(2009)血流动力学参数集合

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简明常用血流动力学参数意义对照表

简明常用血流动力学参数意义对照表

简明常用血流动力学参数意义对照表1. LSI 左心搏指数2. RSI 右心搏指数3. LCI 左心排指数4. RCI 右心排指数以上四个指数代表心脏的功能指数,其中左心排指数最重要,等同于心脏指数(CI),一般来说,CI<1.5=预后极差;1.5—2.0= 心源性休克;2.0—2.2=前向性心功能不全。

5. CWT 心脏总功率:反映心脏的负荷,一般运动时,功率会增大,如果正常情况总功率偏大,则代表心脏负荷偏大;偏小则视情况而定,有身体强健者,心脏功率不必很大,但器质性偏小,则有可能造成供血不足,头晕眼花等等。

6. LWE 左心室有效功率7. LTPF 左心室总泵力8. LWT 左心室功率9. LEWK 左心室机械效率10. JP 左心室喷血压力:该指数与血压有关,如果该指数偏大,则需要小心高血压了。

11. VP 左心室有效泵力12. EF 喷血分数:非常重要的指标,EF值长期偏小,则有很大可能性是心衰。

13. AWK 动脉机械效率14. EPE 射流压力15. LCRI 左室等容指数16. RCRI 右室等容指数15/16两个参数代表心脏的容血量,其意义不如有效循环容量重要。

17. LVDV 左室舒张末血量18. LVDP 左室舒末期压力19. CR 左室喷血阻抗20. PDM 平均舒张压:高血压的判断指标之一21. PSM 平均收缩压:高血压的判断指标之一22. PPM 平均脉压:高血压的判断指标之一23. MAP 平均动脉压:高血压的判断指标之一24. HR 心率25. CVPS 中心静脉收缩压26. CVPM 中心静脉平均压:非常重要的指标严重升高:1.静脉充盈过量(循环超负荷)2.静脉充血(心脏压塞、PEEP右心衰、左心衰晚期)3.左向右分流,严重二尖瓣狭窄右室收缩力下降4.肺血管壁阻力增高(肺水肿、COPD)严重降低:容量不足、血管过度扩张27. PAWPS 肺毛收缩压28. PAWPM 肺毛平均压(肺毛细血管嵌顿压):抽烟过量或者感冒或肺部病变可能导致该值不正常。

正常血流动力学参数表

正常血流动力学参数表
HR< SV/1000
4.0〜8.0L/min
心排指数(CI)
CO/BSA
2
2.5〜4.0L/min/m
每搏量(SV
CO/HR<1000
60〜100ml/次
每搏指数(SVI)
CI/HRX1000
35〜60ml/次/m2
体循环阻力(SVR
80X(MAIRAP /CO
5
800〜1200dyn•s/cm
体循环阻力指数(SVRI)
SVX(MAP—PAWP)X0.0136
58〜104gm-m/次
左室做功指数(LVSWI)
SVIX(MAP—PAWP)X0.0136
50〜62gm-m/m2/次
右室每搏功(RVSW)
SVX(MPAP—RAP)X0.0136
8〜16gm-m/次
右室做功指数(RVSWI)
SVIX(MPAP—RAP)X0.0136
80X(MAIRAP /CI
1970〜2390dyn•s/cm5/m2
肺循环阻力(PVR
80X(MPARPAWP /CO
5
v250dyn•s/cm
肺循环阻力指数(PVRI)
80X(MPARPAWP /CI
52
255〜285dyn•s/cm /m
血流动力学参数成人
参数
公式
正常范围
左室每搏功(LVSW)
右室射血分数(RVEF)
SV/EDV
40〜60%
氧代谢动力学参数成人
参数
公式
正常范围
动脉血氧分压(PaO2)
80〜100mmHg
动脉血二氧化碳分压(PaCO)
35〜45mmHg
碳酸氢根(HCO)

血液动力学参数

血液动力学参数

中文英文英文缩写心率HR动脉收缩压ABP S, SBP 动脉舒张压ABP D, DBP平均动脉压Mean arterial pressure MAP, ABP M 中心静脉压Central venous pressure CVP肺动脉收缩压pulmonary arterial systolicpressurePASP,SPAP肺动脉舒张压pulmonary arterial diastolicpressurePADP,DPAP平均肺动脉压Mean pulmonary arterialpressureMPAP, PAP M肺动脉楔压pulmonary arterial wedge pressurePAWP肺毛细血管楔压pulmonary capillary wedge pressurePCWP心排血量Cardiac output CO 心脏排血指数Index of cardiac output CI 射血分数Ejective fraction EF 射血容量(每搏量)SV 射血容量指数SVI 左房压Left atrial pressure LAP左室舒张末容量Left ventricular end-diastolicvolume LVEDV左室每搏功指数Left ventricular systolic workindex LVSWI右室每搏功指数Right ventricular systolicwork index RVSWI肺动脉收缩压PAP S 肺动脉舒张压PAP D肺循环阻力(肺血管阻力)Pulmonary resistance PVR肺血管阻力指数PVRI 体循环阻力(全身血管阻力)Systemic resistance SVR全身血管阻力指数SVRI 总外周血管阻力LCWI 左室射血做功指数LVSWIRCWI右室射血做功指数RVSWI 肺毛细血管阻断压PAPO参考文献:郭加强,心脏外科护理学。

参数解读与血流动力学讲课文档

参数解读与血流动力学讲课文档
非连续指标,正常值3.0–5.0 L/min/m2
PCCI:脉搏持续心指数
第二十二页,共34页。
第二十二页,共34页。
2、Cardiac function index(心功能指数, CFI)和Global ejection fraction(全心射血 分数,GEF)
CFI = CI / GEDVI
第二十四页,共34页。
第二十四页,共34页。
1、 Extravascular Lung Water(血管外肺水,
EVLW)
Extravascular Lung Water (EVLW) is the amount of water content in the lungs. It allows bedside
11 第十一页,共34页。
High contractility
Normal Contractility Poor contractility
volume overloaded
Preload
第十一页,共34页。
Preload, CO and Frank-Starling Mechanism
SV
V
SV
GEDI = GEDV / M,是非连续指标 不受PEEP、导管位置、心肌收缩力及顺应性影响 正常值:680–800 mL/m2
第十四页,共34页。
第十四页,共34页。
2、Intrathoracic Blood Volume(胸腔内血容量,ITBV )
Intrathoracic Blood Volume (ITBV) is the volume of the 4 chambers of the heart + the blood
评估全心收缩功能 不受前负荷因素所影响,可真正了解强心药物的药效 正常值:4.5-6.5/min

血流动力学

血流动力学

无创血流动力学参数心输出量(cardiac output,CO)、心脏指数(cardiac index,CI)是评价心功能及血流灌注的诊断指标,是机体功能发生重大变化时的早期报警。

每搏输出量(stroke volume,SV)的变化是机体血流量和心肌收缩发生变化的早期信号。

加速指数(acceleration index,ACI)、CI是评价心脏收缩功能的指标。

外周血管阻力(systemic vascular resistance ,SVR)、外周血管阻力指数(systemic vascular resistance index,SVRI)是反映心脏后负荷的参数,与外周阻力增加呈正相关,胸腔积液量(Thoracic fluid content,TFC)反映心脏前负荷。

