Modelo de gestión impuesto por la transformación tecnológica en los laboratorios de análisis clínicos. Impacto en el Hospital Garrahan a treinta años de historia / Management model imposed by the technological transformation in clinical analysis laboratories. Impact at Hospital Garrahan on thirty years of history

Las actividades del laboratorio de análisis clínicos están fuertemente identificadas con el ritmo del cambio tecnológico. En los últimos treinta años se vive un cambio de época que afecta la cultura y la experiencia humana en todos sus aspectos. Este cambio modifico el modelo de producción. En el laboratorio ha incorporado tecnología que combina la química, la robótica, la óptica y la informática, y se ha impuesto como premisa externa de cambio un modelo de gestión global que afecta la forma de trabajo, la gestión y el rol de los profesionales (bioquímicos y técnicos). El hospital Garrahan inscribe su historia dentro de este periodo histórico y el proceso de cambio ha generado y genera incertidumbre, resistencia y adecuaciones al nuevo paradigma impuesto. Nos fijamos como objetivo analizar el impacto de este cambio sobre la gestión de procesos del laboratorio de nuestro hospital. Comprobamos que la demanda del laboratorio se incrementó al ritmo del crecimiento de consultas y egresos de pacientes, y de como este aumento demando adecuaciones de gestión, modificaciones arquitectónicas, incorporación de tecnologías (algunas emergentes), aumento en la trazabilidad de muestras y resultados, y mejoras en la seguridad del paciente en todos sus aspectos. Describimos el nuevo paradigma, sus ventajas, las adecuaciones hechas y los tiempos en que se fueron realizados. Concluimos sugiriendo un rol para los profesionales del laboratorio en función del paradigma en curso

Activities at the laboratory of clinical analysis are closely related to the pace of technological change. Over the past 30 years there has been a change of times affecting human culture and experience in all its aspects. This change has modified the model of production. The laboratory has incorporated technology combining chemistry, robotics, and optics, as well as information technology, and the premise of a global management model has been imposed affecting the way of working, administration, and the role of professionals (biochemists and technicians). Garrahan hospital has written its own history in this historical period and process of change has produced uncertainty, resistance as well as adaptation to this new paradigm. Our aim has been to analyze the impact of this change on the management of processes of the laboratory of our hospital. We have observed that the demand of the laboratory has increased at the same pace as the increase of patient visits and discharges. This increase has required modifications in the management and facilities, incorporation of new technologies (some of them state of the art), improved traceability of the samples and results, and improvements in patient safety in all aspects. Here we describe the new paradigm, its advantages, adaptations made, and improved times introduced. In our conclusions, we consider the new role for laboratory professionals in this paradigm.

Age-specific thyroid hormone and thyrotropin reference intervals for a pediatric and adolescent population.

BACKGROUND: Establishment of reliable reference intervals remains valuable for confirming validity and advancing standardization across methods and populations. Moreover, knowledge of the measurement uncertainty (U) and of the reference change value (RCV) has important applications in clinical chemistry. METHODS: Starting from the information available in the laboratory data base (29,901 subjects) an initial selection was carried out by eliminating all subjects with a clinical or laboratory pathological report; data from 7581 0- to 20-year-old subjects (53.87% girls) remained in the study. These subjects, divided into nine age groups, were used to define reference distribution percentiles (2.5th, 50th and 97.5th) of serum thyrotropin (TSH), triiodothyronine (T3), thyroxine (T4), and free T4 (fT4), as well as U and RCV of these assays. RESULTS: In early infancy, T4 and fT4 values were higher than in the older age groups. Serum T4 95th percentile reference value, useful for the diagnosis of hyperthyroidism, was 142.9 in 20-year-old boys and 230.4 nmol/L in early infants and serum T3 95th percentile was 2.6 and 3.5 nmol/L, respectively, while fT4 2.5th percentile reference value, useful for the diagnosis of hypothyroidism, was 9.6 and 13.0 pmol/L, respectively. Serum TSH 97.5th percentile showed less age variation, 4.38-4.88 mIU/L. Performance of the four assays resulted in approximately 20% Us, reflecting simple and complex imprecision, trueness, analytical and functional sensitivity. RCV of serum TSH (58.6%) was larger than for thyroid hormones (28.3%-34.7%), probably due to the high biological variation of this hormone. CONCLUSIONS: We have established reference interval for TSH and thyroid hormones, as well as Us for assessing reliability of measurements, and RCVs to alert users on the presence of clinical significant changes.

Is BaF3 bioassay useful to identify patients with bioinactive growth hormone?

