Oximeter Plethysmographic Waveform Research Articles

Pulse oximeter plethysmograph waveform and automated oscillometric sphygmomanometer for ankle-brachial index measurement.

There are limited non-invasive methods to assess lower extremity arterial injuries in the emergency department (ED) and pre-hospital setting. The ankle-brachial index (ABI) requires careful auscultation by Doppler, an approach made difficult in noisy environments. We sought to determine the agreement of the ABI measured using the pulse oximeter plethysmograph waveform (Pleth) with auscultation by Doppler in a controlled setting. A secondary outcome sought to examine the agreement of ABI by automated oscillometric sphygmomanometer (AOS) with Doppler. We measured blood pressure in the right upper and lower extremities of healthy volunteers using: (1) Doppler and manual sphygmomanometer; (2) Pleth and manual sphygmomanometer; and (3) AOS. The Bland-Altman approach to assessing agreement between methods was used comparing mean differences between ABI pairs to their means for Doppler versus Pleth and Doppler versus AOS. The intraclass correlation coefficient (ICC) from mixed effects models examined intra- and inter-rater reliability. Among 100 participants with normal ABI the mean ABI (95%CI) were Doppler 1.11 (0.90-1.33), Pleth 1.10 (0.91-1.30), and AOS 1.10 (0.90-1.30). The ABI difference (95% CI for limits of agreement) were 0.01 (-0.20,0.18) for Doppler-Pleth and 0.02 (-0.26, 0.22) for Doppler-AOS. The ICC for the Doppler-Pleth comparison (ICC=0.56, 95% CI 0.47-0.63) was greater than for the Doppler-AOS (ICC=0.32, 95% CI 0.19-0.43). The ABI measured using the Pleth has a high level of agreement with measurement by Doppler. The AOS and Doppler have good agreement with greater measurement variability. Pleth and AOS may be reasonable alternatives to Doppler for ABI.

Pulse Oximeter Plethysmograph Variation During Hemorrhage in Beta-Blocker–Treated Swine

BackgroundBeta-blockers blunt the stress response to hemorrhage. Our aim was to investigate the feasibility of noninvasive pulse oximeter plethysmographic waveform variation (PoPV) for predicting blood volume loss in an esmolol-treated swine hemorrhagic shock model. Materials and MethodsControlled hemorrhage was induced in eight male domestic pigs. In four pigs, a total of 15% and 30% blood volume was drawn step-by-step over 10 min in each step (controlled hemorrhage–only pigs). In the other four pigs, the heart rate (HR) was reduced and maintained by 30% from baseline by esmolol infusion before controlled hemorrhage (esmolol-treated pigs). Diagnostic abilities of HR, pulse pressure variation (PPV), PoPV, and mean arterial pressure for 15% and 30% blood volume loss were determined by the area under the receiver operating characteristic curve (AUC). ResultsPoPV was well correlated with PPV in controlled hemorrhage–only pigs (r = 0.717) and esmolol-treated pigs (r = 0.532). In controlled hemorrhage-only pigs, HR (AUC = 0.841 and 0.864), PPV (0.878 and 0.843), and PoPV (0.779 and 0.793) accurately predicted 15% and 30% of blood volume loss. In esmolol-treated pigs, the diagnostic ability of HR was decreased (AUC = 0.766 and 0.733). However, diagnostic abilities of PPV (0.848 and 0.804) and PoPV (0.808 and 0.842) were not deteriorated. ConclusionsThe diagnostic ability of HR for blood volume loss was blunted by esmolol. However, those of PPV and PoPV were not altered. PoPV may be considered to be a useful noninvasive tool to predict blood volume loss in injured patients taking beta-blockers.

100EMF Ankle-Brachial Index Measured Using Pulse Oximeter Plethysmograph Waveform and Automated Blood Pressure Device to Assess Lower Extremity Vascular Integrity

