| 摘要: | 背景：末期腎臟病造成的全球疾病負擔日益增加，儘管透析技術不斷進步，但末期腎臟病患者的死亡率還是比一般族群高出10至20倍。台灣是世界上慢性腎臟病和末期腎臟病發生率和盛行率最高的國家，造成龐大的醫療花費與疾病負擔。根據改善全球腎臟病預後組織(Kidney Disease: Improving Global Outcomes, KDIGO)統整出的慢性腎臟病危險因子，發現促使慢性腎臟病惡化的危險因子包含高血壓 ;糖尿病患者的血糖控制不佳以及可能存在血脂異常等代謝風險。然而，目前未有文獻同時探討長期血糖 ;血脂及血壓三項代謝風險指標發展對於慢性腎臟病預後的影響。因此，本篇研究的目的是透過群組化多軌跡模式找出不同代謝風險指標軌跡分群，並探討不同代謝風險指標軌跡分群與慢性腎臟病預後發展(透析及全死因死亡)之間的相關性。
研究方法：本研究屬於回溯性世代研究，研究對象來自臺北醫學大學附設醫院 ;萬芳醫院以及雙和醫院，納入了2009年至2013年符合慢性腎臟病第三期至第五期的患者，並使用群組化多軌跡模式同時考慮到隨著時間變化的長期空腹血糖 ;血壓 ;三酸甘油酯以及低密度脂蛋白膽固醇發展並定義出潛在的代謝風險指標軌跡分群，並且利用Cox 比例風險模型分析不同代謝風險指標軌跡分群之間的透析及全死因死亡之風險比(Hazard ratio, HR)(95%信賴區間(Confidence interval, CI))。
研究結果：本次研究總共納入了15,210位慢性腎臟病第三期至第五期患者，年齡中位數(四分位距)為72歲(62, 79)，其中女性有7,008人(46.07%)，男性有8,202人(53.93%)。本研究透過群組化多軌跡模式定義出三個不同的代謝風險指標軌跡分群，包含對照組(代謝風險指標呈現穩定控制) ;血糖血脂偏高組 ;以及血糖血脂血壓過高組(代謝風險指標嚴重過高)。對照組之基線年齡 ;慢性腎臟病第三期占比 ;高血壓占比及腎絲球過濾率顯著高於血糖血脂偏高組及血糖血脂血壓過高組；血糖血脂偏高組之基線血脂異常占比 ;收縮壓以及舒張壓顯著高於對照組及血糖血脂血壓過高組；而血糖血脂血壓過高組之基線女性比例 ;慢性腎臟病第四和五期占比 ;糖尿病占比 ;身體質量指數 ;肌酸酐 ;空腹血糖 ;三酸甘油脂 ;低密度脂蛋白膽固醇顯著高於對照組及血糖血脂偏高組。再者，與對照組相比，血糖血脂偏高組以及血糖血脂血壓過高組具有顯著較高的全死因死亡風險(分別為HR：1.22，95%CI：1.09-1.38；HR：2.09，95%CI：1.72-2.53)，且血糖血脂血壓過高組發生長期透析的風險顯著較高(HR：1.76，95%CI：1.04-2.98)。
結論：在代謝嚴重異常(嚴重高血糖 ;嚴重高血脂及高收縮壓)的情況下，慢性腎臟病第三期至第五期的患者具有顯著較高發生透析或全死因死亡的風險。在臨床照護方面，可將群組化多軌跡模式分群的結果應用於患者個人化精準醫療，透過定期回診監測慢性腎臟患者可能伴隨的代謝異常情況，或是未來可搭配一些穿戴式裝置與人工智慧方法，監測患者可能伴隨的代謝異常情況，給予及時的精準醫療預測與照護，同時穩定控制血糖 ;血脂以及血壓等代謝生化指標，進而達到降低慢性腎臟病患者嚴重預後發展的情形發生。同時，也支持臨床醫生，患者及其患者家庭成員之間共同的決策過程。
Background: End-stage kidney disease (ESKD) is a major global health problem. According to the 2021 Unites States Renal Data System (USRDS) Annual Data Report, Taiwan has the highest prevalence rate of treated ESKD in the world. Moreover, the 2020 Taiwan Renal Registry Data System (TWRDS) database revealed that the medical expenditure of ESKD accounted for 9% of overall National Health Insurance (NHI) expenditures in Taiwan. In addition, patients with ESKD have 10 to 20-times higher mortality rates than the general population, despite advancements in dialysis technology. According to the Kidney Disease: Improving Global Outcomes (KDIGO), risk factors for chronic kidney disease (CKD) progression include high blood pressure, poor blood glucose control, and dyslipidemia. However, there is currently a lack of literature that simultaneously examines the influence of long-term trajectory of blood glucose, blood lipids, and blood pressure on the prognosis of CKD. Therefore, this study aims to use Group-based multi-trajectory modeling (GBMM) to determine the time-varying trajectories of metabolic risk factors and explore the relationship between these trajectories and risk of dialysis or all-cause mortality among patients with CKD.
Methods: This study is a retrospective cohort study that examined the metabolic risk factor trajectories of patients with CKD stage III to V from the Taipei Medical University Hospital, Wan Fang Hospital, and Shuang Ho Hospital between 2009 and 2013. We used GBMM approach to identify trajectory pattern of long-term fasting blood glucose, blood pressure, triglyceride and low-density lipoprotein cholesterol. The Cox proportional hazards model was used to investigate the association between these trajectory groups and risk of progression to ESKD and all-cause mortality.
Results: The study included 15,210 patients with CKD stage III to V, with 7,008 (46.07%) being women, and the median (interquartile range) age was 72 (62, 79) years. Three distinct metabolic risk cluster trajectories were identified by GBMM: the reference trajectory group (metabolic risk are maintained optimal level or under control), the high blood glucose and blood lipid trajectory group, and the severely high metabolic risk trajectory group. The reference trajectory group had a higher median age, proportion of CKD stage III and diagnosed hypertension, and baseline estimated glomerular filtration rate (eGFR) compared to the other two trajectories. The high blood glucose and blood lipid trajectory group had a higher proportion of dyslipidemia, higher levels of baseline systolic blood pressure, and diastolic blood pressure compared to the reference trajectory group and the severely high metabolic risk trajectory group. Also, the severely high metabolic risk trajectory group had a higher proportion of females, CKD stage VI and V, and diabetes mellitus, higher levels of baseline body mass index, creatinine, fasting blood glucose, triglyceride and low-density lipoprotein cholesterol compared to the reference trajectory group and the high blood glucose and blood lipid trajectory group. Compared to the reference trajectory group, the adjusted hazard ratio for all-cause mortality was 1.22 (95% CI: 1.09-1.38) and 2.09 (95% CI: 1.72-2.53) in high blood glucose-high blood lipid trajectory and severely high blood glucose- severely high blood lipid- high blood pressure trajectory, respectively. For long-term dialysis, it was 1.76 (95% CI: 1.04-2.98) for severely high blood glucose- severely high blood lipid- high blood pressure trajectory.
Conclusion: This study found that patients with CKD stages III to V who had abnormal metabolic risk factor trajectory had a significantly increased risk of dialysis or all-cause mortality. The results of GBMM could aid in the individualize medicine and enhance the shared decision-making process between clinicians and patients. Identifying metabolic risk factor trajectories, including blood glucose, blood lipid, and blood pressure, could provide a more nuanced understanding of disease progression, ultimately contributing to better healthcare for patients with CKD. |
