ICU病人生理参数监测技术的研究进展
摘要: 生理参数监测是指导临床医护人员定量评估、诊断和治疗重症患者的必要手段。心电、血压、血氧、呼吸和体温等是ICU病人最基本的生命体征,目前监测方法相对成熟,未来主要发展方向是精准化、舒适化和无线化。血流动力学、氧代谢和微循环等指标是急危重病人救治过程中需要深入关注的内容,相关监测技术在近年来取得了显著进步,未来发展趋势是减少创伤以及提高准确度和易用性。随着机器视觉和数据融合技术的应用,病人行为和病情恶化等状态的自动识别问题逐渐成为国际前沿热点。该研究聚焦物理测量,针对ICU中的主要病症对象,分析和总结参数监测技术的研究现状,旨在为日后重症监测的相关研究提供参考。
Abstract: Physiological parameters monitoring is essential to direct medical staff to evaluate, diagnose and treat critical patients quantitatively. ECG, blood pressure, SpO2, respiratory rate and body temperature are the basic vital signs of patients in the ICU. The measuring methods are relatively mature at present, and the trend is to be wireless and more accurate and comfortable. Hemodynamics, oxygen metabolism and microcirculation should be taken seriously during the treatment of acute critical patients. The related monitoring technology has made significant progress in recent years, the trend is to reduce the trauma and improve the accuracy and usability. With the development of machine vision and data fusion technology, the identification of patient behavior and deterioration has become hot topics. This review is focused on current parameters monitoring technologies, aims to provide reference for future related research.
[1] 刘大为. 实用重症医学[M]. 2版. 北京: 人民卫生出版社, 2017. [2]EDE J, VOLLAM S, DARBYSHIRE J L, et al. Non-contact vital sign monitoring of patients in an intensive care unit: A human factors analysis of staff expectations[J]. Appl Ergon, 2021, 90: 103149.
[3] 管向东. 融合与创新: 重症医学发展的灵魂[J]. 中华重症医学电子杂志(网络版), 2019, 5(2): 89-92. [4]ANGUS D C, VAN DER POLL T. Severe sepsis and septic shock[J]. N Engl J Med, 2013, 369(21): 2063.
[5] 中华医学会心血管病学分会心血管急重症学组. 心原性休克诊断和治疗中国专家共识(2018)[J]. 中华心血管病杂志, 2019, 47(4): 265-277. [6] 刘良明, 白祥军, 李涛, 等. 创伤失血性休克早期救治规范[J]. 创伤外科杂志, 2017, 19(12): 881-883. [7]THOMPSON B T, CHAMBERS R C, KATHLEEN D L. Acute respiratory distress syndrome [J]. New Engl J Med, 2017, 377(6): 562-572.
[8] 边素艳, 曹丰, 程庆砾, 等. 感染诱发的老年多器官功能障碍综合征诊治中国专家共识[J]. 中国实用内科杂志, 2018, 38(8): 727-738. [9]ZAMAN S U, TAO X Y, COCHRANE C, et al. Understanding the washing damage to textile ECG dry skin electrodes, embroidered and fabric-based; set up of equivalent laboratory tests[J]. Sensors (Basel), 2020, 20(5): E1272.
[10]MAJUMDER S, CHEN L, MARINOV O, et al. Noncontact wearable wireless ECG systems for long-term monitoring[J]. IEEE Rev Biomed Eng, 2018, 11: 306-321.
[11]ATTIA Z I, NOSEWORTHY P A, LOPEZ-JIMENEZ F, et al. An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: A retrospective analysis of outcome prediction[J]. Lancet, 2019, 394(10201): 861-867.
[12]LUCAS A, LIN Y W, DONG S H, et al. Applications of machine learning algorithms in predicting coronary artery disease and myocardial infarction[Z].
[13]SU J W, DAI J, GUAN Z H, et al. A four-lead real time arrhythmia analysis algorithm[C]. 2017 Computing in Cardiology Conference (CinC). Computing in Cardiology, 2017(44):1-4.
[14]SU J W, LIU S C, SUN Z H, et al. Real-time fusion of ECG and SpO2 signals to reduce false alarms[C]. 2018 Computing in Cardiology Conference (CinC). Computing in Cardiology, 2018(45): 1-4.
[15]HUYNH T H, JAFARI R, CHUNG W Y. Noninvasive cuffless blood pressure estimation using pulse transit time and impedance plethysmography[J]. IEEE Trans Biomed Eng, 2019, 66(4): 967-976.