There is no practical, readily available and accurate method to assess lower extremity vascular injuries in the emergency department (ED). The ankle-brachial index (ABI) assesses the integrity of the lower-extremity arterial vasculature and the need for emergent vascular imaging. However, ABI measurement requires careful auscultation by Doppler. This measurement is made more difficult by the noisy environment of the ED or during ambulance or helicopter transport. A critical knowledge gap is whether alternative methods of ABI measurement using the pulse oximeter plethysmograph waveform or automated oscillometric sphygmomanometer (Dynamap®) can be substituted for auscultation with Doppler interrogation of the pulse. We sought to test the hypothesis that the ABI measured using the pulse oximeter plethysmograph waveform and Dynamap® have high levels of agreement with measurement by Doppler, the criterion standard for this measurement. We also tested the hypothesis that each measurement technique has high intra-rater reliability. We conducted a cross-sectional study using a convenience sample of healthy adults age 18 or older. We measured systolic blood pressures in each participant’s right arm and right leg and calculated the ABI using three different methods: (1) Doppler and manual sphygmomanometer; (2) Pulse oximeter plethysmograph waveform (“plethysmograph”) and manual sphygmomanometer; and (3) Automated oscillometric sphygmomanometer (Dynamap®). We repeated each method three times and calculated the mean ABI obtained using each method. We used Bland-Altman plots to visually examine agreement of ABI measured using the Doppler and (1) the plethysmograph waveform and (2) the Dynamap®. We measured intraclass correlation coefficients (ICCs) for intra-rater reliability of the three measurements for each method using a two-way mixed effects model for absolute agreement. Among 58 participants enrolled to date, median age was 26 [24, 28] years, 24 (41.4%) were male, 4 (6.9%) Black, 46 (79.3%) White, and 5 (8.6%) Asian race, median BMI 24.08 [21.94, 38.36], and 0 smokers. Mean absolute difference between ABI measured using plethysmograph and Doppler was 0.01 [95% CI -0.12, +0.14] with limits of agreement -0.11 to 0.14. Mean absolute difference between ABI measured by Dynamap® and Doppler was 0.03 (95% CI -0.17, +0.23) with limits of agreement -0.16 to 0.22. The ICCs for intra-rater reliability were as follows: Doppler, 0.64 (95% CI 0.51, 0.76); plethysmograph, 0.67 (95% CI 0.54, 0.77); and Dynamap® 0.45 (95% CI 0.29, 0.60). ABI measured using the pulse oximeter plethysmograph waveform has a high level of agreement with measurement by Doppler. The Dynamap® and Doppler have good agreement but wider limits of agreement than plethysmograph measurement. The Doppler and plethysmograph measurements have good intra-rater reliability. ABI measured using the pulse oximeter plethysmograph waveform may be a valuable adjunct for assessing lower-extremity vascular integrity in noisy clinical environments.

Pulse Oximeter Plethysmograph Estimate of Pulsus Paradoxus as a Measure of Acute Asthma Exacerbation Severity and Response to Treatment.

Pulsus paradoxus is one of the few objective bedside measures of acute asthma exacerbation severity but is difficult to measure in tachypneic and tachycardic patients and in noisy clinical environments. Our primary objective was to examine whether pulse oximeter plethysmograph estimate of pulsus paradoxus (PEP) is associated with physiologic and symptom measures of acute exacerbation severity (airway resistance by impulse oscillometry [%IOS] and the Acute Asthma Intensity Research Score [AAIRS]). Secondary objectives were to validate the previous association of PEP with percent predicted forced expiratory volume in 1 second (%FEV1 ) and to examine associations of change of PEP with change of these outcomes after 2 hours of treatment. This was a secondary analysis of data from a prospective observational study of patients aged 5-17 years with acute asthma exacerbations. The predictor variable, PEP, was measured using a dedicated pulse oximeter and waveform analysis program. Outcome measures included the AAIRS, %IOS, and %FEV1 at baseline and after 2 hours of treatment. We examined associations of PEP with %IOS and the AAIRS at baseline using multiple linear regression models adjusted for age, sex, and race. As secondary analyses we similarly examined the association of PEP with %FEV1 at baseline and change of PEP with change of %IOS, the AAIRS, and %FEV1 after 2 hours of treatment using multiple linear regression models adjusted for the baseline value of the outcome measure and the AAIRS. Among 684 participants (61% males; 61% African American) there were associations of baseline PEP with %IOS, the AAIRS, and %FEV1 (p < 0.001). Change of PEP after 2 hours of treatment was associated with change of %FEV1 (p < 0.001) and change of the AAIRS (p = 0.01) but not with change of %IOS (p = 0.60). PEP demonstrates criterion validity in predicting baseline %IOS, the AAIRS, and %FEV1 , and responsiveness to change of the AAIRS and %FEV1 . Data contained in the oximeter plethysmograph waveform might be utilized as a continuous, objective measure of acute asthma exacerbation severity and real-time response to treatment.

