• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

心率波动可预测重症监护病房危重症患者的死亡率：一项回顾性队列研究。

Heart rate fluctuation predicts mortality in critically ill patients in the intensive care unit: a retrospective cohort study.

作者信息

Guo Qi, Xiao Zhanchao, Lin Maohuan, Yuan Guiyi, Qiu Qiong, Yang Ying, Zhao Huiying, Zhang Yuling, Zhou Shuxian, Wang Jingfeng

机构信息

Department of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.

Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Guangzhou, China.

出版信息

Ann Transl Med. 2021 Feb;9(4):334. doi: 10.21037/atm-20-7897.

DOI:10.21037/atm-20-7897
PMID:33708961
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7944303/
Abstract

BACKGROUND

To evaluate the association between heart rate (HR) fluctuation and mortality in critically ill patients in the intensive care unit (ICU).

METHODS

A total of 27,814 patients were enrolled from the Medical Information Mart for Intensive Care database and were divided into 3 groups: low HR fluctuation [<25 beats per minute (bpm)], control (25-34 bpm), and high HR fluctuation (≥35 bpm), based on the initial 24-hour HR fluctuation (calculated as the maximum HR minus minimum HR). Multivariate Cox regression and restricted cubic spline models were used.

RESULTS

Compared to the control group, higher risk of 28-day and 1-year mortality remained significant in an adjusted model, with hazard ratios of 1.210 [95% confidence interval (CI), 1.103-1.327] and 1.150 (95% CI, 1.078-1.227), respectively, in the high HR fluctuation group, as well as hazard ratios of 1.130 (95% CI, 1.035-1.232) and 1.087 (95% CI, 1.022-1.157), respectively, in the low HR fluctuation group. Restricted cubic splines showed a U-type curve, with the lowest risk of mortality at an HR fluctuation of 30 bpm.

CONCLUSIONS

This retrospective cohort study revealed that both high and low HR fluctuation correlated with increased mortality in critically ill ICU patients, providing new insights for optimizing HR control strategies.

摘要

背景

评估重症监护病房（ICU）危重症患者心率（HR）波动与死亡率之间的关联。

方法

从重症监护医学信息数据库中纳入27814例患者，根据最初24小时的HR波动情况（计算为最高心率减去最低心率）分为3组：低HR波动[<25次/分钟（bpm）]、对照组（25 - 34 bpm）和高HR波动（≥35 bpm）。使用多变量Cox回归和受限立方样条模型。

结果

与对照组相比，在调整模型中，高HR波动组28天和1年死亡率的风险仍然显著升高，风险比分别为1.210 [95%置信区间（CI），1.103 - 1.327]和1.150（95% CI，1.078 - 1.227），低HR波动组的风险比分别为1.130（95% CI，1.035 - 1.232）和1.087（95% CI，1.022 - 1.157）。受限立方样条显示为U型曲线，HR波动为30 bpm时死亡率风险最低。

结论

这项回顾性队列研究表明，高HR波动和低HR波动均与ICU危重症患者死亡率增加相关，为优化HR控制策略提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fae/7944303/f565b1967aba/atm-09-04-334-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fae/7944303/c3b78cf5d203/atm-09-04-334-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fae/7944303/8159c91c5f0e/atm-09-04-334-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fae/7944303/b1518afd10dc/atm-09-04-334-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fae/7944303/a8666ed77faf/atm-09-04-334-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fae/7944303/f565b1967aba/atm-09-04-334-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fae/7944303/c3b78cf5d203/atm-09-04-334-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fae/7944303/8159c91c5f0e/atm-09-04-334-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fae/7944303/b1518afd10dc/atm-09-04-334-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fae/7944303/a8666ed77faf/atm-09-04-334-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fae/7944303/f565b1967aba/atm-09-04-334-f5.jpg

