Yu Yanna, Li Fen, Wang Zhan, Ni Zhibin, Zhang Shu, Zhao Weihong, Pei Xiaohua
Department of Nephrology The First Affiliated Hospital of Guangzhou University of Chinese Medicine Guangzhou China.
Guangdong Clinical Research Academy of Chinese Medicine Guangzhou China.
Aging Med (Milton). 2024 Dec 24;7(6):737-743. doi: 10.1002/agm2.12384. eCollection 2024 Dec.
Comorbidity prediction models have been demonstrated to offer more comprehensive and accurate predictions of death risk compared to single indices. However, their application in China has been limited, particularly among maintenance hemodialysis (MHD) patients. Therefore, the objective of this study was to evaluate the utility of comorbidity index models in predicting mortality risk among Chinese MHD patients.
The MHD patients in the First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine were taken as the subjects. Claims-based disease-specific refinements matching translation to ICD-10 and flexibility (CDMF-CCI) model and Liu model were selected as the candidate models for this verification research. Univariate and multivariate Cox regression calculations were used to analyze the independent predictive effect of the models on survival rate.
Annually, nearly 500 patients undergo hemodialysis treatment. From January 2019 to June 2022, a total of 199 patients succumbed, with a mean age of 65.2 years. During these 4 years, the mortality rates were 13.04%, 9.68%, 11.69%, and 6.39%, respectively. The leading causes of death were sudden demise (82 patients, 41.2%), cardiovascular disease (48 patients, 24.1%), pulmonary infection (33 patients, 16.5%), and stroke (19 patients, 9.5%). When compared to individual indices, the CDMF-CCI model displayed more accurate and predictive results, with an HR of 1.190 ( = 0.037). Conversely, the Liu model failed to identify high-risk individuals.
The MHD patients face a significant risk of mortality. When compared to univariate parameters and the Liu model, the CDMF-CCI model exhibits superior predictive accuracy for mortality in MHD patients.
与单一指标相比，合并症预测模型已被证明能更全面、准确地预测死亡风险。然而，其在中国的应用有限，尤其是在维持性血液透析（MHD）患者中。因此，本研究的目的是评估合并症指数模型在预测中国MHD患者死亡风险中的效用。
以广州中医药大学第一附属医院的MHD患者为研究对象。选择基于索赔的疾病特异性细化匹配翻译至ICD - 10和灵活性（CDMF - CCI）模型以及刘模型作为本验证研究的候选模型。采用单因素和多因素Cox回归计算分析模型对生存率的独立预测作用。
每年有近500例患者接受血液透析治疗。2019年1月至2022年6月，共有199例患者死亡，平均年龄为65.2岁。在这4年中，死亡率分别为13.04%、9.68%、11.69%和6.39%。主要死亡原因是猝死（82例，41.2%）、心血管疾病（48例，24.1%）、肺部感染（33例，16.5%）和中风（19例，9.5%）。与单个指标相比，CDMF - CCI模型显示出更准确的预测结果，风险比为1.190（P = 0.037）。相反，刘模型未能识别出高危个体。
MHD患者面临着显著的死亡风险。与单因素参数和刘模型相比，CDMF - CCI模型在预测MHD患者死亡率方面具有更高的预测准确性。