We analyzed the ability of the BaF3 cell line bioassay to select patients with biologically inactive GH. We first evaluated the biological response of the Ba/F3-hGHR cells to rhGH additional doses from 10 to 5000 pg/ml. The concentration points corresponding to the linear part of the curve were selected. We then analyzed a group of sera, diluted like the standard, including the entire range of GH concentrations that can be analyzed by bioassay. The serum/standard area below the curve ratio was calculated. Serum GH immunoactivity determined by IMMULITE/GH bioactivity ratios was calculated. Our experimental data showed that GH-bioactivity/GH-immunoactivity ratios below 0.303 are indicative of a bioinactive GH molecule. This bioassay would recognize only extreme cases of GH bioinactivity, and it would not be a useful tool in the search for patients with altered forms of GH.

[Presence of early risk markers of metabolic syndrome in prepubertal children with a history of intrauterine growth restriction]. / Marcadores tempranos de riesgo de síndrome metabólico en niños prepúberes con y sin antecedente de restricción de crecimiento intrauterino.

INTRODUCTION: Studies on people with low birth weight found metabolic syndrome associated with intrauterine growth restriction (IUGR). OBJECTIVE: To study the presence of early risk markers of metabolic syndrome in a prepubertal population with IUGR. DESIGN: We studied 45 prepubertal children with a history of IUGR, without apparent disease, and 47 children in a control group. BMI, weight, height, and BMI Z score, and body fat mass were calculated. Basal glycemia, insulin, proinsulin, cortisol, serum lipids and uric acid levels were analyzed. Insulin sensitivity was calculated by QUICKI and insulin resistance by HOMA-IR. RESULTS: Basal insulin levels were higher in the IUGR group compared with the controls (6.6 microU/ml vs. 4.4 microU/ml; p= 0.008). Similar results were found for the basal cortisol levels (18.8 ug/dl vs. 13.1 ug/dl; p= 0.006) and uric acid (4.2 mg/dl vs. 2.7 mg/dl; p= 0.0008). QUICKI index was lower in the IUGR group (2.06 vs. 2.86, p= 0.001). The IUGR children who developed obesity presented higher levels of proinsulin (26.04 ug/dl vs. 13.3 ug/dl; p= 0.05), insulin (11 microU/ml vs. 5.5 microU/ml, p= 0.005), and HOMA-IR (2.06 vs. 0.9, p= 0.004), and lower QUICKI (1.71 vs. 2.16, p= 0.01) than in the case of the IUGR children with appropriate weight; these differences weren't observed among the control group. CONCLUSIONS: Children with IUGR, without apparent disease, showed metabolic changes that were expressed through risk markers of metabolic syndrome in childhood.

Marcadores tempranos de riesgo de síndrome metabólico en niños prepúberes con y sin antecedente de restricción de crecimiento intrauterino / Presence of early risk markers of metabolic syndrome in prepubertal children with a history of intrauterine growth restriction

Introducción. Varios estudios comunican la asociación entre el síndrome metabólico y la restricción de crecimiento intrauterino (RCIU). Objetivo. Estudiar la presencia de marcadores de riesgo tempranos de síndrome metabólico en una población de niños prepuberales con antecedentede RCIU y sin él. Material y métodos. Fueron estudiados 45 niños con antecedente de RCIU sin enfermedad aparente y 47 niños como grupo control. Se evaluaron peso, talla, índice de masa corporal, puntaje Z de índice de masa corporal y masa grasa. Se midieron glucemia basal, insulina, proinsulina, cortisol, lípidos y ácido úrico. La sensibilidad insulínica fue calculada por QUICKI y la resistenciapor HOMA-IR. Resultados. Los niveles de insulina basal fueron mayores en los niños con RCIU que en los controles(6,6 μU/ml contra 4,4 μU/ml; p= 0,008). Se encontraron resultados similares en los niveles de cortisol (18,8 ug/dl contra 13,1 ug/dl; p= 0,006) y ácido úrico (4,2 mg/dl contra 2,7 mg/dl;p= 0,0008). El índice QUICKI fue menor en los niños con RCIU (2,06 contra 2,86; p= 0,001). El grupo de RCIU con obesidad presentó niveles mayores de proinsulina (26,04 ug/dl contra 13,3ug/dl; p= 0,05), insulina (11 μU/ml contra 5,5 μU/ml; p= 0,005), y HOMA-IR (2,06 contra 0,9; p= 0,004), y menor QUICKI (1,71 contra 2,16; p= 0,01) que los niños con RCIU y peso adecuado; estas diferencias no se observaron entre los niños del grupo control. Conclusiones. Los niños con antecedente de RCIU presentaron cambios metabólicos expresados en las variables de riesgo de síndrome metabólico.