ICU Management & Practice, Volume 19 - Issue 4, Winter 2019/2020

The Future of Haemodynamic Monitoring: From Planet Mars to Resource Limited Countries

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When envisioning the future of haemodynamic monitoring, we cannot limit the discussion to new sensors and computer innovations. We also need to consider the accessibility to scientific and technological progress, particularly in resource-limited countries where a large number of patients deserve more rational haemodynamic management.

The growing number of publications regarding new biomaterials, non-invasive sensors and artificial intelligence hold promises for the future of haemodynamic monitoring. In the first part of this article, we will briefly describe innovations that may become available soon in high-income countries and flagship hospitals. It is worth noting that recent surveys and audits have shown that the adoption of existing haemodynamic monitoring techniques is far from optimal, and that one of the key reasons is economic. Therefore, when discussing the future of haemodynamic monitoring we also have to consider that more patients from more countries need to have access to scientific and technological progress. In the second part of the manuscript, we will discuss alternatives to premium haemodynamic solutions, and how they could help rationalise haemodynamic management in resource-limited hospitals and countries.

The Future of Haemodynamic Monitoring in a Perfect World With Unlimited Resources


Let us imagine that we are in 2040 visiting a brand-new hospital built for the first human colony on planet Mars. This hospital would have been developed by an international consortium with virtually unlimited resources and would integrate the most recent medical innovations available on Mother Earth. The ICU would be a very quiet place where alarms would have been excluded from patient rooms (why bother patients with alarms?). Alarms would be seen or heard or felt (haptic signal) exclusively by caregivers at central monitoring stations, or on mobile or wrist devices. Patients would be continuously monitored with wearable sensors (aka electronic tattoos: youtube.com/watch?v=4oeFBGFzcrg). Some of these tiny, flexible and non-invasive sensors would be able to feel our carotid or femoral pulse and record high quality central blood pressure waveforms, from which blood flow information (e.g. stroke volume and cardiac output) would be derived by smart pulse contour algorithms (Michard 2016). Specific sensors would continuously monitor tissue perfusion and oxygenation, when not directly mitochondrial oxygen consumption (Vincent et al. 2017). Other adhesive skin sensors or biostamps would enable measurement of lactates, electrolytes and metabolites in sweat or interstitial fluid (of course, by 2040, clinical studies would have clarified the meaning and kinetics of these measurements).

Many of the above-mentioned sensors would be part of ergonomic monitoring tools such as helmets, shirts, belts, bracelets, gloves or rings worn by patients (Michard et al. 2017a). Data would be transmitted wirelessly to computers and artificial intelligence systems able to filter artefacts, fuse parameters together and predict most adverse events before they actually occur (Pinsky 2016; Michard and Teboul 2019). Decision support systems would constantly help clinicians to think proactively, to make the right therapeutic decisions and to minimise drug side effects (Michard 2013). The use of central venous catheters would belong to the past, as well as their associated thrombotic, haemorrhagic and infectious complications (Vincent et al. 2018). Blood samples would be very small (the size of a blood drop) to prevent iatrogenic anaemia. When needed, larger blood samples would be obtained by robots using infra-red transcutaneous illumination and colour Doppler guidance (veebot.com/solutions.html) to improve safety, efficiency and decrease nurse workload. Electrical impedance tomography (EIT), routinely used for visual and functional lung monitoring, could also be useful to monitor stroke volume, cardiac output and pulmonary artery pressures (Braun et al. 2018). All doctors would have an echo probe in their pocket to augment clinical examination (Figure 1). High-end echo machines would only be used from time to time for detailed examination and when precise measurements would be necessary. These measurements would be greatly facilitated by smart systems recognising heart structures and movements and helping clinicians to properly position the probe.



The Future of Haemodynamic Monitoring in Resource-Limited Countries


In many hospitals and in many countries, what we envisioned for the flagship hospital on Mars will never be implemented for several reasons that include lack of awareness, lack of training and of course lack of resources. However, hypovolaemic, septic and cardiogenic shocks will likely remain a reality for millions of patients and thousands of caregivers working in resource-limited settings. In the following paragraphs, we describe existing and future solutions to improve the quality of care of patients with haemodynamic instability without necessarily increasing costs.

