Anesthesiology Research and PracticeVolume 2012 (2012), Article ID 617380, 10 pagesdoi:10.1155/2012/617380

Review Article

Evaluation of Fluid Responsiveness: Is Photoplethysmography a Noninvasive Alternative?

Lars Prag Antonsen¹ and Knut Arvid Kirkebøen1,2

¹Faculty of Medicine, University of Oslo, 0316 Oslo, Norway²Department of Anesthesiology, Oslo University Hospital, Ullevaal, 0424 Oslo, Norway

Received 29 September 2011; Revised 29 November 2011; Accepted 21 December 2011

Academic Editor: Ronald G. Pearl

Copyright © 2012 Lars Prag Antonsen and Knut Arvid Kirkebøen. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Background. Goal-directed fluid therapy reduces morbidity and mortality in various clinical settings. Respiratory variations in photoplethysmography are proposed as a noninvasive alternative to predict fluid responsiveness during mechanical ventilation. This paper aims to critically evaluate current data on the ability of photoplethysmography to predict fluid responsiveness. Method. Primary searches were performed in PubMed, Medline, and Embase on November 10, 2011. Results. 14 papers evaluating photoplethysmography and fluid responsiveness were found. Nine studies calculated areas under the receiver operating characteristic curves for POP (>0.85 in four, 0.75–0.85 in one, and <0.75 in four studies) and seven for PVI (values ranging from 0.54 to 0.98). Correlations between POP/PVI and PP/other dynamic variables vary substantially. Conclusion. Although photoplethysmography is a promising technique, predictive values and correlations with other hemodynamic variables indicating fluid responsiveness vary substantially. Presently, it is not documented that photoplethysmography is adequately valid and reliable to be included in clinical practice for evaluation of fluid responsiveness.

1. Introduction

Whether or not to administer intravenous (iv) fluid is a common, difficult, and controversial challenge in clinical practice. The main aim of fluid therapy during surgery or critical illness is to provide adequate tissue perfusion by increasing stroke volume (SV) or cardiac output (CO). Goal-directed fluid therapy aiming to increase oxygen (O₂) delivery reduces morbidity and mortality in various clinical settings [1–8]. Fluid therapy is guided by clinical variables, as well as static and dynamic variables. Clinical variables include blood pressure, heart rate, capillary refill time, skin turgor and diuresis, mixed venous oxygen saturation (SvO₂), lactate, pH, electrolytes, and creatinine/urea. Conventional static variables include central venous pressure (CVP) and pulmonary artery wedge pressure (PAWP), but these variables have proven less reliable than initially assumed to evaluate fluid responsiveness [8–10]. Dynamic variables include both SV-dependent and non-SV-dependent methods. The ideal new method should be accurate [11], easy to use, noninvasive, and widely available with minimal risk of complications. Potential clinical value also depends on reproducibility and predictive values compared to established methods.

Photoplethysmography (more specifically pulse oximetry plethysmographic waveform analysis) as a noninvasive tool in evaluation of fluid responsiveness was first described by Partridge [12] and has been extensively investigated. A pulse oximeter is a standard equipment for measuring arterial O₂ saturation, and further analysis of the photoplethysmographic signal can easily be implemented in clinical monitoring. This paper aims to critically evaluate current data on the ability of photoplethysmography to predict fluid responsiveness.

2. Methods

This paper is based on searches performed in PubMed, Medline, and Embase on November 10, 2011 with the following search criteria: “(pulse oximetry OR plethysmographic OR Pleth variability index OR PVI) AND ((fluid responsiveness) OR (volume status)).” The searches generated 217 hits. Papers were checked for relevant references and 22 [13–34] papers met the following inclusion criteria:(1)reporting predictive values of ΔPOP and/or PVI after fluid challenges and/or reporting correlations between ΔPOP, PVI, and ΔPP,(2)mechanically ventilated patients,(3)written in English.