[16] 韩锋, 张静静, 骆艳妮, 等. 102例危重病患者有创血压和无创血压的对比[J]. 中华重症医学电子杂志(网络版), 2019, 5(1): 15-19. [17] 童禹浩, 叶艳, 曾敏, 等. ICU危重患者无创脉搏血氧饱和度监测临床应用现状[J]. 现代临床医学, 2019, 45(5): 382-384. [18]WANG G M, ZHANG S M, DONG S R, et al. Stretchable optical sensing patch system integrated heart rate, pulse oxygen saturation, and sweat pH detection[J]. IEEE Trans Biomed Eng, 2019, 66(4): 1000-1005.
[19]ALHARBI S, HU S, MULVANEY D, et al. Oxygen saturation measurements from green and orange illuminations of multi-wavelength optoelectronic patch sensors[J]. Sensors (Basel), 2018, 19(1): E118.
[20]XU K, JIANG X Y, CHEN W. Photoplethysmography motion artifacts removal based on signal-noise interaction modeling utilizing envelope filtering and time-delay neural network[J]. IEEE Sens J, 2020, 20(7): 3732-3744.
[21]XIE F, LIANG K K, WU W M, et al. Research on characteristics of morphological filters[J]. J Phys: Conf Ser, 2019, 1176: 042037.
[22]ALHARBI S, HU S, MULVANEY D, et al. An applicable approach for extracting human heart rate and oxygen saturation during physical movements using a multi-wavelength illumination optoelectronic sensor system[C].SPIE BiOS. Proc SPIE 10486, Design and Quality for Biomedical Technologies XI, San Francisco, California, USA. 2018, 1048: 104860S.
[23]BAO X, HOWARD M, NIAZI I K, et al. Comparison between embroidered and gel electrodes on ECG-derived respiration rate[J]. Annu Int Conf IEEE Eng Med Biol Soc, 2020, 2020: 2622-2625.
[24]RASHEED A, IRANMANESH E, LI W W, et al. An active self-driven piezoelectric sensor enabling real-time respiration monitoring[J]. Sensors (Basel), 2019, 19(14): E3241.
[25]KIM D H, LEE E, KIM J, et al. A sleep apnea monitoring IC for respiration, heart-rate, SpO2 and pulse-transit time measurement using thermistor, PPG and body-channel communication[J]. IEEE Sens J, 2020, 20(4): 1997-2007.
[26]KARACOCUK G, H FLINGER F, ZHANG R, et al. Inertial sensor-based respiration analysis[J]. IEEE Trans Instrum Meas, 2019, 68(11): 4268-4275.
[27]STREKALOV D V, THOMPSON R J, BAUMGARTEL L M, et al. Temperature measurement [J]. Biomed Tech, 2011, 56:241-257.
[28]NONOSE Y, SATO Y, KABAYAMA H, et al. Accuracy of recorded body temperature of critically ill patients related to measurement site: A prospective observational study[J]. Anaesth Intensive Care, 2012, 40(5): 820-824.
[29]ANEKWE D E, MILNER S C, BUSSI RES A, et al. Intensive care unit clinicians identify many barriers to, and facilitators of, early mobilisation: A qualitative study using the Theoretical Domains Framework[J]. J Physiother, 2020, 66(2): 120-127.
[30] 谢志毅, 张振宇, 朱研, 等. 前臂平衡压预测容量负荷试验对重症少尿患者增加尿量的研究初探[J]. 中华内科杂志, 2018, 57(6): 418-422. [31] 谢志毅, 王仲, 许媛, 等. 不同阻断血流时间对前臂平衡压的影响及与全身血流动力学指标的相关性[J]. 中华内科杂志, 2017, 56(5): 349-352. [32]MAAS J J, PINSKY M R, GEERTS B F, et al. Estimation of mean systemic filling pressure in postoperative cardiac surgery patients with three methods[J]. Intensive Care Med, 2012, 38(9): 1452-1460.
