• 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

Spectral analysis of systemic arterial pressure and heart rate signals as a prognostic tool for the prediction of patient outcome in the intensive care unit.

作者信息

Yien H W, Hseu S S, Lee L C, Kuo T B, Lee T Y, Chan S H

机构信息

Department of Anesthesiology, Veterans General Hospital-Taipei, Taiwan, Republic of China.

出版信息

Crit Care Med. 1997 Feb;25(2):258-66. doi: 10.1097/00003246-199702000-00011.

DOI:10.1097/00003246-199702000-00011
PMID:9034261
Abstract

OBJECTIVES

To evaluate the applicability of changes in spectra of systemic arterial pressure and heart rate signals in the prediction of patient outcome in an adult intensive care unit (ICU). To compare the prognostic predictability of this method with the Acute Physiology and Chronic Health Evaluation II (APACHE II) scoring system.

DESIGN

Prospective data collection from 52 ICU patients.

SETTING

Adult ICU at a large, university-affiliated, medical center.

PATIENTS

Consecutive patients who were admitted to the adult ICU due to noncardiac emergencies, and who remained for at least 2 days.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The demographic data, diagnosis, and survival data were recorded for each patient enrolled in this study. For the period between admission and 24 hrs before discharge, the APACHE II score was tabulated daily. Likewise, continuous, on-line, and real-time spectral analysis of systemic arterial pressure and heart rate signals was carried out every day for at least 30 mins at 2200 to 2400 hrs. The averaged power density values during this 30-min recording period of the high-frequency (0.15 to 0.4 Hz), low-frequency (0.08 to 0.15 Hz), and very low-frequency (0.016 to 0.08 Hz) components of systemic arterial pressure and heart rate signals were subsequently computed. Systemic vascular resistance index and cardiac index were also determined daily. We observed a trend of changes in the spectral components of systemic arterial pressure and heart rate signals in patients who eventually survived (n = 25) or died (n = 27). Progressive increases in the power density values of both the low-frequency and very low-frequency components of systemic arterial pressure and heart rate signals appeared to be related to recovery. Conversely, progressive decreases in the power density values of these spectral components was indicative of deterioration and fatality. The predicted outcome based on the trend of changes in the low-frequency and very low-frequency components of systemic arterial pressure and heart rate signals correlated positively with daily APACHE II scores. No direct correlation, however, was indicated by mean systemic arterial pressure, heart rate, systemic vascular resistance index, and cardiac index. We also confirmed that the differential trend of spectral changes in patients who survived or died was not due to circadian rhythm, nor alterations in the responsiveness of the blood vessels to intravenous infusion of dopamine.

CONCLUSION

Power spectral analysis of systemic arterial pressure and heart rate signals offers a reasonable means of monitoring acute, critically ill patients, and may be used as an alternative prognostic tool for the prediction of patient outcome in the ICU.

摘要

相似文献

1
Spectral analysis of systemic arterial pressure and heart rate signals as a prognostic tool for the prediction of patient outcome in the intensive care unit.
Crit Care Med. 1997 Feb;25(2):258-66. doi: 10.1097/00003246-199702000-00011.
2
Spectral analysis of systemic arterial pressure and heart rate signals of patients with acute respiratory failure induced by severe organophosphate poisoning.
Crit Care Med. 2000 Aug;28(8):2805-11. doi: 10.1097/00003246-200008000-00021.
3
Acute physiology and chronic health evaluation (APACHE II) and Glasgow coma scores as predictors of outcome from intensive care after cardiac arrest.急性生理学与慢性健康状况评估(APACHE II)及格拉斯哥昏迷评分作为心脏骤停后重症监护结局的预测指标。
Crit Care Med. 1991 Dec;19(12):1465-73. doi: 10.1097/00003246-199112000-00005.
4
Verification of the Acute Physiology and Chronic Health Evaluation scoring system in a Hong Kong intensive care unit.香港一间重症监护病房中急性生理学与慢性健康状况评估评分系统的验证
Crit Care Med. 1993 May;21(5):698-705. doi: 10.1097/00003246-199305000-00013.
5
Outcome and prognostic factors in critically ill cancer patients admitted to the intensive care unit.入住重症监护病房的重症癌症患者的结局及预后因素
Crit Care Med. 2000 May;28(5):1322-8. doi: 10.1097/00003246-200005000-00011.
6
Scoring systems in cancer patients admitted for an acute complication in a medical intensive care unit.入住医疗重症监护病房并出现急性并发症的癌症患者的评分系统。
Crit Care Med. 2000 Aug;28(8):2786-92. doi: 10.1097/00003246-200008000-00018.
7
Use of daily Acute Physiology and Chronic Health Evaluation (APACHE) II scores to predict individual patient survival rate.
Crit Care Med. 1994 Sep;22(9):1402-5. doi: 10.1097/00003246-199409000-00008.
8
Microalbuminuria in the intensive care unit: Clinical correlates and association with outcomes in 431 patients.重症监护病房中的微量白蛋白尿:431例患者的临床关联及与预后的关系
Crit Care Med. 2006 Aug;34(8):2158-66. doi: 10.1097/01.CCM.0000228914.73550.BD.
9
Evaluation of predictive ability of APACHE II system and hospital outcome in Canadian intensive care unit patients.评估APACHE II系统对加拿大重症监护病房患者的预测能力及医院治疗结果。
Crit Care Med. 1995 Jul;23(7):1177-83. doi: 10.1097/00003246-199507000-00005.
10
A comparison of the Acute Physiology and Chronic Health Evaluation (APACHE) II score and the Trauma-Injury Severity Score (TRISS) for outcome assessment in intensive care unit trauma patients.急性生理学与慢性健康状况评估(APACHE)II评分与创伤严重程度评分(TRISS)在重症监护病房创伤患者预后评估中的比较。
Crit Care Med. 1996 Oct;24(10):1642-8. doi: 10.1097/00003246-199610000-00007.