血浆N端脑利钠肽(NT-ProBNP)是心室肌细胞合成和分泌的一种肽类物质,也被认为是一种心脏神经激素,是一种含32个氨基酸的多肽类神经激素,NT-ProBNP主要由心室肌细胞合成,当心室容积负荷和压力负荷增加时可刺激NT-ProBNP的分泌,引起排钠、利尿、扩张血管和抑制肾素--血管紧张素--醛固酮系统的效应,并且可抑制促肾上腺皮质激素的释放及交感神经的过度反应,参与调节血压、血容量和盐平衡,有排钠、利尿、扩血管等作用,它的血浆含量与心室的压力、呼吸困难的程度、神经激素调节系统的状况呈正比,NT-ProBNP 是左室收缩功能不全的最强的具有特异性的标志物,可以作为早期诊断心力衰竭的判断指标,2003年美国临床生化学会(NACB Guidelines)即把NT-ProBNP 作为早期检测CHF的标志物。

有研究发现,TFC与NT-ProBNP明显相关,收缩时间比率(Systolic Time Ratio,STR)反映心肌收缩力,STR高低与心功能恶化的严重程度有关;另有研究表明STR的变化与心脏超声射血分数值相关系数为0.85。

2012年欧洲心脏病协会(ESC)强调N末端前B型利钠肽(NT-proBNP)可用于可疑心衰患者的诊断和鉴别诊断,并强调这一生物学标志物的诊断和鉴别诊断价值,对于有症状的可疑心衰患者其阴性预测值和阳性预测值均很高,临床应用价值很高,推荐将NT-ProBNP与X线、超声心动图影像学及临床表现等结合诊断心衰并将其作为心衰的排除试验序,甚至在心衰的诊断流程中推荐先采用生物学标志物NT-ProBNP检测,而将超声心动图检查用于已确诊的心衰患者,以确定基础心血管疾病的病因、心脏损害的程度和评价心功能(如左心室射血分数)等,2013年美国心脏病学院基金会/美国心脏协会(ACCF/AHA;美国指南) 也更多的描述了这个指标在临床上的诊断意义以及对心衰严重程度和治疗效果的评价价值。

血流动力学完整版

血流动力学完整版

血流动力学标准化管理处编码[BBX968T-XBB8968-NNJ668-MM9N]是指每分钟跳动的次数,以第一声音为准。

标准心率1、正常成年人安静时的心率有显着的个体,平均在75次/分左右(60—100次/分之间)。

心率可因年龄、性别及其它生理情况而不同。

初生儿的心率很快,可达130次/分以上。

在成年人中,女性的心率一般比男性稍快。

同一个人,在安静或睡眠时心率减慢,运动时或情绪激动时心率加快,在某些药物或神经体液因素的影响下,会使心率发生加快或减慢。

经常进行体力劳动和体育锻炼的人,平时心率较慢。

近年,国内大样本健康人群调查发现:国人男性的正常范围为50—95次/分,女性为55—95次/分。

所以,心率随年龄,性别和健康状况变化而变化。

2、健康成人的心率为60~100次/分,大多数为60~80次/分,女性稍快;3岁以下的小儿常在100次/分以上;老年人偏慢。

成人每分钟心率超过100次(一般不超过 160次/分)或超过 150次/分者,称为。

常见于正常人运动、兴奋、激动、吸烟、饮酒和喝浓茶后。

也可见于发热、、贫血、甲亢、及应用、、等。

如果心率在 160~220次/分,常称为。

心率低于60次/分者(一般在40次/分以上),称为。

可见于长期从事重体力劳动和;病理性的见于机能低下、、、以及洋地黄、或类药物过量或中毒。

如心率低于40次/分,应考虑有。

超过160次/分,或低于40次/分,大多见于病人,病人常有心悸、、心前区不适,应及早进行详细检查,以便针对病因进行治疗。

心率过缓正常人心跳次数是60~100次/分,小于60就称为。

有几种类型,最常见的是。

可分为病理性及生理性两种。

生理性是正常现象,一般心率及在50~60次 /分,可能会出现40次的心率,不用治疗,常见于正常人睡眠中、较多的人。

心率或小于50次多数为病理性,需要治疗,严重者要安装来加快心率。

有生理性和病理性,是生理性不需要治疗的,是正常的反应.病理性需要治疗,主要上由于供血不足有很大关系,引起心脏负荷加重而导致的,所以治疗上应该用和药治疗相结合的方法比较好,最有效的.正常人,特别是长期参加体育锻炼或强体力劳动者,可有。

血流动力学监测各项参数与病情评估

血流动力学监测各项参数与病情评估

血流动力学监测各项参数与病情评估1. 引言血流动力学监测是对患者的心血管功能进行实时评估的重要方法。

通过监测各项参数,可以客观地评估病情和指导治疗。

本文将探讨血流动力学监测各项参数与病情评估的相关性。

2. 血流动力学监测参数2.1 心率心率是血流动力学监测的基本参数之一,反映了心脏搏动频率。

高心率可能表明心脏负荷增加或存在心律失常,而低心率可能反映心脏功能减退。

通过监测心率,可以初步评估患者的心脏功能状态。

2.2 血压血压是血流动力学监测的另一个重要参数,包括收缩压和舒张压。

收缩压反映了心脏收缩时的压力,舒张压反映了心脏舒张时的压力。

通过监测血压,可以评估患者的心脏泵血功能和外周血管阻力。

2.3 心输出量心输出量是指心脏每分钟向体循环中泵出的血液量。

心输出量的变化可以反映心脏泵血功能的改变。

通过监测心输出量,可以了解患者的心功能状态。

2.4 中心静脉压中心静脉压是指静脉血返回心脏时静脉系统内的压力。

中心静脉压的升高可能表明心脏前负荷增加或心脏泵血功能下降。

通过监测中心静脉压,可以评估患者的心脏前负荷状态。

2.5 氧饱和度氧饱和度是指血液中氧气与血红蛋白结合的程度。

通过监测氧饱和度,可以了解患者的氧供需平衡和组织氧合情况。

低氧饱和度可能提示组织缺氧。

3. 病情评估通过监测血流动力学各项参数,可以进行病情评估,包括但不限于以下方面:- 心脏功能评估:通过心率、血压和心输出量等参数的变化,可以判断心脏功能是否正常,是否存在心脏负荷过大或心脏泵血功能下降等问题。

- 血容量评估:通过中心静脉压的监测,可以了解患者的血容量状态,以指导液体管理和循环支持治疗。

- 氧代谢评估:通过氧饱和度的监测,可以了解患者的氧供需平衡,评估组织氧合情况,从而指导氧疗和呼吸支持治疗。

4. 结论血流动力学监测各项参数与病情评估密切相关。

通过监测心率、血压、心输出量、中心静脉压和氧饱和度等参数,可以客观地评估患者的心血管功能和病情变化,指导临床治疗的决策和调整。

血流动力学

血流动力学

血流动力学This manuscript was revised by the office on December 22, 2012是指每分钟跳动的次数,以第一声音为准。

