Prediction of fluid responsiveness for patients in shock using a ventilator disconnection test combined with the pulse contour-derived cardiac index
Pages 629 - 638
Abstract
Background:
Finding a simple and reliable method to predict and assess fluid responsiveness has long been of clinical interest.
Objective:
To investigate the predictive value of a ventilator disconnection (DV) test combined with the pulse contour-derived cardiac output (PiCCO) index on fluid responsiveness for patients in shock.
Methods:
Thirty-two patients were chosen for the study. Patients who were in shock, received mechanical ventilation, and met the inclusion criteria were selected. Patients were divided into a fluid-responsive group (14 patients) and fluid-unresponsive group (18 patients) based on whether the increase in cardiac index (Δ CI) was > 10% or not, respectively, following the fluid challenge test. Changes in heart rate, pulse oximeter-measured oxygen saturation, mean arterial pressure (MAP), and CI before and after passive leg raising (PLR), DV, and fluid challenge tests were observed. We used Pearson’s correlation coefficient to analyze an increase in the MAP (Δ MAP) and Δ CI before and after the PLR, DV, and fluid challenge tests; the sensitivity and specificity of the Δ MAP and Δ CI in the PLR and DV tests for predicting fluid response were also analyzed by plotting the receiver operating characteristic (ROC) curves.
Results:
CI results in the PLR and DV tests, as well as the fluid challenge test, were significantly higher in the fluid-responsive group compared with before the test (P< 0.05). The Δ CI before and after the PLR, DV, and fluid challenge tests were positively correlated among patients in the fluid-responsive group. The area under the ROC curve for the post-PLR test CI and the post-DV CI for predicting fluid responsiveness was 0.869 (95% confidence interval (CI) [0.735–1.000, P= 0.000]) and 0.937 (95% CI [0.829–1.000, P= 0.000]), respectively, in patients in the fluid-responsive group. The sensitivity and specificity of the post-DV CI for predicting fluid responsiveness in all patients was 100.0% and 88.9%, respectively, using a 5% increase as the cut-off value.
Conclusion:
Application of DV, combined with PiCCO, has a high predictive value for fluid responsiveness among patients in shock.
References
[1]
Vincent J-L, De Backer D, et al. Circulatory shock. N Engl J Med. 2013; 369: 1726-1734.
[2]
Marik PE, Baram M. Noninvasive hemodynamic monitoring in the intensive care unit. Crit Care Clin. 2007; 23(3): 383-400.
[3]
Alsous F, Khamiees M, DeGirolamo A, et al. Negative fluid balance predicts survival in patients with septic shock: A retrospective pilot study. Chest. 2000; 117(6): 1749-1754.
[4]
Michard F, Teboul JL. Predicting fluid responsiveness in ICU patients: A critical analysis of the evidence. Chest. 2002; 121(6): 2000-2008.
[5]
Marik PE, Monnet X, Teboul JL. Hemodynamic parameters to guide fluid therapy. Ann Intensive Care. 2011; 1(1): 1.
[6]
Monnet X, Teboul JL. Passive leg raising. Intensive Care Med. 2008; 34(4): 659-663.
[7]
Preau S, Saulnier F, Dewavrin F, et al. Passive leg raising is predictive of fluid responsiveness in spontaneously breathing patients with severe sepsis or acute pancreatitis. Crit Care Med. 2010; 38(3): 819-825.
[8]
Monnet X, Osman D, Ridel C, et al. Predicting volume responsiveness by using the end-expiratory occlusion in mechanically ventilated intensive care patients. Crit Care Med. 2009; 37(3): 951-956.
[9]
Monnet X, Rienzo M, Osman D, et al. Passive leg raising predicts fluid responsiveness in the critically ill. Crit Care Med. 2006; 34(5): 1402-1407.
[10]
Osman D, Ridel C, Ray P, et al. Cardiac filling pressures are not appropriate to predict hemodynamic response to volume challenge. Crit Care Med. 2007; 35(1): 64-68.
[11]
Marik PE, Baram M, Vahid B. Does central venous pressure predict fluid responsiveness? A systematic review of the literature and the tale of seven mares. Chest. 2008; 134(1): 172-178.
[12]
Cannesson M. Arterial pressure variation and goal-directed fluidtherapy. J Cardiothorac Vasc Anesth. 2010; 24(3): 487-497.
[13]
Marik PE, Cavallazzi R, Vasu T, et al. Dynamic changes in arterial waveform derived variables and fluid responsiveness in mechanically ventilated patients: A systematic review of the literature. Crit Care Med. 2009; 37(9): 2642-2647.
[14]
Teboul JL, Monnet X. Prediction of volume responsiveness in critically ill patients with spontaneous breathing activity. Curr Opin Crit Care. 2008; 14(3): 334-339.
[15]
Monnet X, Bleibtreu A, Ferré A, et al. Passive legraising and end-expiratory occlusion tests perform better than pulse pressure variation in patients with low respiratory system compliance. Crit Care Med. 2012; 40(1): 152-157.
[16]
Rossi A, Polese G, Conti G, et al. Intrinsic positive end-expiratory pressure (PEEPi). Intensive Care Med. 1995; 21(6): 522-536.
[17]
Preau S, Saulnier F, Dewavrin F, et al. Passive leg raising is predictive of fluid responsiveness in spontaneously breathing patients with severe sepsis or acute pancreatitis. Crit Care Med. 2010; 38(3): 819-825.
Recommendations
Predicting fluid-response, the heart of hemodynamic management: A model-based solution
Abstract BackgroundIntravenous fluid infusions are an important therapy for patients with circulatory shock. However, it is challenging to predict how patients’ cardiac stroke volume (SV) will respond, and thus identify how much ...
Highlights- Clinically-applicable model predicts fluid infusion response.
- Model-predicted ...
Sudden cardiac death (SCD) prediction based on nonlinear heart rate variability features and SCD index
SCD is predicated using SVM classifier and sudden cardiac death index (SCDI).Nonlinear features are extracted from HRV signals.SVM predicts SCD with 94.7% accuracy four minutes before its onset.SCDI predicts SCD accurately. In our previous work, we have ...
A new shock/discontinuity detector
A new effective shock/discontinuity detector has been developed in this work. The detector has two steps. The first step is to check the ratio of the truncation errors on the coarse and fine grids, and the second step is to check the local ratio of the ...
Comments
Information & Contributors
Information
Published In
© 2024 – IOS Press. All rights reserved.
Publisher
IOS Press
Netherlands
Publication History
Published: 01 January 2024
Author Tags
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 31 Jan 2025