Predicting Fluid Responsiveness

Predicting fluid responsiveness is useful to rationalise fluid therapy. It helps to identify patients who may benefit from fluid administration and, perhaps more importantly, to prevent unjustified fluid administration in fluid non-responders. In emergency departments and intensive care units, the applicability of dynamic predictors of fluid responsiveness such as pulse pressure variation (PPV) is limited (Michard et al. 2015). Therefore, recommended methods to predict fluid responsiveness include the assessment of changes in stroke volume during a passive leg raising manoeuvre, an end-expiratory occlusion test, a lung recruitment manoeuvre or simply during a fluid challenge (Michard and Biais 2019). The main limiting factor to the clinical adoption of these methods is the availability of a cardiac output monitor to quantify stroke volume changes. In this regard, several alternative methods have been proposed to predict fluid responsiveness (Figure 2). For instance, the decrease in PPV during a fluid challenge has proved to be proportional to the increase in cardiac output (Michard et al. 2000; Mallat et al. 2015). In other words, changes in PPV can be used as a surrogate for assessing changes in stroke volume or cardiac output during fluid administration. Similarly, the rise in PPV during a transient increase in tidal volume (e.g. from 6 to 8 ml/kg) has been shown to be useful to predict fluid responsiveness with high sensitivity and specificity (Myatra et al. 2017; Messina et al. 2019). Additionally, in patients who do not have an arterial catheter in place, pulse oximeters have recently been proposed to track changes in peripheral perfusion index (PI). Beurton et al. showed that changes in PI are proportional to changes in cardiac output during passive leg raising manoeuvres and able to predict fluid responsiveness with acceptable sensitivity and specificity (Beurton et al. 2019). De Courson et al. recently made the same observation during lung recruitment manoeuvres: most patients who experienced a dramatic decrease in PI during a recruitment manoeuvre were fluid responders, whereas patients who did not, were fluid non-responders (De Courson et al. 2019).



Goal-Directed Fluid Therapy in High-Risk Surgical Patients

Most patients undergoing major surgery have an arterial line in place for continuous monitoring of blood pressure and blood samples. General anaesthesia with mechanical ventilation is also the rule in this context. In addition, atrial fibrillation, right ventricular failure, and decreased lung compliance are far less common in patients undergoing elective surgery than in critically ill patients. Protective mechanical ventilation is often described as a potential obstacle to the use of PPV. But it is only the case when very low tidal volumes are used (e.g. 6 ml/kg). If outcome clinical studies have shown that using a tidal volume of 6-8 ml/kg is better than of 10-12 ml/kg, until today there is no evidence than 6 is better than 8 ml/kg (Futier et al. 2013). Actually, a large observational study done in >29,000 patients from the UK suggested that the ideal tidal volume for surgical patients is around 8-9 ml/kg (Levin et al. 2014) and such a tidal volume is ideal to use PPV as a marker of fluid responsiveness. In summary, PPV can be used to rationalise fluid therapy in a large number of patients undergoing major surgery. Lopes et al. were the first to show a dramatic decrease in postoperative complications and hospital length of stay when using PPV to guide fluid therapy in a resource-limited setting (Lopes et al. 2007). Their pilot findings have been confirmed by several more recent clinical studies (Benes et al. 2014).

When cardiac output monitoring is a requirement to predict fluid responsiveness (e.g. when PPV cannot be used), recent studies have shown that pulse contour methods are the preferred choice of anaesthesiologists (Ahmad et al. 2015). However, despite the large number of studies demonstrating the clinical value of pulse contour methods in surgical patients (Michard et al. 2017b), surveys and audits have shown that their adoption remains poor (Molliex et al. 2019). Most of these methods require the use of a disposable sensor, which is likely to double or triple the average cost of anaesthesia (around 100 euros in Europe). The onus of monitoring equipment has to be balanced with the potential savings related to the expected reduction in postoperative morbidity and length of stay. However, upfront investment in monitoring techniques is often a barrier to hospital purchase and clinical adoption. In addition, only a few hospitals have perioperative medicine departments and associated budgets. In most hospitals, anaesthesia departments have to pay for monitoring technologies used by anaesthesiologists, whereas the clinical benefits and associated savings are for the surgical departments. A solution may come from innovative business models recently proposed by several companies that, instead of charging for a single-use-sensor-per-patient, developed sensor-free pulse contour methods. The arterial pressure waveform is simply slaved from the bedside monitor towards a dedicated monitor or computer containing the pulse waveform analysis software. These companies usually charge hospitals a flat fee, that depends on the number of monitors they need, but not on the number of patients they treat. As a result, it gives clinicians the freedom to monitor as many patients as they want without increasing hospital costs (Figure 2).

