Selzman Institute for Kidney Health, Section of Nephrology, Baylor College of Medicine, Houston, TX, USA.
Texas Institute for Measurement, Evaluation, and Statistics, University of Houston, Houston, TX, USA.
Int J Obes (Lond). 2022 Oct;46(10):1910-1917. doi: 10.1038/s41366-022-01208-x. Epub 2022 Aug 17.
This analysis sought to determine factors (including adiposity-related factors) most associated with HF-type symptoms (fatigue, shortness of breath, and edema) in adults with chronic kidney disease (CKD).
Symptom burden impairs quality of life in CKD, especially symptoms that overlap with HF. These symptoms are common regardless of clinical HF diagnosis, and may be affected by subtle cardiac dysfunction, kidney dysfunction, and other factors. We used machine learning to investigate cross-sectional relationships of clinical variables with symptom scores in a CKD cohort.
Participants in the Chronic Renal Insufficiency Cohort (CRIC) with a baseline modified Kansas City Cardiomyopathy Questionnaire (KCCQ) score were included, regardless of prior HF diagnosis. The primary outcome was Overall Summary Score as a continuous measure. Predictors were 99 clinical variables representing demographic, cardiac, kidney and other health dimensions. A correlation filter was applied. Random forest regression models were fitted. Variable importance scores and adjusted predicted outcomes are presented.
The cohort included 3426 individuals, 10.3% with prior HF diagnosis. BMI was the most important factor, with BMI 24.3 kg/m associated with the least symptoms. Symptoms worsened with higher or lower BMIs, with a potentially clinically relevant 5 point score decline at 35.7 kg/m and a 1-point decline at the threshold for low BMI, 18.5 kg/m. The most important cardiac and kidney factors were heart rate and eGFR, the 4th and 5th most important variables, respectively. Results were similar for secondary analyses.
In a CKD cohort, BMI was the most important feature for explaining HF-type symptoms regardless of clinical HF diagnosis, identifying an important focus for symptom directed investigations.
本分析旨在确定与慢性肾脏病（CKD）成人的 HF 型症状（疲劳、呼吸急促和水肿）最相关的因素（包括肥胖相关因素）。
症状负担会降低 CKD 患者的生活质量，尤其是与 HF 重叠的症状。这些症状在 CKD 中很常见，无论是否存在临床 HF 诊断，并且可能受到微妙的心脏功能障碍、肾脏功能障碍和其他因素的影响。我们使用机器学习方法研究了在 CKD 队列中，临床变量与症状评分的横断面关系。
纳入基线时具有改良堪萨斯城心肌病问卷（KCCQ）评分的慢性肾功能不全队列（CRIC）参与者，无论是否存在先前的 HF 诊断。主要结局为连续测量的总综合评分。预测因子为代表人口统计学、心脏、肾脏和其他健康维度的 99 个临床变量。应用相关滤波器。拟合随机森林回归模型。呈现变量重要性得分和调整后的预测结果。
该队列包括 3426 名个体，其中 10.3%有先前的 HF 诊断。BMI 是最重要的因素，BMI 为 24.3kg/m 时症状最少。BMI 越高或越低，症状越严重，BMI 为 35.7kg/m 时症状评分下降 5 分，BMI 低于 18.5kg/m 时下降 1 分，具有潜在的临床相关性。最重要的心脏和肾脏因素分别是心率和 eGFR，分别是第四和第五重要的变量。次要分析结果相似。
在 CKD 队列中，BMI 是解释 HF 型症状的最重要特征，无论是否存在临床 HF 诊断，这确定了一个重要的重点，用于针对症状的调查。