3. Results

3.1. Predictive Values of ΔPOP and PVI

14 studies performed fluid challenges and these are summarized in Table 1. Patients were mechanically ventilated with tidal volumes of 6–10 mL/kg and investigated preoperatively () [23, 26, 28, 30–32], perioperatively () [21, 33, 34], postoperatively () [25, 27], and in the intensive care unit (ICU) () [22, 24]. One study included different groups of patients [29]. The pulse oximeter was placed on a finger in all papers, and in two papers it was also placed on the earlobe [30, 34]. Different types of pulse oximeters were used, summarized in Table 2. The number of patients included in each study varied substantially ( 8–43). Registration periods were, with some exceptions [22, 33], short (<1 min). Six studies did not indicate duration of the registration period [24, 28–31, 34]. Patients with arrhythmias were excluded in all papers except one, in which this was not expliticitly stated [34]. Patients receiving vasoactive medication were included in four papers [24, 27, 29, 33] and excluded in four [23, 26, 31, 32]. Six papers did not indicate use of vasoactive medication [21, 22, 25, 28, 30, 34]. These data are summarized in Table 3. Fluid challenges were given as HES 6% () [22–26, 28–31], “colloid fluid” () [21, 33, 34], and NaCl 0.9% () [27, 32]. Fluid volumes ranged from 250 mL to 1000 mL. Fluid responsiveness was defined as increased CO > 15% () [25, 29], increased CI > 15% () [22–24, 26, 30], ΔPP > 13% () [27], increased SVI > 10% () [21], increased SVI > 15% () [28, 31], increased SV > 10% () [34], increased SV > 15% () [33], and aortic velocity-time integral (AVTI) > 15% () [32]. Best cut-off values ranged from 8.8 to 15% for ΔPP, 9.5 to 15%for ΔPOP, and 9.5 to 17% for PVI. CO was measured with thermodilution () [21–23, 26, 30], echo Doppler () [24, 29, 31–34], FloTrac/Vigileo () [28], and intermittent thermodilution by pulmonary artery catheter (Vigilance monitor) () [25].

Table 1: Papers in which ΔPOP and/or PVI have been evaluated and fluid challenges performed.

Author, Ref.
Fluid challenge
CO/CI/SVI measurement
Responder
ROC
Threshold value
Sens/spec

Solus-Biguenet et al. [21]
250 mL colloid
Thermodilution
SVI: 10%
0.81
PPVfina: 14%
No data

0.68
ΔPOP: 9.5%
No data

0.79
PPVart: 12.5%
No data

Natalini et al. [22]
500 mL HES 6%
Thermodilution
CI: 15%
0.72
ΔPOP: 15%
56/86 (PPV/NPV)

0.74
ΔPP: 15%
55/100 (PPV/NPV)

Cannesson et al. [23]
500 mL HES 6%
Thermodilution
CI: 15%
0.847
ΔPOP: 13%
93/90

0.847
ΔPP: 11%
80/90

Feissel et al. [24]
8 mL/kg HES 6%
Echo-Doppler
CI: 15%
0.94
ΔPP: 12%
100/70

0.94
ΔPOP: 14%
94/80

Wyffels et al. [25]
500 mL HES 6%
Intermittent thermodilution
CO: 15%
0.94
PPV: 11.3%
95/91.7

by pulm. artery catheter

0.89
ΔPOP: 11.3%
90/83.3

Cannesson et al. [26]
500 mL HES 6%
Thermodilution
CI: 15%
0.94
ΔPP: 12.5%
87/89

0.94
ΔPOP: 12%
87/89

0.93
PVI: 14%
81/100

Westphal et al. [27]
500–1000 mL NaCl
Not measured
ΔPP > 13%
0.95
ΔPOP: 11%
91/100

Zimmermann et al. [28]
7 mL/kg HES 6%
FloTrac
SVI: 15%
0.97
PVI: 9.5 %
93/100

Loupec et al. [29]
500 mL HES
Echocardiography
CO: 15%
0.88
PVI: 17%
95/91

or PLR if ΔPP < 13%

Desgranges et al. [30]
500 mL HES
Thermodilution
CI: 15%
0.91
PVIforehead : 15%
89/78

0.88
PVIear: 16%
74/74

0.84
PVIfinger : 12%
74/67

0.84
PPV > 11%
74/89

PVIforehead : 15%
89/100

and PIforehead : 1.37

Renner et al. [31]
HES 10 mL kg⁻¹
Transoesophageal echocardiography
SVI: 15%
0.79
PVI > 13%
84/64

De Souza Neto et al. [32]
Saline, 20 mL/kg
Transthoracic echography
AVTI: 15%
0.51
0–6 yr: ΔPOP
No data

(aortic velocity-time integral)