标准心率1、正常成年人安静时的心率有显着的个体,平均在75次/分左右(60—100次/分之间)。

心率可因年龄、性别及其它生理情况而不同。

初生儿的心率很快,可达130次/分以上。

在成年人中,女性的心率一般比男性稍快。

同一个人,在安静或睡眠时心率减慢,运动时或情绪激动时心率加快,在某些药物或神经体液因素的影响下,会使心率发生加快或减慢。

经常进行体力劳动和体育锻炼的人,平时心率较慢。

近年,国内大样本健康人群调查发现:国人男性的正常范围为50—95次/分,女性为55—95次/分。

所以,心率随年龄,性别和健康状况变化而变化。

2、健康成人的心率为60~100次/分,大多数为60~80次/分,女性稍快;3岁以下的小儿常在100次/分以上;老年人偏慢。

成人每分钟心率超过100次(一般不超过 160次/分)或超过 150次/分者,称为。

常见于正常人运动、兴奋、激动、吸烟、饮酒和喝浓茶后。

也可见于发热、、贫血、甲亢、及应用、、等。

如果心率在 160~220次/分,常称为。

心率低于60次/分者(一般在40次/分以上),称为。

可见于长期从事重体力劳动和;病理性的见于机能低下、、、以及洋地黄、或类药物过量或中毒。

如心率低于40次/分,应考虑有。

超过160次/分,或低于40次/分,大多见于病人,病人常有心悸、、心前区不适,应及早进行详细检查,以便针对病因进行治疗。

心率过缓正常人心跳次数是60~100次/分,小于60就称为。

有几种类型,最常见的是。

可分为病理性及生理性两种。

生理性是正常现象,一般心率及在50~60次 /分,可能会出现40次的心率,不用治疗,常见于正常人睡眠中、较多的人。

心率或小于50次多数为病理性,需要治疗,严重者要安装来加快心率。

有生理性和病理性,是生理性不需要治疗的,是正常的反应.病理性需要治疗,主要上由于供血不足有很大关系,引起心脏负荷加重而导致的,所以治疗上应该用和药治疗相结合的方法比较好,最有效的.正常人,特别是长期参加体育锻炼或强体力劳动者,可有。

血流动力学参数z

血流动力学参数z
5~10gm-m/m2/次
右室每搏功指数(RVSWI)
{1.36(MAP–CVP)×SI}/100
5~10 g·m/m2
冠脉灌注压(CPP)
DBP-PAWP
60~80mmHg
左室舒张末容积(LVEDV)
左室舒张末压力(LVEDP)
右室舒张末容积(RVEDV)
SV/EF
100~160ml
右室舒张末容积指数(RVEDVI)
心输出量(CO)
HR×SV/1000
4.0~8.0L/min
心排指数(CI)
CO/BSA
2.5~4.0L/min/m2
每搏量(SV)
CO/HR×1000
60~100ml/次
每搏指数(SI)
30~65ml/次/m2
每搏指数(SVI)
CI/HR×1000
35~60ml/次/m2
每搏功(SW)
(MAP–PCWP) ×SV×0.136
>1
冠状动脉灌注压(CCP)
DBP–PCWP
血流动力学参数
参数
公式
正常范围
血压(BP)
收缩压(SBP)
90~140mmHg
舒张压(DBP)
60~90mmHg
平均动脉压(MAP)
(SBP+2DBP)/3
70~105mmHg
中心静脉压(CVP)
2~6mmHg
5~12cmH2O
右房压(RAP)
2~6mmHg
右室压(RVP)
收缩压(RVSP)
15~25mmHg
60~100ml/ m2
右室收缩末容积(RVESV)
EDV-SV
50~100ml
右室收缩末容积指数(RVESVI)

血流动力学监测参数

血流动力学监测参数

血流动力学监测参数PAdP:肺动脉舒张压*CVP与BP、血容量关系:1、CVP低,BP低,表示血容量严重不足,需大量补液。

2、CVP低,BP正常,表示血容量不足,需适当补液。

3、CVP正常,BP低,表示血容量不足或心功能不全,可进行补液试验:5~10分钟内静脉滴入等渗盐水250ml→①中心静脉压不变,血压升高,提示血容量不足,根据情况适当补液;②中心静脉压升高3~5mmHg,血压不变,提示心功能不全,根据情况给予强心药物治疗。

4、CVP高,血压低,表示心功能不全或血容量相对过多,需给予强心药物,纠正酸中毒,舒张血管治疗。

5、CVP高,血压正常,表示容量血管过度收缩,需舒张血管治疗。

CVP指导扩容的“5-2法则”:低血容量病人应连续监测CVP,当CVP<8cmH2O,10分钟内输液200ml;CVP为8~13cmH2O 时输液100ml;CVP>14cmH2O时输液50ml。

输液期间观察CVP的变化:若CVP升高5 cmH2O,应停止输液;当CVP升高2~5 cmH2O 时,可暂停输液10分钟,再观察CVP变化,这时CVP仍升高2 cmH2O以上则应停止输液;若CVP升高不超过2cmH2O,按上述标准输液,直到CVP升高超过5 cmH2O,或暂停10分钟后仍升高2 cmH2O以上为止。

@PCWP指导输液的“7-3”法则:危重病人或合并心脏病者应监测PCWP。

当PCWP<10mmHg,10分钟内输液200ml;PCWP 为11~18 mmHg时输液100ml;PCWP>18mmHg时输液50ml。

输液期间观察PCWP的变化:若PCWP升高7mmHg,应停止输液;当PCWP升高3~7mmHg 时,可暂停输液10分钟,再观察PCWP变化,这时PCWP仍升高3mmHg以上则应停止输液;若PCWP升高不超过3mmHg,按上述标准输液,直到PCWP升高超过7mmHg,或暂停10分钟后仍升高3mmHg以上为止。

正常血流动力学参数表

正常血流动力学参数表
Ca-vO2×CO×10
200~250ml/min
氧耗指数(VO2I)
Ca-vO2×CI×10
120~160ml/min/ m2
摄氧率(O2ER)
(Ca-vO2/ CaO2)×100
22~30(25)%
摄氧指数(O2EI)
(SaO2-SvO2)/SaO2×100
20~25%
Qs/Qt
(CcCO2-CaCO2)/(CcCO2-CvCO2)
×Hgb×SaO2+×PaO2
dl
静脉血氧含量(CvO2)
×Hgb×SvO2+×PvO2
dl
动静脉血氧含量差(Ca-vO2)
CaO2-CvO2
4~6ml/dl
氧输送(DaO2)
CaO2×CO×10
1000ml/min
氧输送指数(DaO2I)
CaO2×CI×10
500~600ml/min/m2
氧消耗(VO2)
正常血流动力学参数表
正常血流动力学参数——成人瓣膜 主动脉瓣口面积 ~ 二尖瓣口面积 ~
参数
公式
正常范围
血压(BP)
收缩压(SBP)
90~140mmHg
舒张压(DBP)
60~90mmHg
平均动脉压(MAP)
(SBP+2DBP)/3
70~105mmHg
中心静脉压(CVP)
2~6mmHg
右房压(RAP)
SV/EDV
40~60%
氧代谢动力学参数——成人
参数
公式
正常范围
动脉血氧分压(PaO2)
80~100mmHg
动脉血二氧化碳分压(PaCO2)
35~45mmHg
碳酸氢根(HCO3)

