| 摘要: |
| 目的 分析影响体检人群臂-踝脉搏波传导速度(baPWV)测量值的因素, 构建baPWV的logit预测模型并对其进行评价。 方法 对本院2010—2014年检测的4 159例体检者的体检资料进行回顾性分析, 纳入考察的体检指标包括:性别、年龄、收缩压、舒张压、脉搏、空腹血糖、三酰甘油、胆固醇、丙氨酸转氨酶、谷氨酰转肽酶、肌酐、高密度脂蛋白、低密度脂蛋白、尿酸。采用logistic回归分析方法探究baPWV的影响因素, 建立baPWV的logit预测模型并对其进行评价。 结果 单因素分析结果显示, 除高密度脂蛋白外, 其余检测指标在baPWV正常组与异常组之间的差异均具有统计学意义(P<0.05)。多因素分析得到的logit模型为:logit(p)=-17.888+0.001×尿酸 0.004×丙氨酸转氨酶 0.105×空腹血糖 0.023×脉搏 0.032×舒张压 0.061×收缩压 0.092×年龄 0.411×性别;logit模型对体检人群baPWV的预测正确率为 79.6%, ROC曲线下面积为0.869(95%CI:0.859~0.879)。 结论 性别、年龄、收缩压、舒张压、脉搏、空腹血糖、丙氨酸转氨酶、尿酸值等均可能影响baPWV, logit模型可作为研究此类问题的较好模型。 |
| 关键词: 脉搏波传导速度 心血管疾病 logit模型 |
| DOI：10.3724/SP.J.1008.2015.00569 |
| 投稿时间：2015-01-12修订日期：2015-03-19 |
| 基金项目: |
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| Factors influencing brachial-ankle pulse wave velocity in people undergoing health examination and model evaluation: report of 4 159 cases |
| CAI Xiao-bing1△,LIU Ya-wei2△,SUN Feng-jun3*,HU Xiao-gang4 |
(1. Health Division of Guard Bureau, General Staff Department of PLA, Beijing 100017, China;
2. Chinese PLA Medical School, Beijing 100853, China;
3. Department of Pharmacy, Southwest Hospital, Third Military Medical University, Chongqing 400038, China;
4. Department of Pharmacy, Chongqing Cancer Institute, Chongqing 400030, China
△Co-first authors.
*Corresponding author) |
| Abstract: |
| Objective To analyze the factors influencing brachial-ankle pulse wave velocity (baPWV) and to establish a logit model for predicting baPWV. Methods The data of 4 159 cases who underwent health examination from 2010 to 2014 in our hospital were retrospectively analyzed. The parameters included gender, age, systolic blood pressure, diastolic blood pressure, pulse, fasting glucose, triglyceride, cholesterol, alanine aminotransferase, glutamyl transpeptidase and cholesterol, low density lipoprotein (LDL), high density lipoprotein (HDL), and uric acid. Logistic regression was used to explore the influencing factors of baPWV, and a regression model was established to predict baPWV and it was evaluated. Results Univariate analysis showed that, except for HDL, all the other parameters above were significantly different between normal baPWV group and abnormal baPWV group (P<0.05). Multivariable analysis yielded the following logit model: logit (p)=-17.888+0.001×uric acid 0.004×alanine aminotransferase 0.105×fasting glucose 0.023×pulse 0.032×diastolic blood pressure 0.061×systolic blood pressure 0.092×age 0.411×sex, which showed a correct predicting rate of 79.6% for baPWV in health examination population, with the ROC area being 0.869 (95%CI:0.859-0.879). Conclusion The baPWV values can be influenced by gender, age, systolic blood pressure, diastolic blood pressure, pulse, fasting blood glucose, alanine aminotransferase and uric acid levels, and logit model may serve as a satisfactory model for these types of study. |
| Key words: pulse wave velocity cardiovascular diseases logit model |