Pleth variability index is a weak predictor of fluid responsiveness in patients receiving norepinephrine

In patients receiving an infusion of norepinephrine, the relationship between the amplitude of the oximeter plethysmographic waveform and stroke volume may be variable and quality of the waveform might be reduced, compared with patients not receiving norepinephrine. We assessed the reliability of the pleth variability index (PVI), an automatic measurement of the respiratory variation of the plethysmographic waveform, for predicting fluid responsiveness in patients receiving norepinephrine infusions. We measured the response of cardiac index (transpulmonary thermodilution) to i.v. fluid administration in 42 critically ill patients receiving norepinephrine. Patients with arrhythmias, spontaneous breathing, tidal volume <8 ml kg(-1), and respiratory system compliance <30 ml cm H(2)O(-1) were excluded. Before fluid administration, we recorded the arterial pulse pressure variation (PPV) and pulse contour analysis-derived stroke volume variation (SVV, PiCCO2) and PVI (Masimo Radical-7). In seven patients, the plethysmographic signal could not be obtained. Among the 35 remaining patients [mean SAPS II score=77 (sd=17)], i.v. fluid increased cardiac index ≥15% in 15 'responders'. A baseline PVI ≥16% predicted fluid responsiveness with a sensitivity of 47 (inter-quartile range=21-73)% and a specificity of 90 (68-99)%. The area under the receiver operating characteristic curve was significantly lower for PVI [0.68 (0.09)] than for PPV and SVV [0.93 (0.06) and 0.89 (0.07), respectively]. Considering all pairs of measurements, PVI was correlated with PPV (r(2)=0.27). The fluid-induced changes in PVI and PPV were not significantly correlated. PVI was less reliable than PPV and SVV for predicting fluid responsiveness in critically ill patients receiving norepinephrine. In addition, PVI could not be measured in a significant proportion of patients. This suggests that PVI is not useful in patients receiving norepinephrine.

Pulse Oximeter Plethysmographic Waveform Changes in Awake, Spontaneously Breathing, Hypovolemic Volunteers

McGrath, Susan P.*; Ryan, Kathy L.†; Wendelken, Suzanne M.*; Rickards, Caroline A.†; Convertino, Victor A.† Author Information

Assessment of Intravascular Fluid Status and Fluid Responsiveness during Mechanical Ventilation in Surgical and Intensive Care Patients

Fluid management of critically ill patients and those undergoing major surgery can be extremely difficult. It is important to predict which patients will respond to volume expansion in order to avoid undesired hypovolaemia and fluid overload. Traditionally, central venous pressure and pulmonary artery occlusion pressure have been used to guide fluid management. However, assimilation of available evidence from the past twenty years demonstrates that neither central venous pressure nor pulmonary artery occlusion pressure appears to be a useful predictor of haemodynamic response to fluid challenge. Recent evidence suggests that stroke volume variation, pulse pressure variation and the variation of the amplitude of the pulse oximeter plethysmographic waveform are far more accurate in predicting volume responsiveness in the intensive care unit. It is important for intensivists and perioperative physicians to understand the strengths and limitations of each method in order to scrutinise and interpret such data appropriately.

Accuracy of stroke volume variation compared with pleth variability index to predict fluid responsiveness in mechanically ventilated patients undergoing major surgery

Accurate assessment of a patient's volume status is an important goal for an anaesthetist. However, most variables assessing fluid responsiveness are either invasive or technically challenging. This study was designed to compare the accuracy of arterial pressure-based stroke volume variation (SVV) and variations in the pulse oximeter plethysmographic waveform amplitude as evaluated with the noninvasive calculated pleth variability index (PVI) with central venous pressure to predict the response of stroke volume index (SVI) to volume replacement in patients undergoing major surgery. We studied 20 patients scheduled for elective major abdominal surgery. After induction of anaesthesia, all haemodynamic variables were recorded immediately before (T1) and subsequent to volume replacement (T2) by infusion of 6% hydroxy-ethyl starch (HES) 130/0.4 (7 ml kg) at a rate of 1 ml kg min. The volume-induced increase in SVI was at least 15% in 15 patients (responders) and less than 15% in five patients (nonresponders). Baseline SVV correlated significantly with changes in SVI (DeltaSVI; r = 0.80; P < 0.001) as did baseline PVI (r = 0.61; P < 0.004), whereas baseline values of central venous pressure showed no correlation to DeltaSVI. There was no significant difference between the area under the receiver operating characteristic curve for SVV (0.993) and PVI (0.973). The best threshold values to predict fluid responsiveness were more than 11% for SVV and more than 9.5% for PVI. Although arterial pressure-derived SVV revealed the best correlation to volume-induced changes in SVI, the results of our study suggest that both variables, SVV and PVI, can serve as valid indicators of fluid responsiveness in mechanically ventilated patients undergoing major surgery.