0.63
0–6 yr: PVI
No data

0.71
0–6 yr: ΔPP
No data

0.52
0–6 yr: PPV
No data

0.57
6–14 yr: ΔPOP
No data

0.54
6–14 yr: PVI
No data

0.60
6–14 yr: ΔPP
No data

0.60
6–14 yr: PPV
No data

Hoiseth et al. [33]
250 mL colloid
Esophageal doppler
SV ≥ 15%
0.67
ΔPP: 8.8%
82/67

0.72
ΔPOP: 11.4%
86/67

Hood and wilson [34]
500 mL colloid
Esophageal doppler
SV ≥ 10%
0.96
PVIfinger (baseline) 10%
86/100

0.98
PVIearlobe (baseline) 9.5%
95/100

0.71
PVIfinger (during surgery) 10%
65/67

0.54
PVIearlobe (during surgery)

ΔPOP: pulse oximetry plethysmography; ΔPP: pulse pressure; PVI: Pleth variability index; CI: cardiac index; SV: stroke volume; SVI: stroke volume index; SVV: stroke volume variation; CO: cardiac output; PPVfina: pulse pressure variation obtained with Finapres; PPVart: pulse pressure variation obtained with intraarterial equipment; PPV/NPV: positive predictive value/negative predictive value.

Table 2: Papers in which correlations between ΔPOP, PVI, and ΔPP have been investigated.

Author, Ref.
Relation
Correlation
Pulse oximeter/monitor

Cannesson et al. [13]
ΔPOP-ΔPP
,
M1190A, Philips, Suresnes, France

Natalini et al. [14]
ΔPOP-ΔPP
,
Datex-Engstrom CS/3 Critical Care Monitor, Instrumentarium, Helsinki, Finland

Cannesson et al. [15]
ΔPOP-ΔPP
,
Oxymax Tyco Healthcare Group LP, Pleasanton, CA, USA

Intellivue MP70, Philips Medical Systems, Suresnes, France

Landsverk et al. [16]
ΔPOP-ΔPP
,
OxiMax 451N5, Nellcor, Boulder, CO, USA

Cannesson et al. [17]
ΔPOP-PVI
,
LNOP Adt, Masimo Corp., Irvine, CA, USA

PVI-ΔPP
,
Oxymax, Tyco Healthcare Group LP, Pleasanton, CA, USA

ΔPOP-ΔPP
,
Intellivue MP70, Philips Medical Systems, Suresnes, France

Pizov et al. [18]
ΔPOP-ΔPP

Datex-Ohmeda AS-3, Datex, Helsinki, Finland

Desebbe et al. [19]
PVI VT = 6-PVI VT = 10
9%–12%,
LNOP Adt, Masimo Corp., Irvine, CA, USA

PVIPEEP- PVInon - PEEP
(Significant change)

Biais et al. [20]
PVI-ΔPP
,
LNOP Adt, Masimo Corp., Irvine, CA, USA

PVINE(+)-ΔPP
,
Masimo Radical 7 monitor, Masimo SET, Masimo Corp., Irvine, CA, USA

PVINE(−)-ΔPP
,

Solus-Biguenet et al. [21]

No data

Natalini et al. [22]

Datex-Engstrom CS/3 Critical Care Monitor, Instrumentarium, Helsinki, Finland

Cannesson et al. [23]
ΔPOP-ΔPP
, ,
Oxymax Tyco Healthcare Group LP, Pleasanton, CA, USA

Intellivue MP70, Philips Medical Systems, Suresnes, France

Feissel et al. [24]
ΔPOP-ΔPP
,
SpO2/Pleth, M3150A technology, Philips Medical Systems, Andover, MA, USA

Wyffels et al. [25]

Monitor Hewlett Packard M1166A model G65

Cannesson et al. [26]
ΔPOP-PVI
,
LNOP Adt, Masimo Corp., Irvine, CA, USA, with Masimo Radical 7, 7.0.3.3

Oxymax, Tyco Healthcare Group LP, Pleasanton, CA, USA

Westphal et al. [27]
ΔPOP-ΔPP
,
S/5, Datex-Ohmeda, Helsinki, Finland

Zimmermann et al. [28]

LNCS, Masimo Corp., Irvine, CA, USA, Masimo Radical-7 monitor, 7.0.3.3

Loupec et al. [29]
PVIbaseline -ΔPPbaseline
,
LNCS Adtx, Masimo corp., Irvine, CA, USA