[33] 陈德昌. 血流动力学与肺动脉漂浮导管——不学病理生理学不能取得根本性的进展[J]. 中华危重病急救医学. 2012, 24(8): 449-450. [34] 张家平, 王唯依. 脉搏轮廓心排血量监测技术在严重烧伤治疗中应用的全国专家共识(2018版)[J]. 中华损伤与修复杂志(电子版), 2018, 13(6): 416-420. [35] 沈浩, 王龙, 张宏. 连续血流动力学监测LiDCO系统的临床研究进展[J]. 北京医学, 2019, 41(8): 723-725. [36]KAUFMANN T, CLEMENT R P, HIEMSTRA B, et al. Disagreement in cardiac output measurements between fourth-generation FloTrac and critical care ultrasonography in patients with circulatory shock: A prospective observational study[J]. J Intensive Care, 2019, 7: 21.
[37] 刘大为. 临床血流动力学30年[J]. 协和医学杂志, 2019, 10(5): 433-437. [38] 刘大为. 临床血流动力学[M]. 北京: 人民卫生出版社, 2013. [39]ABUT Y C. Monitoring tissue perfusion in shock: From physiology to the bedside[J]. Anesth Analg, 2019, 128(6): 1.
[40] 胡帅, 韩志岩, 王晓建, 等. 中心静脉氧饱和度替代混合静脉氧饱和度对先天性心脏病合并肺动脉高压术后的监护价值: 多中心前瞻性研究[J]. 协和医学杂志, 2018, 9(3): 228-233. [41]HERNER A, HALLER B, MAYR U, et al. Accuracy and precision of ScvO2 measured with the CeVOX-device: A prospective study in patients with a wide variation of ScvO2-values[J]. PLoS One, 2018, 13(4): e0192073.
[42]BERG A N, CONZEMIUS M G, EVANS R B, et al. Evaluation of tissue oxygen saturation in naturally occurring canine shock patients[J]. J Vet Emerg Crit Care (San Antonio), 2019, 29(2): 149-153.
[43] 邵劲松, 周立新, 誉铁鸥. 气道压力释放通气模式对严重创伤患者胃黏膜pH的影响[J]. 国际呼吸杂志, 2019, 39(15): 1157-1162. [44]PALAGYI P, KASZAKI J, MOLNAR Z. Monitoring microcirculatory blood flow with a new sublingual tonometer in a porcine model of haemorrhagic shock[J]. Crit Care, 2013, 17(suppl 2): P210.
[45]KIM J Y, YOON Y H, LEE S W, et al. Accuracy of transcutaneous carbon dioxide monitoring in hypotensive patients[J]. Emerg Med J, 2014, 31(4): 323-326.
[46]NEUSCHWANDER A, COUFFIN S, HUYNH T M, et al. Determinants of transcutaneous ear lobe CO2 tension (PtCO2) at 37℃ during on-pump cardiac surgery[J]. J Cardiothorac Vasc Anesth, 2015, 29(4): 917-923.
[47]HE H W, LIU D W, LONG Y, et al. The transcutaneous oxygen challenge test: A noninvasive method for detecting low cardiac output in septic patients[J]. Shock, 2012, 37(2): 152-155.
[48]INCE C, BOERMA E C, CECCONI M, et al. Second consensus on the assessment of sublingual microcirculation in critically ill patients: Results from a task force of the European Society of Intensive Care Medicine[J]. Intensive Care Med, 2018, 44(3): 281-299.
[49]GRONER W, WINKELMAN J W, HARRIS A G, et al. Orthogonal polarization spectral imaging: A new method for study of the microcirculation[J]. Nat Med, 1999, 5(10): 1209-1212.
[50]GOEDHART P T, KHALILZADA M, BEZEMER R, et al. Sidestream Dark Field (SDF) imaging: A novel stroboscopic LED ring-based imaging modality for clinical assessment of the microcirculation[J]. Opt Express, 2007, 15(23): 15101-15114.
[51]DEN OS M M, VAN DEN BROM C E, VAN LEEUWEN A L I, et al. Microcirculatory perfusion disturbances following cardiopulmonary bypass: A systematic review[J]. Crit Care, 2020, 24(1): 218.
[52]AMSON H, VACHERON C H, THIOLLIERE F, et al. Core-to-skin temperature gradient measured by thermography predicts day-8 mortality in septic shock: A prospective observational study[J]. J Crit Care, 2020, 60: 294-299.
[53]HAQUE A, MILSTEIN A, LI F F. Illuminating the dark spaces of healthcare with ambient intelligence[J]. Nature, 2020, 585(7824): 193-202.
[54]HYLAND S L, FALTYS M, H SER M, et al. Early prediction of circulatory failure in the intensive care unit using machine learning[J]. Nat Med, 2020, 26(3): 364-373.
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