In the future, one may also expect that bedside monitoring companies will develop or simply acquire existing pulse contour algorithms (Michard et al. 2019a). By doing so they will be able to offer cardiac output as a novel vital sign for all patients in whom a continuous BP waveform is recorded, either invasively from a radial catheter, or non-invasively from a volume clamp or tonometric sensor. Another option would be the improvement of methods based on the analysis of expired carbon dioxide (Peyton et al. 2019). These methods would have strong potential for wide clinical adoption if they were integrated into anaesthesia machines.

Assessment of Cardiac Function

Echocardiography is gold standard for the bedside assessment of cardiac function in critically ill patients. Pocket echo probes are now available and have the potential to replace the stethoscope in the pocket of many clinicians, in the ICU and beyond (Figure 1). Although miniaturised, these tools have proven to be useful for a qualitative (e.g. pericardial effusion, right ventricular dilation, left ventricular dysfunction) or even quantitative assessment of cardiac function (e.g. estimation of left ventricular ejection fraction or inferior vena cava variations) (Biais et al. 2012, Liebo et al. 2011). Given their relatively low cost (as compared to high-end ultrasound machines), these pocket echo devices have the potential to be accessible to resource-limited countries and should help to increase the number of patients with shock who may benefit from quick ultrasound evaluations and rational haemodynamic management (Michard et al. 2019b).

Conclusion


Given the number of hardware and software innovations coming to market, the future of haemodynamic monitoring should be nothing but bright. However, the clinical adoption of existing solutions is somewhat concerning, with a minority of patients benefiting today from haemodynamic monitoring tools. In a medical world with increasing economic constraints, in parallel to the exciting development of technical and digital innovations, we must find ways to improve the accessibility of monitoring solutions to more patients and in more countries.

Key Points


  • Haemodynamic monitoring systems enable the rationalisation of haemodynamic therapy. Multiple studies have reported clinical benefits, particularly in patients undergoing high risk surgery.
  • The clinical adoption of existing monitoring solutions remains low. The main barrier to wider adoption is the cost of single-use sensors.
  • In many patients undergoing high-risk surgery under general anaesthesia, the conditions are met in order to use pulse pressure variation (PPV) to predict fluid responsiveness and rationalise fluid administration.
  • In most patients, tracking changes in PPV can be used to detect changes in stroke volume and cardiac output during fluid challenges.
  • Tracking changes in perfusion index (PI) may also have value to detect changes in stroke volume and cardiac output during passive leg raising and lung recruitment manoeuvres.
  • The adoption of modern and affordable solutions for cardiac output monitoring should further help to ensure that more patients from more countries can benefit from rational haemodynamic management.

Disclosure

Frederic Michard (FM) is the founder and managing director of MiCo Sàrl, a Swiss consulting firm. MiCo does not sell any medical device and FM does not own any shares from any medtech company.


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References:

Ahmad T, Beilstein CM, Aldecoa C et al. (2015) Variation in haemodynamic monitoring for major surgery in European nations: secondary analysis of the EuSOS dataset. Perioper Med (Lond) 4:8.

Benes J, Giglio M, Brienza N, Michard F (2014) The effects of goal-directed fluid therapy based on dynamic parameters on post-surgical outcome: a meta-analysis of randomized controlled trials. Crit Care 18:584.

Beurton A, Teboul JL, Gavelli F et al. (2019) The effects of passive leg raising may be detected by the plethysmographic oxygen saturation signal in critically ill patients. Crit Care 23:19.

Biais M, Carrie C, Delaunay F et al. (2012) Evaluation of a new pocket echoscopic device for focused cardiac ultrasonography in an emergency setting. Crit Care 16:R82.

Braun F, Proenca M, Adler A et al. (2018) Accuracy and reliability of noninvasive stroke volume monitoring via ECG-gated 3D electrical impedance tomography in healthy volunteers. PLoS One 13:e0191870.