Desgranges et al. [30]

LNOP Adt, Masimo Corp., Irvine, CA, USA

LNOP TC-I, Masimo Corp., Irvine, CA, USA

LNOP TF-I, Masimo Corp., Irvine, CA, USA

Masimo Radical 7, Masimo SET, Masimo Corp., version 7.1.1.5

Renner et al. [31]

Masimo Rainbow SET, Masimo Corp., Radical 7, V7.6.2.2

De Souza et al. [32]
ΔPOP-PVI
,
Oxymax™, Tyco Healthcare Group LP, Pleasanton, CA, USA

ΔPOP-ΔPP
,
LNOP, Masimo Corp., Irvine, CA, USA

PVI-PPV
,

Hoiseth et al. [33]
ΔPOP-ΔPP
,
OxiMax 451N5, Nellcor, Boulder, CO, USA

Hood and wilson [34]

Masimo Rainbow SET, Masimo Corp., Irvine, CA, USA

ΔPOP: pulse oximetry plethysmography; ΔPP: pulse pressure; PVI: Pleth variability index; PEEP: positive end expiratory pressure; NE: norepinephrine; VT: tidal volume.

Table 3: General characteristics.

Author, Ref.
Year
n
Patient category
Ventilation
Site of meas.
Reg. period
Vasoact.

Cannesson et al. [13]
2005
22
ICU
Mech. vent. 6–10 mL/kg, volume
Finger
3 respiratory cycl.
Incl.

Natalini et al. [14]
2006
49
OR/ICU
Mech. vent. 6–9 mL/kg, volume
Finger/toe
5 respiratory cycl.
No data

Cannesson et al. [15]
2007
25
Preop. CABG/AAA
Mech. vent. 8–10 mL/kg, volume
Finger
3 respiratory cycl.
Excl.

Gen.anaesthesia

Landsverk et al. [16]
2008
14
ICU
Mech. vent. 8 mL/kg, volume/pressure
Finger
15 min
Incl.

Cannesson et al. [17]
2008
25
Preop.CABG
Mech. vent. 8–10 mL/kg
Finger
3 respiratory cycl.
Excl.

Gen.anaesthesia

Pizov et al. [18]
2010
33
Preop. surgery
Mech. vent. 8–10 mL/kg
Finger
3 min
Incl.

Desebbe et al. [19]
2010
21
Postop. CABG and ICU
Mech. vent. 6–10 mL/kg, volume
Finger
3 respiratory cycl.
Excl.

Biais et al. [20]
2011
67
ICU
Mech. vent. 8 mL/kg, volume
Finger
3 respiratory cycl.
Incl.

Solus-Biguenet et al. [21]
2006
8
During hepatic surgery
Mech. vent. 8–10 mL/kg
Finger
3 respiratory cycl.
No data

Natalini et al. [22]
2006
22
ICU
Mech. vent. 6–10 mL/kg, volume
Finger
2 min
No data

Cannesson et al. [23]
2007
25
Preop. CABG
Mech. vent. 8–10 mL/kg, volume
Finger
3 respiratory cycl.
Excl.

Feissel et al. [24]
2007
23
ICU
Mech. vent. 8 mL/kg, pressure
Finger
No data
Incl.

Wyffels et al. [25]
2007
32
Postop. heart surgery
Mech. vent. 8–10 mL/kg
Finger
3 respiratory cycl.
No data

Cannesson et al. [26]
2008
25
Preop.CABG
Mech. vent. 8–10 mL/kg, volume
Finger
3 respiratory cycl.
Excl.

Gen.anaesthesia

Westphal et al. [27]
2009
43
Postop. heart surgery
Mech. vent. 8–10 mL/kg, volume
Finger
1 min
Incl.

Zimmermann et al. [28]
2010
20
Preop. abd. surgery
Mech. vent. 7 mL/kg, volume
Finger
No data
No data

Loupec et al. [29]
2011
40
Several categories
Mech. vent. 8 mL/kg, volume
Finger
No data
Incl.

Desgranges et al. [30]
2011
28
Preop. cardiac surgery
Mech. vent. 8 mL/kg, volume
Finger, earlobe
No data
No data

and forehead

Renner et al. [31]
2011
27
Infants preop. cardiac surgery
Mech. vent. 10 mL/kg, volume
No data
No data
Excl.

