■心脏代谢和肾脏并发症的长期预后,除了新诊断的肺动脉高压患者的死亡率,不清楚。本研究旨在以电子虚弱指数(eFI)的形式开发可扩展的预测模型,以预测不同的不良后果。
■这是一项基于人群的队列研究,研究对象是1月1日之间诊断为肺动脉高压的患者,2000年12月31日,2017年,在香港公立医院。主要结果是死亡率,心血管并发症,肾脏疾病,和糖尿病。单变量和多变量Cox回归分析用于识别显著的危险因素,将其输入到非参数随机生存森林(RSF)模型中以开发eFI。
■共纳入2,560例患者,平均年龄63.4岁(四分位距:38.0-79.0)。在后续行动中,1,347例死亡,1,878、437和684例患者出现心血管并发症,糖尿病,和肾脏疾病,分别。RSF模型识别的年龄,平均再入院率,抗高血压药物,累计停留时间,和总胆红素是预测死亡率的最重要危险因素之一.包括诊断年龄在内的因素的配对相互作用,平均再入院间隔,累积住院时间对死亡率预测也至关重要.与存活的患者相比,出现全因死亡率的患者具有更高的eFI值(P<0.0001)。eFI≥9.5与死亡风险增加相关[风险比(HR):1.90;95%置信区间[CI]:1.70-2.12;P<0.0001]。在65岁或以上且eFI≥9.5的患者中,累积风险较高。使用相同的截止点,eFI预测10年以上的长期死亡率(HR:1.71;95%CI:1.53-1.90;P<0.0001)。与多变量Cox回归相比,精度,召回,曲线下面积(AUC),在预后预测中,RSF和C指数明显更高。
■RSF模型确定了新的风险因素和与并发症和死亡率发展的相互作用。RSF构建的eFI能够准确预测肺动脉高压患者的并发症和死亡率,尤其是老年人。
UNASSIGNED: The long-term prognosis of the cardio-metabolic and renal complications, in addition to mortality in patients with newly diagnosed pulmonary hypertension, are unclear. This study aims to develop a scalable predictive model in the form of an electronic frailty index (eFI) to predict different adverse outcomes.
UNASSIGNED: This was a population-based cohort study of patients diagnosed with pulmonary hypertension between January 1st, 2000 and December 31st, 2017, in Hong Kong public hospitals. The primary outcomes were mortality, cardiovascular complications, renal diseases, and diabetes mellitus. The univariable and multivariable Cox regression analyses were applied to identify the significant risk factors, which were fed into the non-parametric random survival forest (RSF) model to develop an eFI.
UNASSIGNED: A total of 2,560 patients with a mean age of 63.4 years old (interquartile range: 38.0-79.0) were included. Over a follow-up, 1,347 died and 1,878, 437, and 684 patients developed cardiovascular complications, diabetes mellitus, and renal disease, respectively. The RSF-model-identified age, average readmission, anti-hypertensive drugs, cumulative length of stay, and total bilirubin were among the most important risk factors for predicting mortality. Pair-wise interactions of factors including diagnosis age, average readmission interval, and cumulative hospital stay were also crucial for the mortality prediction. Patients who developed all-cause mortality had higher values of the eFI compared to those who survived (P < 0.0001). An eFI ≥ 9.5 was associated with increased risks of mortality [hazard ratio (HR): 1.90; 95% confidence interval [CI]: 1.70-2.12; P < 0.0001]. The cumulative hazards were higher among patients who were 65 years old or above with eFI ≥ 9.5. Using the same cut-off point, the eFI predicted a long-term mortality over 10 years (HR: 1.71; 95% CI: 1.53-1.90; P < 0.0001). Compared to the multivariable Cox regression, the precision, recall, area under the curve (AUC), and C-index were significantly higher for RSF in the prediction of outcomes.
UNASSIGNED: The RSF models identified the novel risk factors and interactions for the development of complications and mortality. The eFI constructed by RSF accurately predicts the complications and mortality of patients with pulmonary hypertension, especially among the elderly.