Most clinicians use logic, experience, and intuition to avoid both unwarranted bolus infusions and refrain from providing excess fluid. Low SV and a marked decrease in SV since the last bolus infusion are among the most common advanced indications that fluid should be given. Our analysis shows that advanced haemodynamic parameters can be used to further refine the clinical decision of whether a bolus infusion should be administered during major surgery.
The present analysis explored how useful such haemodynamic indications are when major surgery involves EDM and pulse oximetry. The results showed that these variables can serve as adjuncts to clinical decisions of whether fluid should be given, although they proved to be only moderately helpful. Specifically, consideration of advanced haemodynamic parameters can help clinicians increase the precision of providing a bolus infusion to the right patient within a range of 20–70%.
The present results show that the likelihood of a patient being fluid-responsive was reduced from the overall likelihood of 44% to 30–35% by considering SV and FTc values above the cut-offs suggested by ROC curves. The likelihood of fluid responsiveness could be further reduced by 10% by applying tougher cut-off values. A limited decrease in SV since the previous optimisation round had the same negative predictive power as the raised cut-off for FTc (> 390 ms). By considering these cut-offs, anesthetists could reduce the risk of providing a bolus infusion that later would prove not to be warranted from 44% to 21–25%. However, the only strengthening of this prediction by combining variables consisted of considering both ΔSV and the raised cut-off for SV. Applying cut-offs on the opposite side of the haemodynamic spectrum increased the chance of providing warranted bolus infusions. In general, the results on the “recommending” side mirrored the “avoiding” side, but combining variables was somewhat more useful for recommending a bolus infusion.
A surprising finding was that the SVI was the same in non-responders and responders before an infusion was given (Table 1). The modest difference in SV between these groups might then only be due to the body size of the patients. Hence, cardiac capacity rather than hypovolemia could be the major determinant of who would be fluid responsive. More precise indications of fluid responsiveness by the haemodynamic variables would probably be given if young patients with blood loss had been studied.
The statistical correlation between cardiac output and body surface is limited, and not superior to the correlation between cardiac output and body weight (Guyton 1973). There are several methods for calculation of the body surface area that may give quite different results (Redlarski et al 2016). The CardioQ device calculates SVI using the Du Bois equation (Du Bois and Du Bois, 1916) but these values were not recorded. In retrospect, we calculated the body surface area according to both de Bois equation and an alternative equation (Mosteller 1987). However, the choice of equation had hardly any influence of the difference in SVI between responders and non-responders (data not shown).
A 10% decrease in SV is a common trigger for initiating a new optimisation round in many GDFT algorithms. However, we and others have described its limited performance in aiding this decision making (Davies et al 2013, Bahlmann et al 2019). Contrary to what is usually assumed, maximal or optimal SV may not always be constant throughout a surgical procedure.
FTc is a variable that several authors have found useful as an indicator of fluid responsiveness (Monnet et al 2005, Sinclair et al 1997), but it might be a better measure of afterload by being inversely proportional to systemic vascular resistance (Singer 2006). In our present evaluation, we found FTc to be a modestly good indicator of fluid responsiveness by increasing the likelihood by almost 10%, which is comparable to SV ≤ 80 mL. Moreover, high FTc values were more effective in precluding fluid responsiveness than low FTc values.
Pulse oximeters that report PVI values may indicate fluid responsiveness as well (Cannesson et al 2008, Forget et al 2010), but this approach has not reached widespread acceptance. Indeed, we previously found poor concordance between EDM and PVI (Bahlmann et al 2016). Our present evaluation confirmed that PVI reduces the likelihood of fluid responsiveness to 38% but increases it up to 53% depending on whether the PVI value is lower or higher than 10%. These predictions only marginally changed by applying other cut-off values (data not shown).
Pulse oximetry could also augment indications given by EDM by increasing the likelihood of a fluid bolus being warranted, which has rarely been reported previously. Deng et al. reported a meta-analysis showing such improved performance by using a combination of dynamic GDFT (e.g., PVI) and CO/CI goals compared to using only dynamic GDFT goals (Deng et al 2018). Together, these data support the idea that the evaluation of multiple parameters instead of one may offer some benefit when making decisions about whether to administer fluid.
The ROC curves showed poor discriminative ability of advanced haemodynamic variables to indicate fluid responsiveness before an infusion is given. However, the ROC curves expressed how many warranted and not warranted infusions were indicated as haemodynamic variable ranges, while the likelihood calculations compared the incidence of responsiveness within an already predetermined haemodynamic range.
One limitation of this report is that it represents a retrospective analysis of a prospective study. This implies that the findings may need to be confirmed in a separate population.
In conclusion, observing advanced haemodynamic values before infusing fluid during major abdominal surgery could decrease or refine the prediction of whether a patient is fluid-responsive by 20–25%. Further improvement could be obtained by using combinations of the variables considered in these predictions.