Pereira de Souza et al. [32]
2011
30
Children preop neurosurgery
Mech. vent. 10 mL/kg, volume
Finger
3 respiratory cycl.
Excl.

Hoiseth et al. [33]
2011
25
During abd. surgery
Mech. vent. 8 mL/kg, volume
Finger
App. 5 min
Incl.

Hood and wilson [34]
2011
25
During colorectal surgery
Mech. vent. 8–10 mL/kg, volume
Finger/earlobe
No data
No data

ICU: intensive care unit; OR: operating room; CABG: coronary artery bypass grafting; AAA: abdominal aortic aneurysm.

Nine studies calculated areas under receiver operating characteristics curves (ROC curves) for ΔPOP [21–27, 32, 33]. It was calculated to >0.85 in four studies [24–27], 0.75–0.85 in one [23], and <0.75 in four [21, 22, 32, 33]. In five studies values for ΔPOP were as good as, or better than, values for ΔPP [23, 24, 26, 27, 33]. In one of these studies, predictive value of ΔPOP was defined as a certain change in ΔPP, thus presuming that ΔPP is a good indicator [27]. One study found poor values for both ΔPP and ΔPOP [33]. Four studies reported lower predictive values for ΔPOP than for ΔPP [21, 22, 25, 32]. Thus, only two of nine studies reported high predictive values for ΔPOP [24, 26]. The ROC curves for ΔPOP and ΔPP were not found to be significantly different in any of the nine studies. The best ΔPOP cut-off value for identifying responders ranged from 9.5 to 15%.

Seven studies calculated ROC curves for PVI [26, 28–32, 34], with values ranging from 0.54 to 0.98. Although correlations between PVI and other parameters vary, predictive values remain relatively good in stable conditions. In one study, the predictive value of PVI decreased from 0.96 at baseline to 0.71 perioperatively [34]. The best PVI cut-off value for identifying responders ranged from 9.5 to 17%.

3.2. Correlations between ΔPOP, PVI, and ΔPP

ΔPP is considered to be a good predictor of fluid responsiveness [6]. Thus, other variables should correlate with ΔPP. 11 of the included papers reported correlations between ΔPP and ΔPOP. Six of these papers reported relatively good correlations () [13, 15, 17, 23, 24, 27]. However, five papers reported relatively poor correlations () [14, 16, 18, 32, 33]. One of these investigated children preoperatively [32]. Landsverk et al. [16] concluded that there are poor correlations between ΔPOP and ΔPP in ICU patients due to sympathetic oscillations in skin circulation, which lead to larger variation in ΔPOP than in ΔPP during registrations over longer time periods. These findings are supported by Hoiseth et al. [33] who also found larger variation in ΔPOP than in ΔPP during ongoing open major abdominal surgery. Four papers examined correlations between PVI and ΔPP. Three of them found relatively poor correlations (, 0.46 and 0.78) [17, 20, 32], whereas one reported better correlations () [29]. Three papers investigated correlations between PVI and ΔPOP [17, 26, 32]. One study reported poor correlations () [32], whereas two studies reported relatively good correlations () [17, 26]. These data are presented in Table 2.

4. Discussion

Photoplethysmography is applicable on most patient categories and is noninvasive, simple, widely available, and without risk of complications. Several physiological, clinical, and practical factors must be taken into account when evaluating whether or not it is a noninvasive alternative to evaluate fluid responsiveness.

Firstly, there are several physiological prerequisitions for using dynamic variables.

Mechanical ventilation provides the stable and predictable variations in intrathoracic pressure required for photoplethysmography to be accurate. A large mechanical tidal volume will influence intrathoracic pressure to a greater extent than a small tidal volume. It is presumed that the influence of tidal volume reaches significance at >8 mL/kg. It is a challenge that the accuracy of photoplethysmography increases with larger tidal volumes, whereas it is clinically desirable to minimize the tidal volume. The accuracy of photoplethysmography relies on a continuous beat-to-beat-analysis. Thus, patients need to have stable heart rate. Additionally, decreased RV ejection fraction can lead to false-positive variations in pulse pressure [35]. These requisitions also apply for other dynamic variables [36–39].