Noninvasive assessment of asthma severity using pulse oximeter plethysmograph estimate of pulsus paradoxus physiology

BackgroundPulsus paradoxus estimated by dynamic change in area under the oximeter plethysmograph waveform (PEP) might provide a measure of acute asthma severity. Our primary objective was to determine how well PEP correlates with forced expiratory volume in 1-second (%FEV1) (criterion validity) and change of %FEV1 (responsiveness) during treatment in pediatric patients with acute asthma exacerbations.MethodsWe prospectively studied subjects 5 to 17 years of age with asthma exacerbations. PEP, %FEV1, airway resistance and accessory muscle use were recorded at baseline and at 2 and 4 hours after initiation of corticosteroid and bronchodilator treatments. Statistical associations were tested with Pearson or Spearman rank correlations, logistic regression using generalized estimating equations, or Wilcoxon rank sum tests.ResultsWe studied 219 subjects (median age 9 years; male 62%; African-American 56%). Correlation of PEP with %FEV1 demonstrated criterion validity (r = - 0.44, 95% confidence interval [CI], - 0.56 to - 0.30) and responsiveness at 2 hours (r = - 0.31, 95% CI, - 0.50 to - 0.09) and 4 hours (r = - 0.38, 95% CI, - 0.62 to - 0.07). PEP also correlated with airway resistance at baseline (r = 0.28 for ages 5 to 10; r = 0.45 for ages 10 to 17), but not with change over time. PEP was associated with accessory muscle use (OR 1.16, 95% CI, 1.11 to 1.21, P < 0.0001).ConclusionsPEP demonstrates criterion validity and responsiveness in correlations with %FEV1. PEP correlates with airway resistance at baseline and is associated with accessory muscle use at baseline and at 2 and 4 hours after initiation of treatment. Incorporation of this technology into contemporary pulse oximeters may provide clinicians improved parameters with which to make clinical assessments of asthma severity and response to treatment, particularly in patients who cannot perform spirometry because of young age or severity of illness. It might also allow for earlier recognition and improved management of other disorders leading to elevated pulsus paradoxus.

Pulse Oximeter Plethysmographic Waveform Changes in Awake, Spontaneously Breathing, Hypovolemic Volunteers

The primary objective of this study was to determine whether alterations in the pulse oximeter waveform characteristics would track progressive reductions in central blood volume. We also assessed whether changes in the pulse oximeter waveform provide an indication of blood loss in the hemorrhaging patient before changes in standard vital signs. Pulse oximeter data from finger, forehead, and ear pulse oximeter sensors were collected from 18 healthy subjects undergoing progressive reduction in central blood volume induced by lower body negative pressure (LBNP). Stroke volume measurements were simultaneously recorded using impedance cardiography. The study was conducted in a research laboratory setting where no interventions were performed. Pulse amplitude, width, and area under the curve (AUC) features were calculated from each pulse wave recording. Amalgamated correlation coefficients were calculated to determine the relationship between the changes in pulse oximeter waveform features and changes in stroke volume with LBNP. For pulse oximeter sensors on the ear and forehead, reductions in pulse amplitude, width, and area were strongly correlated with progressive reductions in stroke volume during LBNP (R(2) ≥ 0.59 for all features). Changes in pulse oximeter waveform features were observed before profound decreases in arterial blood pressure. The best correlations between pulse features and stroke volume were obtained from the forehead sensor area (R(2) = 0.97). Pulse oximeter waveform features returned to baseline levels when central blood volume was restored. These results support the use of pulse oximeter waveform analysis as a potential diagnostic tool to detect clinically significant hypovolemia before the onset of cardiovascular decompensation in spontaneously breathing patients.