血流动力学整理版

血流动力学整理版

Allen,s试验
心 的: 心 法: 1.抬心 前臂, 术者心 双心 拇指分别 摸到桡尺动脉搏动; 2.嘱患者做3次握拳和松拳动作, 压迫阻断桡尺动脉心 流直心 心 部变心 ; 3.放平前臂, 只解除尺动脉压迫, 观察心 部转红的时间, 正常为<5~7s, 0~7s表示掌心 侧心 循环良好, 8~15s属可疑, >15s属循环不良, 禁忌穿刺;
影响波形传输的因素
• 管道堵塞 *心栓 * 管道中有心 或心 泡 * 管道扭曲 • 管道太心 • 太多连接处 • 连接不紧密 • 换能器损坏
动脉压血波形的组成
1. 收缩期峰压PSP: 收缩期峰压反映左心 室最 心 的收缩压, 在主动脉 开放后于波形上看到的尖 锐的上升心 , 代表心 流 从心 室射心 动脉系统
什么是血流动血学监测?
定义: 依据物理学的定律, 结合血理和病理血理学概念, 对循环系统中血液运动的规律性进血定量的、 动态的、 连 续地测量和分析. 血的: 了解病情发展、 指导临床治疗 如何监测?
循环系统
• 体循环与肺循环 • 体循环与肺循环
正常循环的基本条件
1. 正常的心 泵功能 2. 充心 的心 容量( 前负荷) 3. 适当的外周阻心 ( 后负
!正常值值::55-1-21c2mcmHH2O2O
中心静脉压监测
CVP各波形意义
正常波形
ECG
R
P CVP a c
x
T
v Y
• • A波: 由右心 房收缩产心 , EKG
P波之后 • • C波: 三尖瓣关闭所产心 , C波
下降即心 室开始射心
• • X波: 右心 房舒张时容量减少
• V波: 心 室收缩射心 时房室瓣关 • 闭,上下腔静脉回流心 右房的心 产

血流动力学参数

血流动力学参数

血流动力学参数关键词:血流动力学监测,参数,运用,意义摘要:血流动力学监测已经广泛应用于危重症,但其数据多,每个参数因为它来源的监测手段和影响因素等等的不同,其临床意义不同。

血流动力学监测的每个参数都有他的“背景”、有它的长处和短处。

哪个参数有什么意义,怎样结合其它参数或临床等等都是我们应该掌握和经常思考的,而且只有在临床中不断运用、思考才能真正理解这些参数。

本文介绍了直接测量所得指标:上肢动脉血压、心率、中心静脉压、右心房压、右心室压、肺动脉压、肺毛细血管嵌顿压、心输出量。

由直接测量指标所派生的指标:心脏排血指数、心脏搏出量、肺血管阻力、心室做功指数和PICCO参数:血管外肺水、胸内血容量。

介绍了临床应用于判断左心功能、疾病的鉴别、心功能状态的治疗原则、指导疾病的治疗等。

1、主要监测指标1.1直接测量所得指标1.1.1上肢动脉血压(AP) 正常值:收缩压12.0~18.7kPa(90~140mmHg),舒张压8.0~12.0kPa(60~90mmHg)。

心排量、全身血管阻力、大动脉壁弹性、循环容量及血液粘度等均可影响动脉血压。

一般用袖带血压计测量。

在休克或体循环直视心脏手术时,应以桡动脉穿刺直接测量为准[1]。

血压是反应心排量水平和保证器官有效灌注的基础,过高时增大左室后负荷和心肌耗氧,过低不能保证重要器官有效灌注。

当MAP低于75mmHg时,心肌供血曲线变陡下降,因此,MAP75~80mmHg,是保证心肌供血大致正常的最低限度[2]。

对原有高血压病人,合理的MAP应略高于此。

1.1.2心率(HR) 正常值:60~100次/min。

反映心泵对代谢改变、应激反应、容量改变、心功能改变的代偿能力。

心率适当加快有助于心输出量的增加,<50次/min或>160次/min,心输出量会明显下降[3]。

1.1.3中心静脉压(CVP) 正常值:0.49~1.18kPa(5~12cmH20)。

体循环血容量改变、右心室射血功能异常或静脉回流障碍均可使CVP发生变化,胸腔、腹腔内压变化亦可影响CVP测定结果。

SIRS sepsis严重sepsis和MODS的诊断标准

SIRS sepsis严重sepsis和MODS的诊断标准

・专家论坛・SI RS 、sepsis 、严重sepsis 和MODS 的诊断标准俞森洋作者单位:100853 北京,解放军总医院南楼呼吸科 近年对感染和炎症的研究深入,使得该领域的观念不断更新,出现了一些新的术语和定义。

1991年美国胸科医师学会和危重病医学会提出的“全身炎症反应综合征”“sep sis ”和“多器官功能障碍综合征”等名词的定义。

2001年国际脓毒症定义会议对这些名词的定义做了修正,提出了新的诊断标准。

2008年《国际脓毒症和脓毒症休克治疗指南》仍然应用这些标准。

一、全身性炎症反应综合征(system i c i n fl amma tory re 2spon se syndro m e,S I RS) SI RS 指任何致病因素作用于机体所引起的全身炎症反应,并且具备以下2项或2项以上体征:体温>38℃或<36℃;心率>90次/m in;呼吸频率>20次/m in 或动脉血二氧化碳分压(PaC O 2)<32mmHg (1mmHg =01133kPa );外周血白细胞计数>12×109/L 或<4×109/L,或未成熟粒细胞>0110。

SI RS 的诊断标准相当宽松,包括的范围很广,因而敏感性很高,但特异性较差。

符合SI RS 诊断标准者不一定都有全身炎症反应存在。

但国外通过对2527例SI RS 病人的前瞻性研究,发现SI RS 的严重程度(依据符合诊断指标的多少判定)与多器官功能障碍综合征(MODS )的发生率及死亡率相关。

表明SI RS 标准有助于病情估计及预后判定。

临床医师不应满足于SI RS 的诊断,更应注意从SI RS 可能发展为MODS 的过程。

二、脓毒症(sepsis)和严重sepsis 1.脓毒症(sep sis )Sep sis 国内译为脓毒症,50年代提出此概念时系指各种致病微生物或其毒素存在于血液或组织中。