相似文献

1
Heart rate fluctuation predicts mortality in critically ill patients in the intensive care unit: a retrospective cohort study.心率波动可预测重症监护病房危重症患者的死亡率：一项回顾性队列研究。
Ann Transl Med. 2021 Feb;9(4):334. doi: 10.21037/atm-20-7897.
2
Heart Rate Fluctuation and Mortality in Critically Ill Myocardial Infarction Patients: A Retrospective Cohort Study.重症心肌梗死患者的心率波动与死亡率：一项回顾性队列研究
Front Cardiovasc Med. 2021 May 14;8:577742. doi: 10.3389/fcvm.2021.577742. eCollection 2021.
3
Early heart rate fluctuation and outcomes in critically ill patients with sepsis: A retrospective cohort study of the MIMIC-IV database.脓毒症重症患者的早期心率波动与预后：一项基于MIMIC-IV数据库的回顾性队列研究
Heliyon. 2023 Oct 11;9(10):e20898. doi: 10.1016/j.heliyon.2023.e20898. eCollection 2023 Oct.
4
Minimum heart rate and mortality in critically ill myocardial infarction patients: an analysis of the MIMIC-III database.危重症心肌梗死患者的最低心率与死亡率：MIMIC-III数据库分析
Ann Transl Med. 2021 Mar;9(6):496. doi: 10.21037/atm-21-992.
5
Association between heart rate and mortality in patients with septic shock: an analysis revealed by time series data.脓毒性休克患者心率与死亡率之间的关联：一项基于时间序列数据的分析揭示
BMC Infect Dis. 2024 Oct 1;24(1):1088. doi: 10.1186/s12879-024-10004-z.
6
Admission Heart Rate and Mortality in Critically Ill Patients with Acute Aortic Dissection.急性主动脉夹层危重症患者的入院心率与死亡率。
Int Heart J. 2023 Mar 31;64(1):44-52. doi: 10.1536/ihj.22-346. Epub 2023 Jan 31.
7
Effect of mean heart rate on 30-day mortality in ischemic stroke with atrial fibrillation: Data from the MIMIC-IV database.平均心率对合并心房颤动的缺血性卒中患者30天死亡率的影响：来自MIMIC-IV数据库的数据
Front Neurol. 2022 Oct 31;13:1017849. doi: 10.3389/fneur.2022.1017849. eCollection 2022.
8
The association between intensive care unit-acquired hypernatraemia and mortality in critically ill patients with cerebrovascular diseases: a single-centre cohort study in Japan.重症监护病房获得性高钠血症与脑血管疾病重症患者死亡率之间的关联：日本一项单中心队列研究
BMJ Open. 2017 Aug 18;7(8):e016248. doi: 10.1136/bmjopen-2017-016248.
9
Bradycardia and Heart Rate Fluctuation Are Associated with a Prolonged Intensive Care Unit Stay in Patients with Severe COVID-19.心动过缓和心率波动与重症 COVID-19 患者 ICU 住院时间延长相关。
Medicina (Kaunas). 2022 Jul 19;58(7):950. doi: 10.3390/medicina58070950.
10
Serum anion gap is associated with mortality in intensive care unit patients with diastolic heart failure.血清阴离子间隙与舒张性心力衰竭重症监护病房患者的死亡率相关。
Sci Rep. 2023 Oct 4;13(1):16670. doi: 10.1038/s41598-023-43928-8.

引用本文的文献

1
Association between heart rate fluctuation and mortality in intensive care patients with atrial fibrillation.重症监护病房房颤患者心率波动与死亡率之间的关联。
Sci Rep. 2025 Aug 21;15(1):30801. doi: 10.1038/s41598-025-15875-z.
2
The search for optimal nocturnal diurnal heart rate Index targets in ICU patients: a retrospective observational study from large ICU database.在重症监护病房患者中寻找最佳夜间-日间心率指数目标：一项基于大型重症监护病房数据库的回顾性观察研究。
Front Cardiovasc Med. 2024 Jul 8;11:1415467. doi: 10.3389/fcvm.2024.1415467. eCollection 2024.
3
Use of portable single-lead electrocardiogram device as an alternative for QTc monitoring in critically ill patients.

