El rastreo masivo de datos es una segunda oportunidad para mejorar el manejo de los pacientes con fenotipo de hipercolesterolemia familiar / Massive data screening is a second opportunity to improve the management of patients with familial hypercholesterolemia phenotype

Introducción: La Hipercolesterolemia Familiar (HF) es una enfermedad autósómica dominante con una prevalencia estimada entre 1/200-250. Se encuentra infra-tratada e infra-diagnosticada. El rastreo masivo de datos puede incrementar la detección de pacientes con HF. Métodos: Población a estudio: Residentes en la zona sanitaria de cobertura (N: 195.000 habitantes) y con al menos una determinación de colesterol ligado a lipoproteínas de baja densidad (C-LDL) realizada entre el 1 de Enero de 2010 y el 30 de Diciembre de 2019. Se seleccionaron los valores más altos de C-LDL. Criterios de exclusión: síndrome nefrótico, hipotiroidismo, tratamiento hipotiroideo o triglicéridos > 400 mg/dL. Se analizaron 7 algoritmos sugestivos de fenotipo de Hipercolesterolemia Familiar (F-HF).Se seleccionó el algoritmo más eficaz y de fácil traslación a la práctica clínica. Resultados: Partiendo de 6.264.877 asistencias y 288.475 pacientes tras aplicar los criterios de inclusión-exclusión se incluyeron 504.316 analíticas correspondiendo a 106.382 adultos y 10.509 < 18 años. El algoritmo seleccionado presentó una prevalencia de 0.62%.Se detectaron 840 pacientes con fenotipo de Hipercolestereolemia Familiar (F-HF) siendo el 55.8% mujeres y 178 <18 años, El 9.3% tenían antecedentes de enfermedad cardio-vascular (ECV) y 16.4% habían fallecido. El 65% de los pacientes en prevención primaria presentaron valores de C-LDL >130 mg/dL y el 83% en prevención secundaria valores >70mg/dL. Se obtuvo una ratio de 7.64 (1-18) pacientes con HF-P por médico solicitante de analítica.Conclusiones: El rastreo masivo de datos y el perfilado de pacientes son herramientas eficaces y fácilmente aplicables en práctica clínica para la detección de pacientes con HF.(AU)

Introduction: Familial Hypercholesterolemia (FH) is an autosomal dominant disease with an estimated prevalence between 1/200-250. It is under-treated and underdiagnosed. Massive data screening can increase the detection of patients with FH. Methods: Study population: Residents in the health coverage area (N: 195.000 inhabitants) and with at least one determination of cholesterol linked to low-density lipoproteins (LDL-C) carried out between January 1, 2010 and December 30, 2019. The highest LDL-C values were selected. Exclusion criteria: nephrotic syndrome, hypothyroidism, Hypothyroid treatment or triglycerides> 400 mg / dL. Seven algorithms suggestive of Familial Hypercholesterolemia Phenotype (HF-P) were analyzed, selecting the most efficient algorithm that could easily be translated into clinical practice. Results: Based on 6.264.877 assistances and 288.475 patients, after applying the inclusion-exclusion criteria, 504.316 tests were included, corresponding to 106.382 adults and 10.509 <18 years. The selected algorithm presented a prevalence of 0.62%. 840 patients with HF-P were detected, 55.8% being women and 178 <18 years old, 9.3% had a history of cardiovascular disease (CVD) and 16.4% had died. 65% of the patients in primary prevention had LDL-C values> 130 mg / dL and 83% in secondary prevention values> 70mg / dL. A ratio of 7.64 (1-18) patients with HF-P per analytical requesting physician was obtained. Conclusions. Massive data screening and patient profiling are effective tools and easily applicable in clinical practice for the detection of patients with FH.

Massive data screening is a second opportunity to improve the management of patients with familial hypercholesterolemia phenotype. / El rastreo masivo de datos es una segunda oportunidad para mejorar el manejo de los pacientes con fenotipo de hipercolesterolemia familiar.

INTRODUCTION: Familial Hypercholesterolemia (FH) is an autosomal dominant disease with an estimated prevalence between 1/200-250. It is under-treated and underdiagnosed. Massive data screening can increase the detection of patients with FH. METHODS: Study population: Residents in the health coverage area (N: 195.000 inhabitants) and with at least one determination of cholesterol linked to low-density lipoproteins (LDL-C) carried out between January 1, 2010 and December 30, 2019. The highest LDL-C values were selected. EXCLUSION CRITERIA: nephrotic syndrome, hypothyroidism, Hypothyroid treatment or triglycerides> 400 mg / dL. Seven algorithms suggestive of Familial Hypercholesterolemia Phenotype (HF-P) were analyzed, selecting the most efficient algorithm that could easily be translated into clinical practice. RESULTS: Based on 6.264.877 assistances and 288.475 patients, after applying the inclusion-exclusion criteria, 504.316 tests were included, corresponding to 106.382 adults and 10.509 <18 years. The selected algorithm presented a prevalence of 0.62%. 840 patients with HF-P were detected, 55.8% being women and 178 <18 years old, 9.3% had a history of cardiovascular disease (CVD) and 16.4% had died. 65% of the patients in primary prevention had LDL-C values> 130 mg / dL and 83% in secondary prevention values> 70mg / dL. A ratio of 7.64 (1-18) patients with HF-P per analytical requesting physician was obtained. CONCLUSIONS: Massive data screening and patient profiling are effective tools and easily applicable in clinical practice for the detection of patients with FH.