血流动力学

血流动力学

动脉血压相对恒定的意义
动脉血压过低,心室供血不足 动脉血压过高 1)心脏后负荷增加 心负担加重 心衰 2)血管易受损伤 冠心病或脑溢血
四、静脉血压和静脉回心血量
venous pressure and venous return 静脉的功能:通路;血液的贮存库;协助 调节CO (一)静脉血压
1、中心静脉压(central venous pressure):右心房和 胸腔大静脉的血压(4~12cmH2O) 影响因素:心脏射血量;静脉回心血量(量和速度) 意义:1)促进血液回心 2)中心静脉压与泵血功能呈负相关
评估血容量、前负荷、右心功能
CVP BP — — — N 原因
血容量不足 血容量轻度不足
措施
快速补液 适当补液
+ + N
— N —
心功能不全 容量血管收缩
强心,扩血管 扩血管
心功能不全或血容量不足伴容 强心,扩血管,适当补液 量血管收缩
血流动力学监测
右房压力与心输出量关系
血流动力学监测
2.肺动脉压、肺动脉楔压 肺血管无病变 : PADP 二尖瓣功能正常:

动脉血压与动脉脉搏
(一)动脉血压概念及正常值 1.动脉血压 主动脉内流动的血液对单位面积血管壁 的侧压力。 动脉血压随心动周期而呈周期性变化
Mean Internal Pressures Throughout Circulation
1.收缩压
在心动周期中,心室收缩时动脉血压上升 所达到的最高值。 2.舒张压 在心动周期中,心室舒张时动脉血压下降 所达到的最低值。 3.平均动脉压 一个心动周期中动脉血压的平均值。
分配血管 前阻力血管
前括约肌 交换血管
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Sang-Wook Lee Biomedical Simulation Laboratory,University of Toronto,5King’s College Road Toronto,Toronto,ON M5S3G8Canada;School of Mechanical and AutomotiveEngineering,University of Ulsan,Ulsan680-749,South KoreaLuca AntigaDepartment of Bioengineering, Mario Negri Institute for PharmacologicalResearch,24020Ranica(BG),Italy David A.Steinman1Biomedical Simulation Laboratory,University of Toronto,5King’s College Road Toronto,Toronto,ON M5S3G8Canada e-mail:steinman@mie.utoronto.ca Correlations Among Indicators of Disturbed Flow at the Normal Carotid BifurcationA variety of hemodynamic wall parameters(HWP)has been proposed over the years to quantify hemodynamic disturbances as potential predictors or indicators of vascular wall dysfunction.The aim of this study was to determine whether some of these might,for practical purposes,be considered redundant.Image-based computationalfluid dynamics simulations were carried out for Nϭ50normal carotid bifurcations reconstructed from magnetic resonance imaging.Pairwise Spearman correlation analysis was performed for HWP quantifying wall shear stress magnitudes,spatial and temporal gradients,and harmonic contents.These were based on the spatial distributions of each HWP and,harmonic(DH)parameter were found to depend on how the wall shear stress magnitude was defined in the presence offlow reversals.Many of the proposed HWP were found to provide essentially the same information about disturbedflow at the normal carotid bifurcation.RRT is recommended as a robust single metric of low and oscillating shear. On the other hand,gradient-based HWP may be of limited utility in light of possible redundancies with other HWP,and practical challenges in their measurement.Further investigations are encouraged before thesefindings should be extrapolated to other vas-cular territories.͓DOI:10.1115/1.3127252͔Keywords:wall shear stress,atherosclerosis,hemodynamic wall parameter,carotid bifurcation1IntroductionThere is much evidence suggesting that initiation and progres-sion of atherosclerotic disease is influenced by“disturbedflow”͓1͔.Notwithstanding the imprecise nature of this term͓2͔,variousmetrics have been proposed over the years to quantifyflow dis-turbances.Originally focused on the magnitudes of wall shear stress͑WSS͓͒3,4͔these hemodynamic wall parameters͑HWP͒have since incorporated spatial and temporal gradients of WSS ͓5–8͔and,more recently,the harmonic content of time-varying WSS waveforms͓2,9͔.In a recent computationalfluid dynamics͑CFD͒study of the relationship between geometry and disturbedflow at the carotid bifurcations of young adults͓10͔,we noted that ourfindings were relatively insensitive to the choice of either time-averaged wall shear stress magnitude͑TAWSS͒or oscillatory shear index͑OSI͒as metrics of disturbedflow.This was found to be explained by a strong and significant inverse correlation between these two quan-tities.Such correlations among HWP are not unexpected,as rec-ognized early by Friedman and Deters͓11͔;however,they have been little-investigated in light of the growth in the number and complexity of candidate HWP.With this in mind,the objective of the present study was to use a representative sample of normal carotid bifurcation geometries to comprehensively test for correlations among established and recently-proposed HWP.Especially in the context of large-scalestudies of so-called geometric and hemodynamic risk factors inatherosclerosis,we aimed to determine whether a subset of HWP,or even a single HWP,might serve as a sufficiently robust markerof disturbedflow.2Materials and Methods2.1Computational Fluid Dynamics.N=50anatomically re-alistic carotid bifurcation geometries were digitally reconstructedfrom black blood magnetic resonance imaging͑MRI͒of25osten-sibly healthy young adults,as described previously͓12͔.CFDsimulations were carried out using a well-validated in-housefinite-element-based CFD solver͓13–15͔.Quadratic tetrahedral-element meshes were generated by a commercial mesh generator ͑ICEM-CFD;ANSYS,Berkeley,CA͒using a nominally uniform node spacing of0.2mm,previously shown to be sufficient forresolving wall shear stresses to within10%accuracy͓16͔.Rigidwalls and Newtonian rheology were assumed.Pulsatileflowboundary conditions were prescribed based on representativewaveform shapes and allometrically-scaled inlet and outletflowrates.Further details of the CFD simulations are provided else-where͓10͔.For each tetrahedral element the vector WSS,␶w,was calcu-lated as the projection of the stress tensor onto the element’s sur-face at each node,using the element’s quadratic shape functions. As nodes are connected to multiple elements,contributions to each nodal␶w were averaged together.From these time-varying nodal WSS vectors,a variety of HWP were computed,as summa-rized in Table1,and detailed below.1Corresponding author.Contributed by the Bioengineering Division of ASME for publication in the J OUR-NAL OF B IOMECHANICAL E NGINEERING.Manuscript received August12,2008;finalmanuscript received January1,2009;published online May11,2009.Review con-ducted by Fumihiko Kajiya.Paper presented at the2008Summer Bioengineering Conference͑SBC2008͒,Marco Island,FL,June25–29,2008.2.2Magnitude-Based HWP.Time-averaged wall shear stress was calculated by integrating each nodal WSS magnitude over the cardiac cycle.For each CFD model,the nodal TAWSS were normalized by the fully-developed ͑i.e.,Poiseuille ͒value,based on the model’s imposed cycle-averaged flow rate,the as-sumed viscosity,and the mean diameter ofthe model’s commoncarotid artery ͑CCA ͒at a location three radii upstream of the bifurcation ͑i.e.,CCA3,as defined in Ref.͓10͔͒.Oscillatory shear index,a dimensionless metric of changes in the WSS direction,originally introduced by Ku et al.͓6͔,was malized with respect to its fully-developed value at CCA3.2.3Gradient-Based HWP.Originally proposed by Lei et al.