Secondly, the complex network of correlations between ΔPOP/PVI and ΔPP/other hemodynamic variables varies greatly between different studies. The best correlations are found in studies where short registration periods (3–5 respiratory cycles) have been used and in patients under stable pre- and postoperative conditions. These conditions do not reflect genuine intraoperative instability, the setting where precise guidance of fluid therapy is perhaps most important. The correlations are poorer with longer periods of registration [16], in heterogeneous patient groups in ICUs [16], and during ongoing open abdominal surgery [21, 33]. The best predictive values for ΔPOP and PVI were found in papers in which patients were investigated preoperatively [26, 28]. The poorest predictive values (0.51–0.72) were found during ongoing open major abdominal surgery [21, 33], on sedated patients in ICU [22], and on children preoperatively [32]. In one paper, the predictive value of PVI decreased from 0.96 at baseline to 0.71 during surgery [34]. This indicates that photoplethysmography shows best results in standardized conditions, during short registration periods, and in homogenous groups of pre- and postoperative patients. Importantly, it has been demonstrated that PVI reduces both lactate levels and volumes of fluid administered in surgical patients [40]. This is interesting evidence. However, the study does not report improvement in terms of the number of complications. Further studies are needed to clarify the very important aspect of improved outcome.

Finally, a number of additional factors must be considered. Variations in total peripheral resistance and vasomotor tone increase under the influence of general anesthesia [41, 42], with vasoactive drugs, with site of measurement, and with physiological responses such as inflammation, pain, fear, and body temperature. This may lead to inaccuracy of the photoplethysmography signal. The papers included suggest that ΔPOP is less reliable in ICU patients. This may be explained by the above-mentioned factors. Hemodynamics of patients in the OR or in ICUs changes rapidly and continuously. In most papers which good predictive values for photoplethysmography have been found, short registration periods are used. In papers with longer registration periods, poorer predictive values have been reported.

A threshold value refers to a value of ΔPOP, ΔPP, or PVI that separates responders from nonresponders. Failure to agree upon a threshold value in clinical settings does not necessarily make the parameters (i.e., PVI or POP) less valuable. Different patient groups may well present with different threshold values. A septic patient may have a threshold value different from that of a hemodynamically stable patient undergoing surgery. In the same way, threshold values may also change pre-, peri-, and postoperatively. Cannesson et al. [43] discussed the very interesting notion of a gray-zone approach to fluid responsiveness and found that an intermediate zone of pulse pressure variation could not predict fluid responsiveness. Future studies should grade responses instead of dividing responses in two categories.

Cut-off values for increases in SV/CO/CI are defined to separate reponders and nonresponders. These thresholds are based on the variability and errors in the chosen measuring technique as well as what change is believed to be clinically important. These thresholds may be more or less arbitrarily chosen and differ between the studies.

Level of intra-abdominal pressure may influence ΔPP and ΔPOP and is relevant in three of the articles included [21, 28, 33]. Results are not coherent. Animal studies have shown that increased intra-abdominal pressure leads to an increase in ΔPP [44]. Studies investigating the influence of these fluctuations during laparoscopic surgery are currently running.

In theory, a number of potentially confounding factors exist. Different pulse oximeter-technology, errors due to software autogain features which filter and amplify the raw signal (thus making it unreliable for quantitative analysis), atherosclerosis, type of fluid, skin pigmentation, saturation, movement artefacts, statistical weaknesses, variations in pleural and transpulmonary pressures, and venous components of the pulsatile signal may affect measurements.

5. Conclusion

We conclude that although photoplethysmography is a promising technique, predictive values and correlations with other hemodynamic variables indicating fluid responsiveness vary substantially. Based on studies using short registration periods photoplethysmography might seem promising for evaluation of volume status. However, in studies using longer registration periods it has been shown that intra- and interindividual variability for ΔPOP is greater than for ΔPP, leading to poor agreement between ΔPOP and ΔPP. Thus, it is not presently evident that photoplethysmography is adequately accurate, valid, and reliable to be included in clinical practice for evaluation of volume status. In future studies it is important to evaluate new hemodynamic methods in clinically relevant settings and to test their reproducibility in clinically relevant time frames. Relatively poor predictive values during ongoing major surgery further underscore this point and results vary in different patient groups. The greatest potential for photoplethysmography in evaluation of volume status might be in settings where invasive monitoring is not indicated.

Conflict of Interests

There is no conflict of interests for any of the authors.

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