Prompt treatment of hypovolemia is necessary to sustain blood pressure, blood flow & tissue perfusion. Excessive volume administration may result in edema formation and impaired tissue perfusion, with consequent organ dysfunction and increased risk of morbidity and even death.
Un-monitored attempts at central blood volume expansion can be dangerous.
Because blood volume cannot be reliably assessed clinically, the likelihood of hemodynamic response (preload responsiveness) and the actual magnitude of the response to a volume challenge (cardiac output/ stroke volume response) have replaced the use of static volume parameters such as; mean arterial pressure, central venous pressure (CVP) or pulmonary capillary wedge pressure (PCWP).
Arterial preload responsiveness parameters have been calculated manually from arterial blood pressure displayed monitors since at least the late 1960’s. Automated display of; systolic pressure variation (SPV), pulse pressure variation (PPV%), stroke volume variation (SVV%) and stroke volume response (∆SV) are now increasingly used to guide fluid management in the arterial line patient and their protocolized use has been shown to lead to improvements in outcome. (Lopes et al. 2007).
The preload response parameters reported by the LiDCOrapid are all mathematically derived from the PulseCO™ algorithm’s primary measured parameters. They have been independently validated to be appropriately sensitive, specific and precise. When used as diagnostic aids in a fluid management protocol they have been associated with improved outcome in high-risk surgery and transplantation applications.
Studies validating the precision, sensitivity, and utility of LiDCO’s pulse power algorithm (PulseCO™) derived fluid responsiveness and stroke volume response parameters in different patient populations.
Cardiac surgery: Belloni et al. 2007 showed that PPV% and SVV% before fluid challenge were significantly higher in the fluid responder group than in the non-responder group. Patients with PPV% and SVV% of 12% were responsive to fluid challenges, whereas patients who did not increase their cardiac index in response to fluid challenge had PPV% and SVV% < 10%. A significant correlation among baseline PPV% & SVV% and change in cardiac index was also shown; patients with a high value of PPV% & SVV% at baseline responded to volume loading with a larger increase in cardiac index.
Therefore, LiDCO’s baseline PPV% & SVV% provided useful information about the patients’ position on an individual Starling curve. The greater the PPV% & SVV%, the more likely the patient was to be responsive to ventricular fluid loading. Finally, in the fluid responder group, the mean PPV% & SVV% were significantly lower after the fluid challenge compared with baseline values, indicating a change in their volume status after fluid administration.
The authors concluded:
“PCO-LiDCO technology used in this study provided reliable measurements of PPV%, SVV%, and SPV. A further advantage of this technique was that it only required peripheral intravenous and arterial access, both of which are commonly placed for perioperative care.”
Wyffels et al. 2010 also examined the performance of the LiDCO monitor PPV% and SVV% in a cardiac surgery population. They investigated the ability of pulse pressure variation and stroke volume variation to predict fluid responsiveness during mechanical ventilation in 15 patients undergoing open chest surgery by comparing their respective correlations with cardiac output changes induced by a passive leg raise. Under closed chest conditions, both pulse pressure variation and stroke volume variation correlated well with the induced cardiac output changes (r = 0.856, P = 0.002 and r = 0.897, P = 0.0012, respectively). Their data show that LiDCO’s pulse pressure variation and stroke volume variation are valid predictors of fluid responsiveness under closed chest conditions. In contrast, the static parameters of CVP or wedge pressure did not predict fluid response.
Bariatric surgery: Avery et al. 2010 assessed the LiDCO preload responsiveness parameters in bariatric surgery patients. ROC curve analysis gave predicted cut-off limits of 9.5% for SVV% (AUC = 0.900), 15.5% for PPV% (AUC=0.912). There was no difference between SVV% and PPV% (p=0.69). Sensitivity and specificity for SVV% (100 & 75) and PPV% (100 & 85) were similar and acceptable, whereas that of HR (87 & 35) and MAP (75 & 60) were less reliable.
Their conclusion was:
“PulseCO™ derived Stroke Volume Variation predicts fluid responsiveness in the morbidly obese with consistent sensitivity and specificity. This compares favorably with studies in non-obese patients.”
Intensive care: Cecconi et al. 2009 assessed the LiDCO/PulseCO™ preload responsiveness parameters in post-operative intensive care patients on IPPV with 8ml/kg tidal volumes and PEEP of 5cm H20. Only PPV% and SVV% were able to give cutoff values with sensitivity and specificity >50%. ROC curve analysis gave predicted cut-off limits of 11% for SVV% (Sens: 72%, Spec: 79%) and for PPV% >12% (Sens: 86%, Spec: 70%).
Their conclusion was:
“SVV, PPV and SPV of PulseCO are good predictors of Fluid Responsiveness in fully sedated and mechanically ventilated patients in the intensive care.”