Using ventilation-induced plethysmographic variations to optimize patient fluid status

Hypovolemia is one of the most frequent causes of arterial hypotension in the operating room. Pulse oximeter plethysmographic waveform, obtained using a noninvasive and widely available device, has recently shown its potential interest in predicting fluid responsiveness in mechanically ventilated patients under mechanical ventilation. This review highlights new applications of this routine monitoring. Respiratory variations in the plethysmographic waveform amplitude have been correlated with respiratory variations in arterial pulse pressure and can predict fluid responsiveness in mechanically ventilated patients under general anesthesia. Until recently, pulse oximeter plethysmographic waveform had to be recorded and analyzed off line using software algorithms. Bringing this new index into the clinical field would require devices allowing for automated and continuous real time calculation. Such devices will have potential to guide fluid optimization in the operating room. Automatic detection of respiratory variations in pulse oximetry plethysmographic waveform amplitude can predict fluid responsiveness in the operating room in patients under mechanical ventilation and has potential for fluid optimization in this setting.

Pleth variability index to monitor the respiratory variations in the pulse oximeter plethysmographic waveform amplitude and predict fluid responsiveness in the operating theatre

BackgroundRespiratory variations in pulse oximetry plethysmographic waveform amplitude (ΔPOP) can predict fluid responsiveness in mechanically ventilated patients but cannot be easily assessed at the bedside. Pleth variability index (PVI) is a new algorithm allowing for automated and continuous monitoring of ΔPOP. We hypothesized that PVI can predict fluid responsiveness in mechanically ventilated patients under general anaesthesia. MethodsTwenty-five patients were studied after induction of general anaesthesia. Haemodynamic data [cardiac index (CI), respiratory variations in arterial pulse pressure (ΔPP), ΔPOP, and PVI] were recorded before and after volume expansion (500 ml of hetastarch 6%). Fluid responsiveness was defined as an increase in CI ≥15%. ResultsVolume expansion induced changes in CI [2.0 (sd 0.9) to 2.5 (1.2) litre min−1 m−2; P<0.01], ΔPOP [15 (7)% to 8 (3)%; P<0.01], and PVI [14 (7)% to 9 (3)%; P<0.01]. ΔPOP and PVI were higher in responders than in non-responders [19 (9)% vs 9 (4)% and 18 (6)% vs 8 (4)%, respectively; P<0.01 for both]. A PVI >14% before volume expansion discriminated between responders and non-responders with 81% sensitivity and 100% specificity. There was a significant relationship between PVI before volume expansion and change in CI after volume expansion (r=0.67; P<0.01). ConclusionsPVI, an automatic and continuous monitor of ΔPOP, can predict fluid responsiveness non-invasively in mechanically ventilated patients during general anaesthesia. This index has potential clinical applications.

Does the Pleth Variability Index Indicate the Respiratory-Induced Variation in the Plethysmogram and Arterial Pressure Waveforms?

Respiratory variations in the pulse oximeter plethysmographic waveform amplitude (deltaPOP) are sensitive to changes in preload and can predict fluid responsiveness in mechanically ventilated patients. However, they cannot be easily calculated from a bedside monitor. Pleth variability index (PVI, Masimo Corp., Irvine, CA) is a new algorithm that automatically calculates deltaPOP. The aim of our study was to test the ability of this new device to automatically and continuously monitor deltaPOP. Twenty-five patients were studied after induction of general anesthesia. PVI automatically and continuously calculates the respiratory variations in the plethysmography waveform amplitude (perfusion index). Data (mean arterial blood pressure, central venous pressure, respiratory variations in arterial pulse pressure, deltaPOP, and PVI) were recorded at baseline in anti-Trendelenburg position and, finally, in Trendelenburg position. There was a significant relationship between PVI and deltaPOP (r = 0.92; P < 0.05). Over the 75 measurements, 42 (56%) presented a deltaPOP value > 13%. A PVI threshold value of 11.5% was able to discriminate between deltaPOP >13% and deltaPOP < or = 13% with a sensitivity of 93% and a specificity of 97%. Area under the curve for PVI to predict deltaPOP > 13% was 0.990 +/- 0.07. This study is the first to demonstrate the ability of PVI, an index automatically derived from the pulse oximeter waveform analysis, to automatically and continuously monitor deltaPOP. This new index has potential clinical applications for noninvasive fluid responsiveness monitoring.

