Salomón Martín Pérez , Teresa Arrobas Velilla , Juan Fabiani de la Iglesia , Ignacio Vázquez Rico , Gema Varo Sánchez , Antonio León-Justel
{"title":"初级保健心血管预防临床实验室的地质统计分析","authors":"Salomón Martín Pérez , Teresa Arrobas Velilla , Juan Fabiani de la Iglesia , Ignacio Vázquez Rico , Gema Varo Sánchez , Antonio León-Justel","doi":"10.1016/j.arteri.2022.08.003","DOIUrl":null,"url":null,"abstract":"<div><h3>Introduction and objectives</h3><p>Cardiovascular diseases continue to lead the ranking of mortality in Spain. The implementation of geostatistical analysis techniques in the clinical laboratory are innovative tools that allow the design of new strategies in primary prevention of cardiovascular disease. The aim of this study was to study the prevalence and geolocation of severe dyslipidemia in the health areas under study in order to implement prevention strategies in primary care. A retrospective cohort study of low-density protein-bound cholesterol, triglyceride and lipoprotein (a) levels in the years 2019 and 2020 were carried out. In addition, a geostatistical analysis was performed including representation in choropleth maps and the detection of clustering clusters, using geographic information in zip code format included in the demographic data of each analytic.</p></div><div><h3>Results</h3><p>The analytical data included in the study were triglycerides (<em>n</em> <!-->=<!--> <!-->365,384), low density protein-bound cholesterol (<em>n</em> <!-->=<!--> <!-->289,594) and lipoprotein to lipoprotein (a) (<em>n</em> <!-->=<!--> <!-->502). Areas with the highest and lowest percentage of cases were identified for the established cut-off points of LDL-C<!--> <!-->><!--> <!-->190<!--> <!-->mg/dL and TG<!--> <!-->><!--> <!-->150<!--> <!-->mg/dL. Two clustering clusters with statistical significance were detected for cLDL<!--> <!-->><!--> <!-->190<!--> <!-->mg/dL and a total of 6 clusters for TG values<!--> <!-->><!--> <!-->150<!--> <!-->mg/dL.</p></div><div><h3>Conclusions</h3><p>The detection of clusters, as well as the representation of choropleth maps, can be of great help in detecting geographic areas that require greater attention to intervene and improve cardiovascular risk.</p></div>","PeriodicalId":45230,"journal":{"name":"Clinica e Investigacion en Arteriosclerosis","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Análisis geoestadístico desde el laboratorio clínico en prevención cardiovascular para atención primaria\",\"authors\":\"Salomón Martín Pérez , Teresa Arrobas Velilla , Juan Fabiani de la Iglesia , Ignacio Vázquez Rico , Gema Varo Sánchez , Antonio León-Justel\",\"doi\":\"10.1016/j.arteri.2022.08.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Introduction and objectives</h3><p>Cardiovascular diseases continue to lead the ranking of mortality in Spain. The implementation of geostatistical analysis techniques in the clinical laboratory are innovative tools that allow the design of new strategies in primary prevention of cardiovascular disease. The aim of this study was to study the prevalence and geolocation of severe dyslipidemia in the health areas under study in order to implement prevention strategies in primary care. A retrospective cohort study of low-density protein-bound cholesterol, triglyceride and lipoprotein (a) levels in the years 2019 and 2020 were carried out. In addition, a geostatistical analysis was performed including representation in choropleth maps and the detection of clustering clusters, using geographic information in zip code format included in the demographic data of each analytic.</p></div><div><h3>Results</h3><p>The analytical data included in the study were triglycerides (<em>n</em> <!-->=<!--> <!-->365,384), low density protein-bound cholesterol (<em>n</em> <!-->=<!--> <!-->289,594) and lipoprotein to lipoprotein (a) (<em>n</em> <!-->=<!--> <!-->502). Areas with the highest and lowest percentage of cases were identified for the established cut-off points of LDL-C<!--> <!-->><!--> <!-->190<!--> <!-->mg/dL and TG<!--> <!-->><!--> <!-->150<!--> <!-->mg/dL. Two clustering clusters with statistical significance were detected for cLDL<!--> <!-->><!--> <!-->190<!--> <!-->mg/dL and a total of 6 clusters for TG values<!--> <!-->><!--> <!-->150<!--> <!-->mg/dL.</p></div><div><h3>Conclusions</h3><p>The detection of clusters, as well as the representation of choropleth maps, can be of great help in detecting geographic areas that require greater attention to intervene and improve cardiovascular risk.</p></div>\",\"PeriodicalId\":45230,\"journal\":{\"name\":\"Clinica e Investigacion en Arteriosclerosis\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinica e Investigacion en Arteriosclerosis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0214916822001127\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"PERIPHERAL VASCULAR DISEASE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinica e Investigacion en Arteriosclerosis","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0214916822001127","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PERIPHERAL VASCULAR DISEASE","Score":null,"Total":0}
Análisis geoestadístico desde el laboratorio clínico en prevención cardiovascular para atención primaria
Introduction and objectives
Cardiovascular diseases continue to lead the ranking of mortality in Spain. The implementation of geostatistical analysis techniques in the clinical laboratory are innovative tools that allow the design of new strategies in primary prevention of cardiovascular disease. The aim of this study was to study the prevalence and geolocation of severe dyslipidemia in the health areas under study in order to implement prevention strategies in primary care. A retrospective cohort study of low-density protein-bound cholesterol, triglyceride and lipoprotein (a) levels in the years 2019 and 2020 were carried out. In addition, a geostatistical analysis was performed including representation in choropleth maps and the detection of clustering clusters, using geographic information in zip code format included in the demographic data of each analytic.
Results
The analytical data included in the study were triglycerides (n = 365,384), low density protein-bound cholesterol (n = 289,594) and lipoprotein to lipoprotein (a) (n = 502). Areas with the highest and lowest percentage of cases were identified for the established cut-off points of LDL-C > 190 mg/dL and TG > 150 mg/dL. Two clustering clusters with statistical significance were detected for cLDL > 190 mg/dL and a total of 6 clusters for TG values > 150 mg/dL.
Conclusions
The detection of clusters, as well as the representation of choropleth maps, can be of great help in detecting geographic areas that require greater attention to intervene and improve cardiovascular risk.
期刊介绍:
La publicación idónea para acceder tanto a los últimos originales de investigación como a formación médica continuada sobre la arteriosclerosis y su etiología, epidemiología, fisiopatología, diagnóstico y tratamiento. Además, es la publicación oficial de la Sociedad Española de Arteriosclerosis.