͓19͔,the wall shear stress spatial gradient ͑WSSG ͒may be con-sidered a marker of endothelial cell tension.As shown in Table 1,it is calculated from the WSS gradient tensor components parallel and perpendicular to the time-averaged WSS vector ͑m and n ,respectively ͒.Here the WSS gradients were calculated directly from the velocities of each element,taking advantage of their quadratic shape functions.As with WSS itself,elemental contri-butions to nodal WSSG values were averaged together.Since the WSSG of fully-developed flow in a straight uniform pipe is zero,here it is normalized by the fully-developed TAWSS divided by the mean diameter at CCA3.Subsequently,Longest and Kleinstreuer ͓20͔proposed the WSS angle gradient ͑WSSAG ͒to highlight regions exposed to large changes in WSS direction,irrespective of magnitude.As indicated by the formula in Table 1,this was done by calculating,for each element’s node ͑index j ͒,its direction relative to some reference WSS vector ͑index i ͒,here chosen to be that at the element’s centroid.The WSS temporal gradient ͑WSST ͒,originally suggested by Ojha ͓7͔as a factor in distal anastomotic intimal hyperplasia,is simply the maximum absolute rate of change in WSS magnitude over the cardiac cycle.Here it is normalized to WSST at location CCA3,determined from Womersley’s solution of fully-developed pulsatile flow based on the CCA3diameter,the heart rate,and the imposed flow rate Fourier coefficients.2.4Harmonic-Based HWP.Recently,Himburg and Fried-man ͓2͔suggested the harmonic content of the WSS waveform as a possible metric of disturbed flow,subsequently linking this to the frequency-dependent responses of endothelial cells ͓21͔.Fol-lowing those authors,the time-varying WSS magnitude at each node was Fourier-decomposed,with the dominant harmonic ͑DH ͒simply defined as the harmonic with the highest amplitude.Around the same time,Gelfand et al.͓9͔defined the harmonic index ͑HI ͒as the relative fraction of the harmonic amplitude spec-trum arising from the pulsatile flow components.Table 1Definitions of hemodynamic wall parameters …HWP …2.5Data Analysis.Correlations among the various HWP were evaluated in two ways:locally,whereby spatial distributionsof HWP were compared;and globally,whereby overall“burdens”of disturbedflow were compared.Local correlations were tested byfirst discretizing each model’ssurface into afinite number of contiguous patches,within each ofwhich the respective HWP was averaged͑for the ordinal DH,themedian was used͒.This amounted to mapping each distribution ofHWP onto an objective template plane,fixed with respect to abifurcation-specific coordinate system͓22͔.Remembering thatmodel dimensions have previously been normalized with respectto their respective CCA3radius,patches were nominally0.5unitsin length along the direction of the vessel axis,with12patchesdistributed circumferentially at each axial level.To facilitate pool-ing of patches from all cases,and in light of differences in eachCFD model’s relative length,only those patch locations presentfor all CFD models were included,resulting in288patches permodel.Although absolute patch sizes may have varied betweenand within models,this mapping procedure ensured that all sur-faces were spatially discretized in a consistent way͓22͔.Global comparisons were made by calculating,for each CFDmodel,the fraction of its surface area exposed to“abnormal”val-ues of a particular HWP.As detailed in Ref.͓10͔,“abnormal”wasdefined,for each HWP,as the upper quintile͑for TAWSS,thelower quintile͒of the HWP data pooled from all CFD models,thus providing an objective threshold between normal and abnor-mal.To ensure a consistent spatial extent across all cases,thesurfaces were clipped at planes three andfive maximally inscribedsphere radii along the common and internal carotid arteries ͑CCA3and ICA5,respectively͓10͔͒.Then,for each case,the area of the surface experiencing HWP above͑for TAWSS,below͒thethreshold was calculated.To factor out the influence of vesselsize—for the same shape,a larger vessel will experience a largerarea of disturbedflow—this absolute surface area was divided bythe total͑clipped͒surface area.In this way,for each HWP,eachCFD model was assigned a single value characterizing how muchof its surface was exposed to disturbedflow.For both local and global comparisons,a Spearman rank corre-lation coefficient͑r͒and significance͑p-value͒were computed for each of the28unique pairs of HWP using PRISM version4͑GraphPad Software,San Diego,CA͒.Correlations having p Ͻ0.05were deemed strong for͉r͉Ͼ0.8,weak for͉r͉Ͻ0.5,and moderate in between.Spearman correlation analysis was chosen in part because HWP distributions are unlikely to be normal.Also, in assessing these correlations based on rank,we sought to iden-tify,in the local correlations,whether the sites of extrema for one HWP would be reflected in the sites of extrema for another HWP. Global correlations sought to identify whether the ranking of cases from low to high burden of“disturbedflow,”based on the threshold of a given HWP,would be the same as that obtained based on another HWP.3ResultsAs depicted in Fig.1for a representative case,disturbedflow based on WSS magnitude quantities͑TAWSS,OSI,and RRT͒was concentrated around the outer walls of the bifurcation,consistent with many previous observations.For gradient-based HWP ͑WSSG,WSSAG,and WSST͒elevated values were concentrated around the bifurcation apex and,to a lesser but more variable extent,around the external and internal carotid artery͑ECA and ICA͒branches.Distributions of harmonic HWP͑DH and HI͒were more distinctive:higher DH was concentrated away from the outer walls of the bifurcation,whereas elevated HI reflected the general locations,if not the specific spatial extents,of the magnitude-based HWP.Overall,these observations hint at the correlations among the patched HWP distributions,detailed in Table2and depicted graphically for selected HWP pairs in Fig.2.Strong correlations were seen between TAWSS and both RRT͑r=−0.99͒and WSSG ͑r=0.86͒,albeit for different reasons:regions of elevated RRT correlated well with those experiencing low TAWSS͑r=−0.99͒, whereas elevated WSSG correlated with elevated TAWSS͑r =0.86͒.Moderate inverse correlations were found between TAWSS and both OSI and HI͑r=−0.66and r=−0.72,respec-tively͒,whereas TAWSS was positively correlated with WSST ͑r=0.63͒.Although many of the correlations were weak,all were statistically significant.Of all HWP,only DH was neither stronglynor moderately correlated with any other HWP.It is also worthnoting that the correlations identified by pooling the cases werefairly consistent across the50cases analyzed individually,as evi-denced by the relatively narrow confidence intervals shown in thesame table.According to the global correlations summarized in Table3,TAWSS,OSI,or RRT would rank vessels in similar order fromlow to high burdens of disturbedflow,as indicated by the strongpositive global correlation coefficients.Conversely,if disturbedflow was defined as elevated WSSG,vessels would be ranked inreverse order to this,as indicated by the moderate negative corre-lations with TAWSS,OSI,and RRT.As with the local correla-tions,HI was moderately correlated with the trio of magnitude-based HWP,while DH was only weakly correlated with otherHWP.Overall,corresponding local and global correlations wereof similar strength.A notable exception was OSI versus WSSAG, for which the local correlation was moderate͑r=0.73͒,while the global correlation was weak͑r=0.05͒and not significant.Reasons for this are given in Sec.4.It is worth noting that the above results were found to be rela-tively insensitive to the choice of data analysis method.For ex-ample,the Spearman correlation analysis of the continuous distri-butions of HWP͑i.e.,the CFD nodal values prior to patching͒revealed correlations similar to those obtained after patching.Glo-bal correlations based on a90th percentile threshold for disturbedflow were similar to those reported here using the80th percentilethreshold,afinding consistent with Ref.