At the Threshold of Noninvasive Functional Hemodynamic Monitoring

At the Threshold of Noninvasive Functional Hemodynamic Monitoring

Estimation of airway obstruction using oximeter plethysmograph waveform data

BackgroundValidated measures to assess the severity of airway obstruction in patients with obstructive airway disease are limited. Changes in the pulse oximeter plethysmograph waveform represent fluctuations in arterial flow. Analysis of these fluctuations might be useful clinically if they represent physiologic perturbations resulting from airway obstruction. We tested the hypothesis that the severity of airway obstruction could be estimated using plethysmograph waveform data.MethodsUsing a closed airway circuit with adjustable inspiratory and expiratory pressure relief valves, airway obstruction was induced in a prospective convenience sample of 31 healthy adult subjects. Maximal change in airway pressure at the mouthpiece was used as a surrogate measure of the degree of obstruction applied. Plethysmograph waveform data and mouthpiece airway pressure were acquired for 60 seconds at increasing levels of inspiratory and expiratory obstruction. At each level of applied obstruction, mean values for maximal change in waveform area under the curve and height as well as maximal change in mouth pressure were calculated for sequential 7.5 second intervals. Correlations of these waveform variables with mouth pressure values were then performed to determine if the magnitude of changes in these variables indicates the severity of airway obstruction.ResultsThere were significant relationships between maximal change in area under the curve (P < .0001) or height (P < 0.0001) and mouth pressure.ConclusionThe findings suggest that mathematic interpretation of plethysmograph waveform data may estimate the severity of airway obstruction and be of clinical utility in objective assessment of patients with obstructive airway diseases.

Pulse Oximetry Plethysmographic Waveform During Changes in Blood Volume

Systolic pressure variation (SPV) and its dDown component have been shown to be sensitive factors in estimating intravascular volume in patients undergoing mechanical ventilation. In this study, ventilation-induced changes in pulse oximeter plethysmographic waveform were evaluated after removal and after reinfusion of 10% estimated blood volume. The plethysmographic waveform variation (SPVplet) was measured as the difference between maximal and minimal peaks of waveform during the ventilatory cycle, and expressed as a percentage of the signal amplitude during apnoea. dUp(plet) and dDown(plet) were measured as the distance between the apnoeic plateau and the maximal or minimal plethysmographic systolic waveform, respectively. Intravascular volume was changed by removal of 10% of estimated blood volume and followed by equal volume replacement with Haemaccel. A 10% decrease in blood volume increased SPVplet from mean 17.0 (SD 11.8)% to 31.6 (28.0)% (P = 0.005) and dDown(plet) from 8.7 (5.1)% to 20.5 (12.9)% (P = 0.0005) compared with baseline. Changes in plethysmographic waveform correlated with changes in arterial SPV and dDown (r = 0.85; P = 0.0009). In the absence of invasive arterial pressure monitoring, ventilation-induced waveform variability of the plethysmographic signal measured from pulse oximetry is a useful tool in the detection of mild hypovolaemia.

Pulse oximetry plethysmographic waveform during changes in blood volume

Systolic pressure variation (SPV) and its dDown component have been shown to be sensitive factors in estimating intravascular volume in patients undergoing mechanical ventilation. In this study, ventilation-induced changes in pulse oximeter plethysmographic waveform were evaluated after removal and after reinfusion of 10% estimated blood volume. The plethysmographic waveform variation (SPVplet) was measured as the difference between maximal and minimal peaks of waveform during the ventilatory cycle, and expressed as a percentage of the signal amplitude during apnoea. dUp(plet) and dDown(plet) were measured as the distance between the apnoeic plateau and the maximal or minimal plethysmographic systolic waveform, respectively. Intravascular volume was changed by removal of 10% of estimated blood volume and followed by equal volume replacement with Haemaccel. A 10% decrease in blood volume increased SPVplet from mean 17.0 (SD 11.8)% to 31.6 (28.0)% (P = 0.005) and dDown(plet) from 8.7 (5.1)% to 20.5 (12.9)% (P = 0.0005) compared with baseline. Changes in plethysmographic waveform correlated with changes in arterial SPV and dDown (r = 0.85; P = 0.0009). In the absence of invasive arterial pressure monitoring, ventilation-induced waveform variability of the plethysmographic signal measured from pulse oximetry is a useful tool in the detection of mild hypovolaemia.