Urine specific gravity to identify and predict hydration need in ALS

<i>Introduction</i>: Multiple factors contribute to increased risk of dehydration in amyotrophic lateral sclerosis (ALS), which contributes to shortened survival independent of nutritional status. The assessment of hydration by doubly labeled water is restricted due to the limited availability of this gold standard technique for clinical use. This prompted us to examine the utility of urine-specific gravity (USG) as a predictor of hydration need in ALS subjects. <i>Material and Methods:</i> Using data from a multicenter study of 80 ALS subjects with 250 visits, we conducted a secondary analysis of the original data set from doubly labeled water experiments. We used a cross-section of the data (one visit per 75 subjects) in the model selection step (“test set”), and a repeated measures analysis in the validation step with data from 63 subjects and 142 follow-up visits. The sensitivity to detect inadequate water turnover rate (a surrogate for water intake) was the goal of the predictive model presented for clinical use. <i>Results and discussion:</i> The final predictive model to estimate water requirement included USG, gender, body mass index, and the ALSFRS gross motor subscale score. We developed a best-fit equation to estimate water intake from USG, determine hydration status, and improve clinical care of real-world ALS subjects.

引言：肌萎缩侧索硬化症（amyotrophic lateral sclerosis, ALS）患者脱水风险升高受多种因素影响，且该风险可独立于营养状况缩短患者生存周期。双标水法（doubly labeled water）作为水合状态评估的金标准技术，因临床可及性有限而应用受限，这一局限促使我们探究尿比重（urine-specific gravity, USG）作为ALS患者水合需求预测指标的应用价值。
材料与方法：本研究依托一项纳入80名ALS患者、共250次随访的多中心研究数据，对双标水法实验的原始数据集开展二次分析。在模型选择阶段（即“测试集”），我们选取数据的横断面子集（每75名患者对应1次随访数据）；在验证阶段，则采用63名患者的142次随访数据进行重复测量分析。本研究所构建的临床可用预测模型，核心目标为灵敏检测水更新率不足（饮水量的替代指标）。
结果与讨论：最终用于估算水需求的预测模型纳入了尿比重、性别、体质量指数以及肌萎缩侧索硬化功能评定量表（Amyotrophic Lateral Sclerosis Functional Rating Scale, ALSFRS）粗大运动分项得分。本研究拟合得到最优拟合方程，可通过尿比重估算饮水量、评估患者水合状态，从而优化临床真实场景中ALS患者的诊疗管理。