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伊朗东北部基于办公室的致命性心血管疾病风险评分系统的临床性能。

The clinical performance of an office-based risk scoring system for fatal cardiovascular diseases in North-East of Iran.

作者信息

Sepanlou Sadaf G, Malekzadeh Reza, Poustchi Hossein, Sharafkhah Maryam, Ghodsi Saeed, Malekzadeh Fatemeh, Etemadi Arash, Pourshams Akram, Pharoah Paul D, Abnet Christian C, Brennan Paul, Boffetta Paolo, Dawsey Sanford M, Kamangar Farin

机构信息

Digestive Disease Research Institute, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran.

Digestive Disease Research Institute, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.

出版信息

PLoS One. 2015 May 26;10(5):e0126779. doi: 10.1371/journal.pone.0126779. eCollection 2015.

Abstract

BACKGROUND

Cardiovascular diseases (CVD) are becoming major causes of death in developing countries. Risk scoring systems for CVD are needed to prioritize allocation of limited resources. Most of these risk score algorithms have been based on a long array of risk factors including blood markers of lipids. However, risk scoring systems that solely use office-based data, not including laboratory markers, may be advantageous. In the current analysis, we validated the office-based Framingham risk scoring system in Iran.

METHODS

The study used data from the Golestan Cohort in North-East of Iran. The following risk factors were used in the development of the risk scoring method: sex, age, body mass index, systolic blood pressure, hypertension treatment, current smoking, and diabetes. Cardiovascular risk functions for prediction of 10-year risk of fatal CVDs were developed.

RESULTS

A total of 46,674 participants free of CVD at baseline were included. Predictive value of estimated risks was examined. The resulting Area Under the ROC Curve (AUC) was 0.774 (95% CI: 0.762-0.787) in all participants, 0.772 (95% CI: 0.753-0.791) in women, and 0.763 (95% CI: 0.747-0.779) in men. AUC was higher in urban areas (0.790, 95% CI: 0.766-0.815). The predicted and observed risks of fatal CVD were similar in women. However, in men, predicted probabilities were higher than observed.

CONCLUSION

The AUC in the current study is comparable to results of previous studies while lipid profile was replaced by body mass index to develop an office-based scoring system. This scoring algorithm is capable of discriminating individuals at high risk versus low risk of fatal CVD.

摘要

背景

心血管疾病(CVD)正成为发展中国家的主要死因。需要心血管疾病风险评分系统来优先分配有限的资源。这些风险评分算法大多基于一系列风险因素,包括血脂的血液标志物。然而,仅使用基于门诊的数据(不包括实验室标志物)的风险评分系统可能具有优势。在当前分析中,我们在伊朗验证了基于门诊的弗雷明汉风险评分系统。

方法

该研究使用了伊朗东北部戈勒斯坦队列的数据。在风险评分方法的开发中使用了以下风险因素:性别、年龄、体重指数、收缩压、高血压治疗、当前吸烟情况和糖尿病。开发了用于预测10年致命心血管疾病风险的心血管风险函数。

结果

共有46674名基线时无心血管疾病的参与者被纳入。检查了估计风险的预测价值。所有参与者的受试者工作特征曲线下面积(AUC)为0.774(95%可信区间:0.762 - 0.787),女性为0.772(95%可信区间:0.753 - 0.791),男性为0.763(95%可信区间:0.747 - 0.779)。城市地区的AUC更高(0.790,95%可信区间:0.766 - 0.815)。女性中致命心血管疾病的预测风险和观察到的风险相似。然而,在男性中,预测概率高于观察到的概率。

结论

在本研究中,用体重指数取代血脂谱来开发基于门诊的评分系统时,AUC与先前研究的结果相当。这种评分算法能够区分致命心血管疾病高风险和低风险的个体。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8e6/4444120/488e6a765536/pone.0126779.g001.jpg

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