Sex and age affect agreement between fasting plasma glucose and glycosylated hemoglobin for diagnosis of dysglycemia / El sexo y la edad afectan la concordancia entre glucemia basal y hemoglobina glicada para el diagnóstico de disglucemia

Aim: To assess agreement between fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) levels for diagnosis of dysglycemia (diabetes and risk of diabetes), overall and depending on clinical characteristics. Methods: The study enrolled 1020 adult subjects without drug-treated diabetes who underwent a laboratory test at a Spanish health care center. The criteria for dysglycemia of the American Diabetes Association were used. A logistic regression analysis was used to predict de novo diagnosis of dysglycemia based on sex, age, body mass index, anemia, and iron levels. Results: Overall prevalence of dysglycemia was 28.04%, and was identified by FPG only in 13.63% of subjects, by both FPG and HbA1c in 7.65%, and by HbA1c only in 6.76% (de novo diagnoses). Independent predictors of de novo diagnoses based on HbA1c were female sex (odds ratio [OR]: 2.119, 95% confidence interval [CI]: 1.133-4.020; p<0.020), age (OR for 42-56 years: 2.541, 95% CI: 0.634-17.140; OR for ≥57 years: 5.656, 95% CI: 1.516-36.980; overall p<0.007), and serum ferritin levels (borderline significance). Conclusions: In this study population, agreement between FPG and HbA1c for diagnosis of dysglycemia was poor, with FPG being the test that identified more subjects. De novo diagnoses based on HbA1c were more common in females and increased with age (AU)

Objetivo: Evaluar la concordancia entre el diagnóstico de disglucemia (diabetes y riesgo de diabetes) realizado por glucemia basal (GB) y hemoglobina A1c (HbA1c), globalmente y según características clínicas. Métodos: El estudio incluyó a 1.020 sujetos adultos con diabetes no tratada con fármacos que realizaron una prueba de laboratorio en un centro de salud español. Los criterios de disglucemia fueron los de la American Diabetes Association. Se utilizó un análisis de regresión logística para predecir un nuevo diagnóstico de disglucemia a partir del sexo, edad, índice de masa corporal, presencia de anemia y estatus férrico. Resultados: La prevalencia global de disglucemia fue del 28,04%, identificada únicamente por GB en el 13,63% de los sujetos, por GB y HbA1c en el 7,65% y solo por HbA1c en el 6,76% (nuevos diagnósticos). Los predictores independientes de nuevo diagnóstico según HbA1c fueron el sexo femenino (odds ratio [OR]: 2,119; intervalo de confianza [IC] 95%: 1,133-4,020; p<0,020), la edad (OR para 42-56 años: 2,541; IC 95%: 0,634-17,140; OR para ≥57 años: 5,656, IC 95%: 1,516-36,980; p<0,007 en general) y la ferritina sérica (significación límite). Conclusiones: En esta población la concordancia entre GB y HbA1c para el diagnóstico de disglucemia es pobre; la GB es la prueba que identifica más sujetos. Los nuevos diagnósticos por HbA1c se realizan con mayor frecuencia en mujeres y aumentan con la edad (AU)

Sex and age affect agreement between fasting plasma glucose and glycosylated hemoglobin for diagnosis of dysglycemia.

AIM: To assess agreement between fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) levels for diagnosis of dysglycemia (diabetes and risk of diabetes), overall and depending on clinical characteristics. METHODS: The study enrolled 1020 adult subjects without drug-treated diabetes who underwent a laboratory test at a Spanish health care center. The criteria for dysglycemia of the American Diabetes Association were used. A logistic regression analysis was used to predict de novo diagnosis of dysglycemia based on sex, age, body mass index, anemia, and iron levels. RESULTS: Overall prevalence of dysglycemia was 28.04%, and was identified by FPG only in 13.63% of subjects, by both FPG and HbA1c in 7.65%, and by HbA1c only in 6.76% (de novo diagnoses). Independent predictors of de novo diagnoses based on HbA1c were female sex (odds ratio [OR]: 2.119, 95% confidence interval [CI]: 1.133-4.020; p<0.020), age (OR for 42-56 years: 2.541, 95% CI: 0.634-17.140; OR for ≥57 years: 5.656, 95% CI: 1.516-36.980; overall p<0.007), and serum ferritin levels (borderline significance). CONCLUSIONS: In this study population, agreement between FPG and HbA1c for diagnosis of dysglycemia was poor, with FPG being the test that identified more subjects. De novo diagnoses based on HbA1c were more common in females and increased with age.

Effects of hemoglobin variants on hemoglobin a1c values measured using a high-performance liquid chromatography method.