Effects of vasoactive drugs on PPV%/ SVV%. A key question for pressure waveform analysis methods has been their robustness in the presence of vasoactive administration – Hadian et al. 2010 investigated the effects of vasoactive therapy on LIDCO’s PPV% and SVV%. Seventy-one paired events were studied – 38 vasodilators, 10 vasoconstrictor & 14 inotrope administrations. As expected, vasodilator therapy increased PPV% and SVV% from 13% to 17% and 9 to 15% respectively (P < 0.001). Whereas, increasing inotropes or vasoconstriction did not alter PPV% and SVV%. The authors’ conclusion was “ Thus, SVV% and PPV% can be used to drive fluid resuscitation algorithms in the setting of changing vasoactive drug therapy”.
High-risk general surgery: Richard et al. 2010 compared measurements of arterial pulse pressure variation (PPV) from the LiDCOrapid to the same parameter displayed by the Philips Intellivue MP50 monitors on patients during high-risk abdominal surgery.
Their conclusions were that the:
“LiDCOrapid PPV measurement demonstrated a high degree of correlation with the Philips Intellivue MP50 PPV values. Use of either monitor should generate accurate measurements of continuous PPV to guide fluid resuscitation.”
Stroke volume response
No fluid responsiveness parameter is 100% accurate in predicting the magnitude of the fluid response. The increase in stroke volume needs to be> 10% for a 200 ml infusion, or the hemodilution effects will override the flow increase resulting in a net decrease in oxygen delivery. Therefore a very necessary safety check is for the clinician to monitor the fluid response itself (% change in blood flow/stroke volume) to the fluid administration. Trended stroke volume response (∆SV) should be displayed in order that the user can reassure them that the response is proportionate to the volume of fluid infused.
The LiDCOrapid monitor shows both trended changes in SVV% or PPV% and ∆SV in response to fluid challenges to increase stroke volume – see below for an example:
The absolute precision of the PulseCO™ algorithm for discerning the small stroke volume changes necessary to detect small changes in SVV% and ∆SV was investigated at Pittsburgh University by Marquez et al. 2008. The PulseCO™ derived stroke volume changes following an inferior vena cava occlusion were compared to flow changes measured with an aortic electromagnetic flow probe.
These investigators showed elegantly that the PulseCO™ algorithm can precisely follow small acute/fast changes in stroke volume. Another US-based group at Columbia University, NY (Dizon et al. 2010) showed that the core PulseCO™ algorithm could discriminate < 5% changes of stroke volume in heart failure patients undergoing biventricular pacemaker resynchronisation.
They further showed that patients with a > 5% improvement of stroke volume performed better at 2-month follow-up clinics in terms of length of 6 min walk, and improvement in their echocardiographic dyssynchrony profile.
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2. Murugan R, Venkataraman R, Wahed A, Elder M, Carter M, Madden N, Kellum J. Preload responsiveness is associated with increased interleukin-6 and lower organ yield from brain-dead donors. Crit Care Med. 2009;37(8):2387-2393.
3. Jain A, Dutta A. Stroke Volume Variation as a Guide to Fluid Administration in Morbidly Obese Patients Undergoing Laparoscopic Bariatric Surgery. Obes Surg. 2010. DOI 10.1007/s11695-009-0070
4. Abdel-Galil K, Craske D, McCaul J. Optimisation of intraoperative haemodynamics: early experience of its use in major head and neck surgery. Br J Oral and Maxillofac Surg. 2010;48(3):189-191.
5. Brass P, Mills E, Latza J, Peters J, Berendes E. LiDCOrapid and PiCCOplus preload response parameter validation study. Proceedings of 31st International Symposium on Intensive Care and Emergency Medicine. 2011;(Suppl 1):P62 doi:10.1186/cc9481
6. Hadian M, Severyn D, Pinsky M. The effects of vasoactive drugs on pulse pressure and stroke volume variation in postoperative ventilated patients. J Critical Care. 2010;(26)3:328.e1-8.
7. Wyffels P, Sergeant P, Wouters P. The value of pulse pressure and stroke volume variation as predictors of fluid responsiveness during open chest surgery. Anaesthesia. 2010;65:704-709
8. Marquez J, McCurry K, Severyn D, Pinsky M. Ability of Pulse Power, Esophageal Doppler and Arterial Pulse Pressure to Estimate Rapid Changes in Stroke Volume in Humans. Crit Care Med. 2008;36(11)3001-3007.
9. Dizon J, Quinn TA, Cabreriza S, Wang D, Spotnitz H, Hickey K, Garan H. Real-time Stroke Volume Measurements for the Optimization of Biventricular Pacing Parameters. Europace. 2010;12(9):1270-4.
10. Richard K, Novak M, Quill T, Cannesson M, Koff M. Functional Hemodynamics during High-Risk Abdominal Surgery: Are All Monitors Created Equal? Presentation A997 at the ASA, 2010 San Diego
11. Avery S, Mills E. Jonas M, Margarson M. PulseCO derived stroke volume variation for prediction of fluid responsiveness in the morbidly obese. Presentation A996 at the ASA, 2010 San Diego