本文引用的文献

1
Effect of resting heart rate on the risk of all-cause death in Chinese patients with hypertension: analysis of the Kailuan follow-up study.静息心率对中国高血压患者全因死亡风险的影响：开滦随访研究分析。
BMJ Open. 2020 Mar 10;10(3):e032699. doi: 10.1136/bmjopen-2019-032699.
2
Chronobiological Influence Over Cardiovascular Function: The Good, the Bad, and the Ugly.生物钟对心血管功能的影响：好的、坏的和丑的。
Circ Res. 2020 Jan 17;126(2):258-279. doi: 10.1161/CIRCRESAHA.119.313349. Epub 2020 Jan 16.
3
Relationship between heart rate and outcomes in patients in sinus rhythm or atrial fibrillation with heart failure and reduced ejection fraction.
在危重症患者中，使用便携式单导联心电图设备替代 QTc 监测。
Ann Noninvasive Electrocardiol. 2024 May;29(3):e13116. doi: 10.1111/anec.13116.
4
Identifying vital sign trajectories to predict 28-day mortality of critically ill elderly patients with acute respiratory distress syndrome.识别生命体征轨迹预测急性呼吸窘迫综合征危重症老年患者 28 天死亡率。
Respir Res. 2024 Jan 4;25(1):8. doi: 10.1186/s12931-023-02643-8.
5
Early heart rate fluctuation and outcomes in critically ill patients with sepsis: A retrospective cohort study of the MIMIC-IV database.脓毒症重症患者的早期心率波动与预后：一项基于MIMIC-IV数据库的回顾性队列研究
Heliyon. 2023 Oct 11;9(10):e20898. doi: 10.1016/j.heliyon.2023.e20898. eCollection 2023 Oct.
6
Clinical surrogates of dysautonomia predict lethal outcome in COVID-19 on intensive care unit.自主神经功能障碍的临床替代指标可预测新冠病毒病患者在重症监护病房的致死结局。
Neurol Res Pract. 2023 May 4;5(1):17. doi: 10.1186/s42466-023-00243-x.
7
Bradycardia and Heart Rate Fluctuation Are Associated with a Prolonged Intensive Care Unit Stay in Patients with Severe COVID-19.心动过缓和心率波动与重症 COVID-19 患者 ICU 住院时间延长相关。
Medicina (Kaunas). 2022 Jul 19;58(7):950. doi: 10.3390/medicina58070950.
8
Admission Resting Heart Rate as an Independent Predictor of All-Cause Mortality in Elderly Patients with Hip Fracture.入院静息心率作为老年髋部骨折患者全因死亡率的独立预测因素
Int J Gen Med. 2021 Nov 4;14:7699-7706. doi: 10.2147/IJGM.S333971. eCollection 2021.
9
Heart Rate Fluctuation and Mortality in Critically Ill Myocardial Infarction Patients: A Retrospective Cohort Study.重症心肌梗死患者的心率波动与死亡率：一项回顾性队列研究
Front Cardiovasc Med. 2021 May 14;8:577742. doi: 10.3389/fcvm.2021.577742. eCollection 2021.
心率与心力衰竭和射血分数降低的窦性心律或心房颤动患者结局的关系。
Eur J Heart Fail. 2020 Mar;22(3):528-538. doi: 10.1002/ejhf.1682. Epub 2019 Dec 17.
4
Heart rate control using beta-blockers for heart failure with atrial fibrillation: more than enough is too much.使用β受体阻滞剂控制心率治疗伴有心房颤动的心力衰竭：过犹不及。
Hypertens Res. 2019 Nov;42(11):1826-1827. doi: 10.1038/s41440-019-0303-x. Epub 2019 Jul 30.
5
The current application of the Royston-Parmar model for prognostic modeling in health research: a scoping review.Royston-Parmar模型在健康研究预后建模中的当前应用：一项范围综述
Diagn Progn Res. 2018 Feb 7;2:4. doi: 10.1186/s41512-018-0026-5. eCollection 2018.
6
Circadian rhythms and the molecular clock in cardiovascular biology and disease.昼夜节律和分子钟在心血管生物学和疾病中的作用。
Nat Rev Cardiol. 2019 Jul;16(7):437-447. doi: 10.1038/s41569-019-0167-4.
7
Higher heart rates increase risk of diabetes and cardiovascular events: A prospective cohort study among Inner Mongolians.心率升高增加糖尿病和心血管事件风险：一项针对内蒙古人群的前瞻性队列研究。
Diabetes Metab. 2020 Feb;46(1):20-26. doi: 10.1016/j.diabet.2019.01.002. Epub 2019 Jan 11.
8
Impact of Mean Arterial Pressure Fluctuation on Mortality in Critically Ill Patients.平均动脉压波动对危重症患者死亡率的影响。
Crit Care Med. 2018 Dec;46(12):e1167-e1174. doi: 10.1097/CCM.0000000000003435.
9
Determinants of heart rate variability in the general population: The Lifelines Cohort Study.一般人群中心率变异性的决定因素：莱夫兰队列研究。
Heart Rhythm. 2018 Oct;15(10):1552-1558. doi: 10.1016/j.hrthm.2018.05.006. Epub 2018 May 9.
10
Heart rate variability as predictive factor for sudden cardiac death.心率变异性作为心脏性猝死的预测因素。
Aging (Albany NY). 2018 Feb 23;10(2):166-177. doi: 10.18632/aging.101386.