Introduction

Pleth Variability Index (PVI) is a new algorithm that allows continuous and automatic estimation of respiratory variations in the pulse oximeter waveform amplitude. Our aim was to test its ability to detect changes in preload induced by passive leg raising (PLR) in spontaneously breathing volunteers.

Methods

We conducted a prospective observational study. Twenty-five spontaneously breathing volunteers were enrolled. PVI, heart rate and noninvasive arterial pressure were recorded. Cardiac output was assessed using transthoracic echocardiography. Volunteers were studied in three successive positions: baseline (semirecumbent position); after PLR of 45 degrees with the trunk lowered in the supine position; and back in the semirecubent position.

Results

We observed significant changes in cardiac output and PVI during changes in body position. In particular, PVI decreased significantly from baseline to PLR (from 21.5 +/- 8.0% to 18.3 +/- 9.4%; P < 0.05) and increased significantly from PLR to the semirecumbent position (from 18.3 +/- 9.4% to 25.4 +/- 10.6 %; P < 0.05). A threshold PVI value above 19% was a weak but significant predictor of response to PLR (sensitivity 82%, specificity 57%, area under the receiver operating characteristic curve 0.734 +/- 0.101).

Conclusion

PVI can detect haemodynamic changes induced by PLR in spontaneously breathing volunteers. However, we found that PVI was a weak predictor of fluid responsiveness in this setting.

Background

Left ventricular stroke area by transoesophageal echocardiographic automated border detection has been shown to be strongly correlated to left ventricular stroke volume. Respiratory variations in left ventricular stroke volume or its surrogates are good predictors of fluid responsiveness in mechanically ventilated patients. We hypothesised that respiratory variations in left ventricular stroke area (DeltaSA) can predict fluid responsiveness.

Methods

Eighteen mechanically ventilated patients undergoing coronary artery bypass grafting were studied immediately after induction of anaesthesia. Stroke area was measured on a beat-to-beat basis using transoesophageal echocardiographic automated border detection. Haemodynamic and echocardiographic data were measured at baseline and after volume expansion induced by a passive leg raising manoeuvre. Responders to passive leg raising manoeuvre were defined as patients presenting a more than 15% increase in cardiac output.

Results

Cardiac output increased significantly in response to volume expansion induced by passive leg raising (from 2.16 +/- 0.79 litres per minute to 2.78 +/- 1.08 litres per minute; p < 0.01). DeltaSA decreased significantly in response to volume expansion (from 17% +/- 7% to 8% +/- 6%; p < 0.01). DeltaSA was higher in responders than in non-responders (20% +/- 5% versus 10% +/- 5%; p < 0.01). A cutoff DeltaSA value of 16% allowed fluid responsiveness prediction with a sensitivity of 92% and a specificity of 83%. DeltaSA at baseline was related to the percentage increase in cardiac output in response to volume expansion (r = 0.53, p < 0.01).

Conclusion

DeltaSA by transoesophageal echocardiographic automated border detection is sensitive to changes in preload, can predict fluid responsiveness, and can quantify the effects of volume expansion on cardiac output. It has potential clinical applications.

Abstract Introduction Systemic inflammatory response syndrome (SIRS) is a frequent condition after cardiopulmonary bypass (CPB) and makes conventional biological tests fail to detect postoperative sepsis. Biphasic waveform (BPW) analysis is a new biological test derived from activated partial thromboplastin time that has recently been proposed for sepsis diagnosis. The aim of this study was to investigate the accuracy of BPW to detect sepsis after cardiac surgery under CPB. Methods We conducted a prospective study in American Society of Anesthesiologists' (ASA) physical status III and IV patients referred for cardiac surgery under CPB. Procalcitonin (PCT) and BPW were recorded before surgery and every day during the first week following surgery. Patients were then divided into three groups: patients presenting no SIRS, patients presenting with non-septic SIRS and patients presenting with sepsis. Results Thirty two patients were included. SIRS occurred in 16 patients (50%) including 5 sepsis (16%) and 11 (34%) non-septic SIRS. PCT and BPW were significantly increased in SIRS patients compared to no SIRS patients (0.9 [0.5-2.2] vs. 8.1 [2.0-21.3] ng/l for PCT and 0.10 [0.09-0.14] vs. 0.29 [0.16-0.56] %T/s for BPW; P < 0.05 for both). We observed no difference in peak PCT value between the sepsis group and the non-septic SIRS group (8.4 [7.5-32.2] vs. 7.8 [1.9-17.5] ng/l; P = 0.67). On the other hand, we found that BPW was significantly higher in the sepsis group compared to the non-septic SIRS group (0.57 [0.54-0.78] vs. 0.19 [0.14-0.29] %T/s; P < 0.01). We found that a BPW threshold value of 0.465%T/s was able to discriminate between sepsis and non-septic SIRS groups with a sensitivity of 100% and a specificity of 93% (area under the curve: 0.948 +/- 0.039; P < 0.01). Applying the previously published threshold of 0.25%T/s, we found a sensitivity of 100% and a specificity of 72% to discriminate between these two groups. Neither C-reactive protein (CRP) nor PCT had significant predictive value (area under the curve for CRP was 0.659 +/- 0.142; P = 0.26 and area under the curve for PCT was 0.704 +/- 0.133; P = 0.15). Conclusions BPW has potential clinical applications for sepsis diagnosis in the postoperative period following cardiac surgery under CPB.