Hipertensión arterial asociada a osteoporosis en pacientes mujeres del hospital del Seguro Social, Trujillo

Jeanpierre De La Cruz-Burgos, Víctor Bardales-Zuta
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Abstract

Objective: To determine if hypertension is associated with osteoporosis in female patients of Seguro Social de Salud (EsSalud) Hospital I in Trujillo. Materials and methods: An observational, analytical and cross-sectional study, which included 351 female patients treated in the Internal Medicine Unit of EsSalud Hospital I Florencia de Mora, Trujillo, from 2016 to 2019. According to the screening criteria, patients were divided into two groups—175 with hypertension and 176 without hypertension—to determine the number of patients with osteoporosis. The data was analyzed with Pearson’s chi-square test using IBM SPSS Statistics V26 to perform the statistical analysis and present the results in graphs and tables in Microsoft Excel Windows 10. Results: It was found that the prevalence of osteoporosis with hypertension accounted for 31.4 %, while that of osteoporosis without hypertension was 1.7 %. This shows that the prevalence of osteoporosis in women with hypertension is statistically significant ( p < 0.001) with respect to women without hypertension. Regarding the analysis of the intervening variables, age ( p < 0.001), cholesterol ( p < 0.001) and coffee ( p < 0.001) were statistically significant. Variables such as type 2 diabetes mellitus, sex, obesity, anemia, triglycerides and smoking were not statistically significant. Conclusions: Hypertension is associated with osteoporosis as well as with the intervening variables age, cholesterol and coffee, as they were statistically significant.
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特鲁希略社会保险医院女性患者与骨质疏松症相关的动脉高血压
目的:了解特鲁希略市塞古罗社会医院(EsSalud)第一医院女性患者的高血压是否与骨质疏松症相关。材料与方法:一项观察性、分析性和横断面研究,纳入2016年至2019年在特鲁希略弗洛伦西亚德莫拉EsSalud医院内科治疗的351名女性患者。根据筛查标准,将患者分为高血压组175例和非高血压组176例,确定骨质疏松患者的数量。采用IBM SPSS Statistics V26对数据进行Pearson卡方检验进行统计分析,并在Microsoft Excel Windows 10中以图表形式呈现结果。结果:骨质疏松伴高血压的患病率为31.4%,骨质疏松无高血压的患病率为1.7%。这表明,与没有高血压的女性相比,高血压女性骨质疏松症的患病率具有统计学意义(p < 0.001)。对于干预变量的分析,年龄(p < 0.001)、胆固醇(p < 0.001)、咖啡(p < 0.001)具有统计学意义。2型糖尿病、性别、肥胖、贫血、甘油三酯和吸烟等变量无统计学意义。结论:高血压与骨质疏松相关,且与年龄、胆固醇、咖啡等干预变量相关,且具有统计学意义。
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