A REVIEW OF FUNCTIONAL HAEMODYNAMIC MONITORING AJ van den Berg

Definition  The assessment of the dynamic interactions of haemodynamic variables in response to a defined intervention.

Goals  To use proactive interventions to create parameters of robust sensitivity and specificity  To monitor and identify cardiovascular insufficiency, volume responsiveness and vasomotor tone  To define end-points to guide early goal-directed therapy

Predicting Volume Responsiveness  Defined as at least a 15% increase in Cardiac Output following a 500ml bolus.  During positive pressure ventilation, various measures have been found to be good indicators of volume responsiveness  Pulse Pressure Variation (PPV)  Left Ventricular Stroke Volume Variation (SVV)  Systolic Pressure Variation  Change in inferior and superior vena cavae diameters

Predicting Volume Responsiveness  SVV > 10% or PPV > 13-15% on a tidal volume of 8ml/kg highly predictive of volume responsiveness  Problems:  Influenced by tidal volume, chest wall compliance and contractility  In the presence of spontaneous breathing or irregular heartbeats, PPV and SVV become inaccurate

Predicting Volume Responsiveness  Problems (continued)  Ventilation with low tidal volumes the cyclical changes in flow are dependent on changes in intra- thoracic pressures Tidal volume is a major determinant of intrathoracic pressure and therefore needs to be great enough to alter central venous pressure Tidal volumes of 6 ml/kg alter the sensitivity but not the specificity of these parameters  Intra-abdominal Hypertension Reduced chest wall compliance PPV and SVV remain reliable if tidal volume is maintained Passive Leg Raise (PLR) has reduced sensitivity

Predicting Volume Responsiveness  Marik et al (2013):  cardiac output measured by bioreactance, cerebral blood flow measured by carotid Doppler in 34 critically ill patients.  Volume responsiveness assessed by PLR induced changes in stroke volume index (SVI)  PLR had a sensitivity of 94% and a specificity of 100% for predicitng volume responsiveness

Predicting Volume Responsiveness  Marik et al (continued):  Carotid blood flow increased by 79±32% in fluid responders, compared to 0.1±14% in non-responders (P < )  If carotid blood flow was used as an estimate of volume responders, a value of 20% seperated responders from non-responders with a sensitivity of 94% and a specificity of 86%.

Predicting Volume Responsiveness  Improved assessment of fluid responsiveness  Study by Lopes  High-risk surgery patients  Volume loading guided by PPV minimisation  Improved postoperative outcome,  decreased length of hospital stay,  lower duration of mechanical ventilation,  lower length of stay in ICU

Assessing Arterial Tone  Dynamic central arterial elastance (Ea)  If the arterial circuit becomes stiffer, then for the same stroke volume change, there will be a larger pulse pressure change  Ea = PPV/SVV

Assessing Arterial Tone

 Monge et al (2011)  Assessed the effect of volume loading in hypotensive septic shock patients who’s PPV indicated that they were volume responsive  All patients increased cardiac output  Only patients with normal or increased Ea increased their arterial pressure  Only the PPV/SVV (Ea) slope predicted responders from non-responders  Ea < 0.9 reflects a severely vasodilated state

Identifying Cardiovascular Insufficiency  Inadequate oxygen delivery relative to metabolic demands  In compensated shock, arterial pressure and cardiac output are often within normal ranges  Therefore insensitive as early predictors of decompensation  Microcirculatory changes already occur  Tissue cardiovascular reserve should therefore be a sensitive early warning sign

 Near-infrared spectroscopy has used to evaluate tissue oxygen saturation (StO2)  A dynamic ischaemic challenge (vascular occlusion test) improves the ability of StO2 to identify tissue hypoperfusion  Deoxygenation rate reflects local metabolic rate  Reoxygenation rate reflects local cardiovascular reserve and microcirculatory flow Identifying Cardiovascular Insufficiency

 Study comparing septic patients to haemodynamically stable non-septic patients  Reoxygenation rate lower in septic patients  Reoxygenation rates were higher in survivors  Reoxygenation rates tended to increase during resuscitation in survivors but not in nonsurvivors  The reoxygenation slope was found to be a good predictor of ICU death (cut-off value 2.55%/s, sensitivity 85%, specificity 73%) Identifying Cardiovascular Insufficiency

 Reoxygenation rate is related more to the severity of the sepsis than to MAP or vasopressor dose  Other studies:  Reoxygenation rate predicted organ failure as well as failure of SBT’s  In acute trauma patients, when lactate > 1.7, reoxygenation rate was 100% specific for patients in need of life-saving intervention Identifying Cardiovascular Insufficiency

References  Pinsky MR. Functional Haemodynamic Monitoring. Curr Opin Crit Care 2014; 20:  Lopes RL, Oliveira MA, Pereira VOS, et al. Goal-directed fluid management based on pulse pressure variation monitoring during high-risk surgery: a pilot randomized controlled trial. Crit Care 2007; 11:R100.  Marik PE, Levitov A, Young A, Andrews L. The use of bioreactance and carotid doppler to determine volume responsiveness and blood flow redistribution following passive leg raising in hemodynamically unstable patients. Chest 2013; 143:364– 370.  Monge MI, Gil A, Garcia RM. Dynamic arterial elastance to predict arterial pressure response to volume loading in preload-dependent patients. Crit Care 2011; 15:R15.  Giraud R, Slegenthaler N, Bendjelid K. Pulse pressure variation, stroke volume variation and dynamic arterial elastance. Crit Care 2011; 15:414.  Creteur J, Carollo T, Soldati G, et al. The prognostic value of muscle StO2 in septic patients. Intensive Care Med 2007; 33:1549–1556.