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高血压合并阻塞性睡眠呼吸暂停患者肝脂肪变性指数与主要不良心血管事件的线性关系:一项来自中国的真实世界队列研究

Linear Relationship between Hepatic Steatosis Index and Major Adverse Cardiovascular Events in Hypertensive Patients with Obstructive Sleep Apnea: A Real-World Cohort Study from China.

作者信息

Wen Wen, Cai Xintian, Zhu Qing, Hu Junli, Hong Jing, Zhang Xiangyang, Li Nanfang

机构信息

Hypertension Center of People's Hospital of Xinjiang Uygur Autonomous Region, Xinjiang Hypertension Institute, NHC Key Laboratory of Hypertension Clinical Research, Key Laboratory of Xinjiang Uygur Autonomous Region "Hypertension Research Laboratory", Xinjiang Clinical Medical Research Center for Hypertension (Cardio-Cerebrovascular) Diseases, 830000 Urumqi, Xinjiang Uygur Autonomous Region, China.

The First Affiliated Hospital of Xinjiang Medical University, 830000 Urumqi, Xinjiang Uygur Autonomous Region, China.

出版信息

Rev Cardiovasc Med. 2023 Oct 7;24(10):280. doi: 10.31083/j.rcm2410280. eCollection 2023 Oct.

Abstract

BACKGROUND

Hypertensive patients with obstructive sleep apnea (OSA) are at a high risk of cardiovascular disease (CVD), but assessments of CVD risk in this population are frequently constrained by the presence of comorbid medical conditions. The noninvasive and convenient hepatic steatosis index (HSI) can not only predict the degree of fatty liver degeneration but also correlates well with the severity of numerous diseases. However, the relationship between the HSI and CVD in hypertensive patients with OSA remains unclear.

METHODS

This retrospective cohort study included patients aged 18 years with hypertension and a primary diagnosis of OSA and grouped them according to their baseline HSI. The primary outcome was new or recurrent major adverse cardiovascular and cerebrovascular events (MACCE), while the secondary outcomes were cardiac and cerebrovascular events. The relationship between the baseline HSI and the risk of endpoint events was evaluated using Kaplan-Meier curves, risk-factor graphs, and Cox regression models, while generalized additive models were used to identify linear relationships. The C-statistic, integrated discrimination improvement (IDI), and net reclassification index (NRI) were used to evaluate the predictive value of HSI increments for endpoint events.

RESULTS

A total of 2467 participants were included in the analysis and separated into four groups (Q1-Q4) based on their HSI quartiles. Kaplan-Meier survival curves indicated that patients in the Q4 group had the lowest survival time. The Q4 group also showed a significantly higher risk of MACCE (HR [hazard ratio], 2.95; 95% CI [confidence interva]: 1.99-4.39; 0.001), cardiac events (HR, 2.80; 95% CI: 1.68-4.66; 0.001), and cerebrovascular events (HR, 3.21; 95% CI: 1.71-6.03; 0.001). The dose-response curve revealed a linear association between the HSI and the occurrence of endpoint events. For every unit increase in the HSI, the risks of MACCE, cardiac events, and cerebrovascular events increased by 43%, 38%, and 51%, respectively. The C-statistic, IDI, and NRI all indicated that the model including the HSI showed better discriminatory and classification efficacy for endpoint events in comparison with the conventional model ( 0.05).

CONCLUSIONS

The HSI showed a linear relationship with the risk of MACCE in hypertensive OSA patients.

摘要

背景

患有阻塞性睡眠呼吸暂停(OSA)的高血压患者心血管疾病(CVD)风险较高,但该人群CVD风险评估常受合并症的限制。无创且便捷的肝脂肪变性指数(HSI)不仅可以预测脂肪肝变性程度,还与多种疾病的严重程度密切相关。然而,HSI与患有OSA的高血压患者的CVD之间的关系仍不清楚。

方法

这项回顾性队列研究纳入了年龄≥18岁的高血压患者,这些患者的初步诊断为OSA,并根据其基线HSI进行分组。主要结局是新发或复发性重大心血管和脑血管事件(MACCE),次要结局是心脏和脑血管事件。使用Kaplan-Meier曲线、风险因素图和Cox回归模型评估基线HSI与终点事件风险之间的关系,同时使用广义相加模型确定线性关系。C统计量、综合判别改善(IDI)和净重新分类指数(NRI)用于评估HSI增量对终点事件的预测价值。

结果

共有2467名参与者纳入分析,并根据其HSI四分位数分为四组(Q1-Q4)。Kaplan-Meier生存曲线表明,Q4组患者的生存时间最短。Q4组的MACCE风险(风险比[HR],2.95;95%置信区间[CI]:1.99-4.39;P<0.001)、心脏事件风险(HR,2.80;95%CI:1.68-4.66;P<0.001)和脑血管事件风险(HR,3.21;95%CI:1.71-6.03;P<0.001)也显著更高。剂量反应曲线显示HSI与终点事件的发生之间存在线性关联。HSI每增加一个单位,MACCE、心脏事件和脑血管事件的风险分别增加43%、38%和51%。C统计量、IDI和NRI均表明,与传统模型相比,包含HSI的模型对终点事件具有更好的判别和分类效能(P<0.05)。

结论

HSI与高血压OSA患者的MACCE风险呈线性关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab5/11273115/7cafa6ac2f87/2153-8174-24-10-280-g1.jpg

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