify acylcarnitine profiles in normal weight neonatal dried blood spots (DBS) specimens. Methods: By using liquid chromatography tandem mass spectrometry (LC-MS/MS) for neonatal screening and eventually the examination and analysis of LC-MS/MS results, 34 acylcarnitine derivatives were identified. Results: The normal range for acylcarnitine analytes with carbon numbers ranging from zero to 18, both main and the branched ones, were ultimately measured. Afterward, they were compared with the results of some other diagnostic laboratories to be verified. Conclusions: This study differed from the other findings, which could be due to diversity in population and work methods. However, the reference range of most acylcarnitine derivatives in Tehran closely aligned with this study's findings.
RESUMEN
INTRODUCTION: Indirect methods for reference interval (RI) establishment apply statistical techniques to generate RIs for test result interpretation using stored laboratory data. They present unique advantages relative to traditional direct approaches such as fewer resource requirements; however, there is debate regarding their performance. Herein, we aimed to compare indirect and direct approaches for RI establishment by harnessing data from the Isfahan Cohort Study (ICS). This cohort includes both healthy individuals and those with a history of disease, enabling a direct comparison. METHODS: Participants were recruited as part of ICS, including 6504 adults aged 34 years and older. Sociodemographic characteristics, anthropometry, blood pressure, various biochemical indices, and hematology parameters were collected. The refineR method was used to establish indirect RIs (before applying exclusion criteria). Direct RIs were calculated using nonparametric methods per CLSI EP28-A3 guidelines (after applying exclusion criteria). Bias ratios were calculated for each parameter to assess significant differences in estimations. RESULTS: Direct and indirect RI estimations for most hematological and biochemical parameters were comparable. Statistically significant bias ratios between methods were observed for the upper limits of total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C), hemoglobin (female), and platelet count as well as the lower limits of mean corpuscular hemoglobin (female), mean corpuscular volume, hemoglobin, and hematocrit (female). CONCLUSION: Data presented indicate RIs derived from direct and indirect approaches are similar, but not identical. Further work should focus on the clinical significance of such differences as well as the investigation of necessary data-cleaning criteria before indirect method application.