De Courson H, Biais M, Chavignier C et al. (2019) Do changes in perfusion index (deltaPI) reflect changes in stroke volume (deltaSV) during preload-modifying maneuvers? Eur J Anaesth 59:e-Supplement 57.

Futier E, Constantin JM, Paugam-Burtz C et al. (2013) A trial of intraoperative low-tidal-volume ventilation in abdominal surgery. N Engl J Med 369:428-37.

Levin MA, McCormick PJ, Lin HM et al. (2014) Low intraoperative tidal volume ventilation with minimal PEEP is associated with increased mortality. Br J Anaesth 113:97-108.

Liebo MJ, Israel RL, Lillie EO et al. (2011) Is pocket mobile echoardiography the next generation stethoscope? A cross-sectional comparison of rapidly acquired images with standard transthoracic echocardiography. Ann Intern Med 155:33-8.

Lopes MR, Oliveira MA, Pereira VO et al (2007) Goal-directed fluid management based on pulse pessure variation monitoring during high-risk surgery: a pilot randomized controlled trial. Crit Care 2007; 11:R100.

Mallat J, Meddour M, Durville E et al. (2015) Decrease in pulse pressure and stroke volume variations after mini-fluid challenge accurately predicts fluid responsiveness. Br J Anaesth 115:449-56.

Messina A, Montagnini L, Cammarota G et al. (2019) Tidal volume challenge to predict fluid responsiveness in the operating room: an observational study. Eur J Anaesthesiol 36:583-591.

Michard F, Boussat S, Chemla D et al. (2000) Relationship between respiratory changes in arterial pulse pressure and fluid responsiveness in septic patients with acute circulatory failure. Am J Respir Crit Care Med 162:134-8.

Michard F (2013) Decision support for hemodynamic management: from graphical displays to closed loop systems. Anesth Analg 117:876-82.

Michard F, Chemla D, Teboul JL (2015) Applicability of pulse pressure variation: how many shades of grey? Crit Care 19:144

Michard F (2016) Hemodynamic monitoring in the era of digital health. Ann Intensive Care 2016; 6:15.

Michard F, Pinsky MR, Vincent JL (2017a) Intensive care medicine in 2050: NEWS for hemodynamic monitoring. Intensive Care Med 43:440-2.

Michard F, Giglio MT, Brienza N (2017b) Perioperative goal-directed therapy with uncalibrated pulse contour methods: impact on fluid management and postoperative outcome. Br J Anaesth 119:22-30.

Michard F, Biais M (2019) Predicting fluid responsiveness: time for automation. Crit Care Med 47:618-620.

Michard F, Teboul JL (2019) Predictive analytics: Beyond the buzz. Ann Intensive Care 9:46.

Michard F, Biais M, Lobo SM, Futier E (2019a) Perioperative hemodynamic management 4.0. Best Pract Res Clin Anaesthesiol 33:247-255.

Michard F, Barrachina B, Schoetkker P (2019b) Is your smartphone the future of physiologic monitoring? Intensive Care Med 45:869-71.

Molliex S, Passot S, Morel J, et al. (2019) A multicentre observational study on management of general anaesthesia in elderly patients at high-risk of postoperative adverse outcomes. Anaesth Crit Care Pain Med 38:15-23.

Myatra SN, Prabu NR, Divatia JV et al. (2017) The changes in pulse pressure variation or stroke volume variation after a “tidal volume challenge” reliably predict fluid responsiveness during low tidal volume ventilation. Crit Care Med 45:415-21

Peyton PJ, Wallin M, Hallback M (2019) New generation continuous cardiac output monitoring from carbon dioxide elimination. BMC Anesthesiol 19:28.

Pinsky MR, Clermont G, Hravnak M (2016) Predicting cardiorespiratory instability. Crit Care 20:70

Vincent JL, Slutsky A, Gattinoni L (2017) Intensive care medicine in 2050: the future of ICU treatments. Intensive Care Med 43:1401-2.

Vincent JL, Michard F, Saugel B (2018) Intensive care medicine in 2050: towards critical care without central lines. Intensive Care Med 44:922-924.



Haemodynamic monitoring, Future ICU, non-invasive sensor, predictive analysis, resource-limited countries, middle income countries An overview of existing and future solutions to improve the quality of care of patients with haemodynamic instability without increasing costs.

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