siMS Score: Simple Method for Quantifying Metabolic Syndrome

Objective
To evaluate siMS score and siMS risk score, novel continuous metabolic syndrome scores as methods for quantification of metabolic status and risk.
Materials and Methods
Developed siMS score was calculated using formula: siMS score = 2*Waist/Height + Gly/5.6 + Tg/1.7 + TAsystolic/130—HDL/1.02 or 1.28 (for male or female subjects, respectively). siMS risk score was calculated using formula: siMS risk score = siMS score * age/45 or 50 (for male or female subjects, respectively) * family history of cardio/cerebro-vascular events (event = 1.2, no event = 1). A sample of 528 obese and non-obese participants was used to validate siMS score and siMS risk score. Scores calculated as sum of z-scores (each component of metabolic syndrome regressed with age and gender) and sum of scores derived from principal component analysis (PCA) were used for evaluation of siMS score. Variants were made by replacing glucose with HOMA in calculations. Framingham score was used for evaluation of siMS risk score.
Results
Correlation between siMS score with sum of z-scores and weighted sum of factors of PCA was high (r = 0.866 and r = 0.822, respectively). Correlation between siMS risk score and log transformed Framingham score was medium to high for age groups 18+,30+ and 35+ (0.835, 0.707 and 0.667, respectively).
Conclusions
siMS score and siMS risk score showed high correlation with more complex scores. Demonstrated accuracy together with superior simplicity and the ability to evaluate and follow-up individual patients makes siMS and siMS risk scores very convenient for use in clinical practice and research as well.

研究目标：评估新型连续性代谢综合征（metabolic syndrome）评分——siMS评分（siMS score）与siMS风险评分（siMS risk score），用于量化代谢状态与代谢风险。
材料与方法：已开发的siMS评分按照以下公式计算：siMS评分 = 2×腰围（Waist）/身高 + 血糖（Gly）/5.6 + 甘油三酯（Tg）/1.7 + 收缩压（TAsystolic）/130 — 高密度脂蛋白胆固醇（HDL）/1.02 或 1.28（分别对应男性与女性受试者）。siMS风险评分按照以下公式计算：siMS风险评分 = siMS评分 × 年龄/45 或 50（分别对应男性与女性受试者） × 心脑血管事件家族史（有事件记为1.2，无事件记为1）。本研究纳入528名肥胖与非肥胖受试者作为样本，用于验证siMS评分与siMS风险评分的效能。以Z得分（z-score）之和（将代谢综合征各组分针对年龄与性别进行回归分析后得到的得分）以及主成分分析（PCA）衍生得分之和作为参照，用于评估siMS评分的性能。本研究还构建了将葡萄糖替换为稳态模型评估（HOMA）的计算变体，以拓展验证范围。以弗雷明汉风险评分（Framingham score）作为参照，评估siMS风险评分的效能。
研究结果：siMS评分与Z得分之和、主成分分析因子加权得分均呈高度相关（相关系数r分别为0.866与0.822）。在18岁及以上、30岁及以上、35岁及以上年龄组中，siMS风险评分与对数转换后的弗雷明汉风险评分均呈中高度相关（相关系数分别为0.835、0.707与0.667）。
研究结论：siMS评分与siMS风险评分与更为复杂的代谢评分均呈高度相关。该两类评分兼具优异的准确性与简洁性，且可用于个体患者的代谢状态评估与随访，因此在临床实践与科研工作中均具备极高的应用价值。