͓10͔.Finally,in light ofthe concentrations of HWP extrema around the bifurcation region,we repeated the local correlation analysis using patches extendingaxially only halfway along each branch͑i.e.144patches permodel͒to exclude the distal parts of the branches.Again thetrends were the same,although some of the moderate correlationsactually increased in strength,such as TAWSS versus OSI͑from r=−0.66to r=−0.77͒and TAWSS versus WSST͑from r=0.62to r=0.75͒.The detailed results are omitted in the interest of space, and because they do not affect the implications and conclusions discussed below.4Discussion4.1Summary and Implications of Findings.This compre-hensive evaluation of correlations among HWP at the normal ca-rotid bifurcation clearly demonstrates that some of these param-eters may,for practical purposes,be considered redundant.By virtue of their definitions in Table1,correlations among WSS, OSI,and RRT were expected,although not necessarily at the strengths observed.While WSS and OSI were moderately corre-lated,Fig.1suggests the OSI captures apparentflow disturbances at the ECA branch.Notwithstanding whether these are significant in the context of atherosclerosis—plaques do tend to occur at the ICA—our results would suggest that RRT can replace WSS and OSI as a single marker of“low and oscillatory”shear.In fact,as noted earlier,RRT is,by definition,the inverse of the magnitude of the time-averaged WSS vector.This explains its near-perfect correlation with TAWSS,which,remember,is the time-average of the WSS magnitude.In other words,RRT is simply another type of time-averaged WSS,but inverted and with a more tangible connection to the biological mechanisms underlying atherosclero-sis͓18͔.To appreciate the practical implications of replacing TAWSS and OSI with RRT,consider our recent study in which exposure todisturbed flow was found to be significantly predicted by a com-bination of bifurcation area ratio and tortuosity ͓10͔.There,the findings were shown to be independent of the choice of TAWSS or OSI as the metric of disturbed flow.Here,repeating the multiple regressions using RRT above the 80th percentile as the criterion for disturbed flow,we found near-identical—if anything,slightly stronger—coefficients:R adj 2=0.341͑p =0.0001͒,␤tortuosity =−0.498͑p =0.0001͒,and ␤AR1=0.459͑p =0.0007͒.In other words,exposure of the vessels to “disturbed flow”is the same,whether defined by extrema of TAWSS,OSI,or RRT.The strong positive local correlations ͑and consequent strong negative global correlations ͒between TAWSS and its spatial and temporal gradients likely reflect the fact that all of these quantities are highest around the apex of the bifurcation.As pointed out by Ojha ͓7͔,the use of WSS spatial gradients as risk indicators for intimal thickening is questionable in light of their concentration about the bifurcation apex,a region usually spared of plaques.As suggested recently by Goubergrits et al.͓23͔,regions elsewhere experiencing elevated WSSG may represent a consequence of ath-erosclerosis rather than a cause.Either way,for the normal carotid bifurcation at least,our findings would suggest that TAWSS could be used instead of WSSG,which is anyway more susceptible to measurement uncertainty ͓24,25͔,owing to its reliance on spatial gradients.A similar conclusion may be drawn from the moderate correla-tions between TAWSS and WSST,although it is worth remember-ing that in this study all CFD models were exposed to the same waveform shape .Intersubject variations in waveform shape are reported to be on the order of 10%͓26,27͔.Such variations in flow rate dynamics have been found to have a relatively minor influence on variations in the distributions of a variety of HWP,at least relative to the influence of uncertainty in the reconstructed geometry ͓25͔.Thus,it is reasonable to conclude that our findings are robust to our assumptions about waveform shape.It was also observed that the spatial distributions of OSI and WSSAG were moderately correlated ͑r =0.73͒,consistent with previous qualitative observations for carotid bifurcations ͓25͔and coronary arteries ͓23͔.As pointed out by Goubergrits et al.͓23͔,WSSAG may be thought of as an extension of OSI;however,being based on differential versus integrated quantities,WSSAG distributions tend to be noisier and more sensitive to uncertainty,something evident here and also in Ref.͓25͔.Nevertheless,for the representative case presented in Fig.1,this correlation is less obvious.Elevated values of WSSAG do coincide with the periph-ery of those regions exposed to elevated OSI;however,the core region of elevated OSI at the carotid bulb is characterized by low WSSAG and,as with the other gradient-based HWP,elevated WSSAG is concentrated at the bifurcation apex,a regiontypicallyFig.1HWP distributions for a representative case.Except for the ordinal DH,contour levels de-picted in each frame’s legend correspond to the 80th,85th,90th,and 95th percentile values based on the HWP distribution pooled over all cases.Note identification of CCA3and ICA5clip planes in the upper left …TAWSS …panel.spared of atherosclerosis.Moreover,the global correlation of these quantities was much weaker ͑r =0.05͒.This may be ex-plained in reference to the respective scatter plot in Fig.2,which clearly shows that the local ͑i.e.,patchwise ͒Spearman rank cor-relation was biased by the preponderance of patches having low OSI and WSSAG values.Focusing only on those patches having OSI Ͼ0.1,it can be seen that there is no obvious correlation with WSSAG.Because the global correlations focused only on those regions exposed to the upper quintile of HWP values,they better reflect the correlation,or lack thereof,of these extrema.Having said this,it is worth noting that,for most of the other pairwise comparisons,global and local correlation coefficients were in much closer agreement.Of all HWP,only DH was found to be essentially independent of the other HWP.This was somewhat surprising,since Himburg and Friedman ͓2͔,in introducing the use of WSS harmonics as metrics of disturbed flow,reported an inverse correlation between DH and TAWSS ͑Pearson r =−0.62͒.By way of explaining