Hemoglobin A1c (HbA1c) is routinely used to monitor long-term glycemic control and for diagnosing diabetes mellitus. However, hemoglobin (Hb) gene variants/modifications can affect the accuracy of some methods. The potential effect of Hb variants on HbA1c measurements was investigated using a high-performance liquid chromatography (HPLC) method compared with an immunoturbimetric assay. Fasting plasma glucose (FPG) and HbA1c levels were measured in 42 371 blood samples. Samples producing abnormal chromatograms were further analyzed to characterize any Hb variants. Fructosamine levels were determined in place of HbA1c levels when unstable Hb variants were identified. Abnormal HPLC chromatograms were obtained for 160 of 42 371 samples. In 26 samples HbS was identified and HbA1c results correlated with FPG. In the remaining 134 samples HbD, Hb Louisville, Hb Las Palmas, Hb N-Baltimore, or Hb Porto Alegre were identified and HbA1c did not correlate with FPG. These samples were retested using an immunoturbidimetric assay and the majority of results were accurate; only 3 (with the unstable Hb Louisville trait) gave aberrant HbA1c results. Hb variants can affect determination of HbA1c levels with some methods. Laboratories should be aware of Hb variants occurring locally and choose an appropriate HbA1c testing method.

Comparación entre 2 sistemas analíticos para la determinación de la hemoglobina A1c: inmunoturbidimetría versus cromatografía líquida de alta eficiencia / Comparison of 2 analytical systems for hemoglobin A1c: An immunoturbidimetric method versus high performance liquid chromatography

Introducción. La hemoglobina A1c (HbA1c) es ampliamente utilizada en la determinación del estado glucémico de pacientes con diabetes mellitus. El objetivo de este estudio fue comparar 2 métodos automatizados para medir HbA1c basados en diferentes principios de medida, evaluar la correlación entre ambos y su practicabilidad. Métodos. Se analizaron 622 muestras mediante 2 sistemas analíticos con fundamentos diferentes de medición: cromatografía líquida de alta eficiencia (HPLC) (analizador ADAMS A1c HA-8160; A. Menarini Diagnostics, Italia) e inmunoturbidimetría (Tina-quant Hemoglobin A1c Gen.3, plataforma Cobas 6000; Roche Diagnostics, Suiza). Ambos métodos fueron calibrados según el procedimiento de referencia de la IFCC. Se valoró la correlación entre ambos métodos mediante los análisis de regresión de mínimos cuadrados y Passing-Bablok (R programa v.2.11.1). También se registró el tiempo de puesta en marcha, las tareas de mantenimiento diario y el rendimiento de los 2 instrumentos. Resultados. La correlación fue muy alta tanto por mínimos cuadrados (ordenada en el origen 0.05, pendiente 0.98) como en Passing-Bablok (ordenada en el origen 0,10, pendiente 1,00). El tiempo invertido diariamente para la puesta en marcha del analizador HA-8160 fue de 25 min y el tiempo de finalización fue de 15 min. Las tareas de mantenimiento del Cobas 6000 al inicio y fin del día son procesos automatizados. El rendimiento de los analizadores fue 20 muestras/h en el HA-8160 y 100 muestras/h en el Cobas 6000. El sistema analítico cuyo principio de medida es HPLC incluye también el análisis manual de cada cromatograma. Conclusiones. Existe una correlación excelente entre los métodos de HPLC e inmunoturbidimétrico. La ventaja del sistema analítico que utiliza la inmunoturbidimetría es la optimización del tiempo de procesamiento de las determinaciones de HbA1c, lo que reduce el coste unitario de la prueba (AU)

Introduction. Hemoglobin A1c (HbA1c) is widely used to assess glycemic status in patients with diabetes mellitus. The purpose of this study was to compare 2 automated analytical systems to measure HbA1c that use different measurement principles, evaluating the correlation between the two methods, as well as their ease of use. Methods. A total of 622 samples were analyzed using 2 methods: high performance liquid chromatography (HPLC) (analyzer ADAMS A1c HA-8160; A. Menarini Diagnostics, Italy) and an immunoturbidimetric assay (Tina-quant Hemoglobin A1c Gen.3, Cobas 6000 analyzer; Roche Diagnostics, Switzerland). Both methods were calibrated in accordance with IFCC reference measurement procedure. The correlation between the two methods was assessed by least squares and Passing-Bablok linear regression analyses (R program v.2.11.1). The daily start-up time of the 2 instruments used, daily maintenance tasks, and determination of throughput were also recorded. Results. There was a strong correlation between the results generated by the two test methods using both the least squares (intercept 0.54; slope 0.98) and Passing-Bablok (intercept 0.10; slope 1.00) regression methods. The time spent daily for the start-up of the HA-8160 analyzer was 25 min and completion time was 15 min. Maintenance tasks for the Cobas 6000 analyzer at the beginning and end of the day are automated processes. The throughput for the HA-8160 analyzer was 20 samples/h, and 100 samples/h for the Cobas 6000 analyzer. The HPLC method also included a time-consuming manual analysis of each chromatogram. Conclusions. An excellent correlation was observed between the HPLC and immunoturbidimetric methods. The advantages of the immunoturbidimetric method are optimization of processing time of HbA1c tests and a reduction in the unit cost per test (AU)