引用本文的文献

1
Predictors of Anemia Intolerance for Real-Time Transfusion Decision-Making During Resuscitation of Trauma Subjects: A Machine Learning Approach Using Heart Rate Variability.创伤患者复苏期间实时输血决策中贫血不耐受的预测因素:一种使用心率变异性的机器学习方法
Crit Care Explor. 2025 Sep 22;7(10):e1319. doi: 10.1097/CCE.0000000000001319. eCollection 2025 Oct 1.
2
Test-retest reliability of transfer function analysis metrics for assessing dynamic cerebral autoregulation to spontaneous blood pressure oscillations.评估自发性血压波动的传递函数分析指标的重测信度。
Exp Physiol. 2024 Jul;109(7):1024-1039. doi: 10.1113/EP091500. Epub 2024 Apr 8.
3
Defining predictors for successful mechanical ventilation weaning, using a data-mining process and artificial intelligence.
使用数据挖掘和人工智能定义机械通气撤机成功的预测因素。
Sci Rep. 2023 Nov 22;13(1):20483. doi: 10.1038/s41598-023-47452-7.
4
Association between circadian variation of heart rate and mortality among critically ill patients: a retrospective cohort study.心率昼夜节律变化与危重症患者死亡率的关系:一项回顾性队列研究。
BMC Anesthesiol. 2022 Feb 12;22(1):45. doi: 10.1186/s12871-022-01586-9.
5
[Predicting prolonged length of intensive care unit stay machine learning].[预测重症监护病房长期住院时间 机器学习]
Beijing Da Xue Xue Bao Yi Xue Ban. 2021 Dec 18;53(6):1163-1170. doi: 10.19723/j.issn.1671-167X.2021.06.026.
6
Use of heart rate variability to predict hospital length of stay for COVID-19 patients: A prospective observational study.利用心率变异性预测新冠病毒肺炎患者的住院时间:一项前瞻性观察性研究。
Int J Crit Illn Inj Sci. 2021 Jul-Sep;11(3):134-141. doi: 10.4103/IJCIIS.IJCIIS_196_20. Epub 2021 Sep 25.
7
Autonomic biomarkers of shock in idiopathic systemic capillary leak syndrome.特发性全身性毛细血管渗漏综合征休克的自主生物标志物。
PLoS One. 2021 Jun 1;16(6):e0251775. doi: 10.1371/journal.pone.0251775. eCollection 2021.
8
Physiological and pathophysiological evaluation of baroreflex functionality with concurrent diffusion tensor imaging of its neural circuit in the rat.应用扩散张量成像技术对大鼠压力反射功能及其神经回路的生理学和病理生理学评估。
Biomed J. 2019 Dec;42(6):381-393. doi: 10.1016/j.bj.2019.10.006. Epub 2019 Dec 24.
9
Dose-Dependent Acute Circulatory Fates Elicited by Cadmium Are Mediated by Differential Engagements of Cardiovascular Regulatory Mechanisms in Brain.镉引发的剂量依赖性急性循环命运是由大脑中心血管调节机制的不同参与介导的。
Front Physiol. 2019 Jun 18;10:772. doi: 10.3389/fphys.2019.00772. eCollection 2019.
10
Baroreflex functionality in the eye of diffusion tensor imaging.扩散张量成像眼中的压力感受反射功能。
J Physiol. 2019 Jan;597(1):41-55. doi: 10.1113/JP277008. Epub 2018 Nov 2.