this,we note that their study was carried out on porcine iliac arteries,which are nominally straight vessels experiencing largely axial flows.On the other hand,flow at the carotid bifurcation is decid-edly nonaxial,and likely subject to more reverse flow.In such regions,rectification of the time-varying WSS vector—remember that DH was derived here from the WSS vector magnitude,per its original definition ͓28͔—could alter its harmonic content.To appreciate the impact of this,we recomputed DH and HI using instead the time-varying “axial”WSS,namely,the compo-nent of the instantaneous WSS vector projected onto a unit vector defined by the direction of its time-averaged value.In this way,flow reversals relative to the nominal axial direction are pre-Table 2Spearman rank correlation coefficients for pairwise local comparisons of the pooled HWP distributions …N =14,400patches total ….Shown in brackets are 95%confidence intervals,drawn from pairwise comparisons of the 50datasets individually …N =288patches each ….All correlations significant to p <0.001,except WSSAG versus DH,p =0.03.OSIRRT WSSG WSSAG WSST DH HI TAWSS Ϫ0.66͓Ϫ0.76,Ϫ0.53͔Ϫ0.99͓Ϫ0.99,Ϫ0.98͔0.86͓0.80,0.91͔Ϫ0.29͓Ϫ0.41,Ϫ0.16͔0.63͓0.46,0.79͔Ϫ0.33͓Ϫ0.45,Ϫ0.21͔Ϫ0.72͓Ϫ0.81,Ϫ0.60͔OSI 0.72͓0.59,0.82͔Ϫ0.38͓Ϫ0.62,Ϫ0.16͔0.73͓0.68,0.78͔Ϫ0.27͓Ϫ0.47,Ϫ0.04͔0.06͓Ϫ0.08,0.16͔0.53͓0.39,0.66͔RRT Ϫ0.81͓Ϫ0.88,Ϫ0.72͔0.38͓0.25,0.52͔Ϫ0.57͓Ϫ0.74,Ϫ0.41͔0.30͓0.19,0.43͔0.74͓0.65,0.82͔WSSG 0.09͓Ϫ0.11,0.26͔0.67͓0.52,0.82͔Ϫ0.31͓Ϫ0.47,Ϫ0.14͔Ϫ0.51͓Ϫ0.67,Ϫ0.26͔WSSAG 0.07͓Ϫ0.13,0.24͔Ϫ0.02͓Ϫ0.15,0.10͔0.45͓Ϫ0.32,Ϫ0.55͔WSST Ϫ0.14͓Ϫ0.26,Ϫ0.04͔Ϫ0.08͓Ϫ0.38,0.15͔DH0.27͓0.14,0.41͔Fig.2Scatter plots for selected pairwise comparisons of HWP .Note that the local …patched …data are plotted using a log-log scale to better depict the full dynamic range of data.served.As can be seen by comparing Fig.3to Fig.1,this had a marked effect on the spatial distributions of DH and HI.The rea-son for this is also given in Fig.3:rectification of the instanta-neous WSS served to break up the clear fifth harmonic oscillation of the time-varying axial WSS in favor of the lower frequencies.As summarized in Table 4,this served to strengthen the correla-tions between the harmonic and other HWP.Of note is the local correlation coefficient for TAWSS versus DH ͑r =−0.69͒,now close to that originally reported by Himburg and Friedman.Whether DH and HI should be defined based on magnitude or axial WSS cannot be answered by the present study.It is also not clear whether DH should be considered a monotonic HWP in light of possible limits to the temporal response of endothelial cells to shear ͓21͔.Nevertheless,our findings do bring to attention a heretofore-underappreciated issue in the harmonic analysis of WSS in the presence of strongly nonaxial flow.4.2Potential Limitations.This study has made the custom-ary assumptions of rigid walls,Newtonian rheology,and fully-developed inlet boundary conditions,previously shown to be of relatively minor influence on the distribution of WSS ͓16,29,30͔.The use of allometrically-scaled flow rates was recently shown to have little impact on the relative burdens of disturbed flow among the 50cases considered here ͓10͔;however,as noted earlier,theassumption of a constant waveform shape might have served to underestimate variations in WSST,as well as the harmonic HWP.An obvious limitation of this study is the relatively narrow scope of vascular configurations considered,namely,normal ca-rotid bifurcations.We do note,however,that recent work from Goubergrits et al.͓23͔similarly reported possible redundancies among gradient and magnitude-based HWP for the case of a nor-mal coronary artery.Huo et al.͓31͔also noted a significant power-law relationship between TAWSS and OSI on the outer walls of the common carotid and celiac arteries,based on a CFD model of flow along the length of the mouse aorta.While a power-law relationship is expected based on the definition of OSI,those au-thors did note a difference in the power-law coefficients derived from the carotid and celiac sites,an observation consistent with the branch-specific clustering of data points in the OSI versus TAWSS scatter plot in Fig.2.Those authors also noted a corre-spondence between elevated TAWSS and elevated WSSG,al-though no quantitative relationship was found.Nevertheless,we encourage further investigation before our findings should be ex-trapolated to other vascular territories.It is also important to appreciate that our study has made no attempt to prioritize any of these HWP in terms of their purportedTable 3Spearman rank correlation coefficients for each pair-wise global comparison of the relative surface area exposed to the HWP beyond its 80th percentile value …N =50cases ….OSIRRT WSSG WSSAG WSST DH HI TAWSS 0.80a0.97aϪ0.63a Ϫ0.16Ϫ0.250.040.68a OSI 0.88aϪ0.50a 0.05Ϫ0.260.040.66a RRT Ϫ0.63aϪ0.10Ϫ0.250.020.74a WSSG 0.58a0.54a Ϫ0.33b Ϫ0.27WSSAG 0.43cϪ0.240.20WSST Ϫ0.20Ϫ0.04DH0.01ap Ͻ0.05.bp Ͻ0.01.cp Ͻ0.001.Fig.3Distributions of DH and HI based on the axial WSS component rather than WSS magnitude,shown for same case depicted in Fig.1.The arrows indicate the site of the time-varying WSS waveforms and corresponding spectra shown to the right.Table 4Spearman rank correlation coefficients for local and global comparisons of DH and HI,as derived from the time-varying axial WSS rather than the WSS magnitude.Local GlobalDHHI DH HI TAWSS Ϫ0.69a Ϫ0.77a 0.76a 0.83a OSI 0.55a 0.65a 0.78a 0.89a RRT 0.70a 0.81a 0.78a 0.89a WSSG Ϫ0.58a Ϫ0.54a Ϫ0.54b Ϫ0.46a WSSAG 0.31a 0.51a Ϫ0.180.12WSST Ϫ0.36aϪ0.14a Ϫ0.34cϪ0.15DH0.63a0.64aap Ͻ0.05.bp Ͻ0.01.cp Ͻ0.001.links to the underlying biological mechanisms.Thus,some of the HWP we regard here as redundant might be shown to have closer mechanistic links in studies of individual biological responses to the local hemodynamic environment.Rather,we suggest that our findings are most applicable to large-scale studies of hemody-namic factors in atherosclerosis,which are more concerned with quantifying overall burdens or identifying patterns of localization of disturbedflow,whatever this vague term may prove to mean precisely.5ConclusionsFor the normal carotid bifurcation at least,many of the pur-ported indicators of disturbedflow are significantly correlated. Based on thesefindings we recommend the use of relative resi-dence time͑RRT͒as a robust single metric of low and oscillatory shear.In light of possible redundancies,any perceived benefits of gradient-based HWP are likely outweighed by practical challenges with their measurement.Dominant harmonic͑DH͒is a promising new HWP,but issues related to its definition in nonaxialflow need to be resolved.AcknowledgmentThe authors thank Dr.Mort Friedman for helpful discussions. The authors also thank the anonymous reviewers for their valu-able suggestions.DAS acknowledges the support of Grant No. MOP-62934from the Canadian Institutes of Health Research. 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