Many readers may now be familiar with the new ASA practice guidelines for monitoring and antagonism of neuromuscular blockade that were published this past January (Anesthesiology 2023;138:13-41). For those who are not, this article may serve as a brief overview of the advances made in neuromuscular monitoring in recent years and the considerations of practical application to general anesthesia practices.

In terms of monitoring neuromuscular blockade, train-of-four qualitative peripheral nerve stimulators have been in regular use since the 1970s. In general, these devices are deceptively user-friendly and easy to place on patients, requiring just two electrodes. By measuring the patient’s response to four brief electrical impulses, a level of blockade can be roughly estimated. Major drawbacks to this technique include varying degrees of accuracy based on placement location and the subjective nature of measuring twitches themselves. Residual neuromuscular blockade observed in the postanesthesia care unit (PACU) can be significant and experienced by many patients (Anesth Analg 2015;121:366-72).

Quantitative twitch monitoring using acceleromyography or electromyography is one solution to this issue. It has become more prevalent given recent technological advances and market competition. These monitors provide instant objective feedback on the depth of neuromuscular blockade to the anesthesia provider. There have been multiple studies citing that a train-of-four ratio equal to or greater than 90% is required to ensure adequate neuromuscular reversal for extubation. The use of qualitative twitch monitors makes it impossible to achieve this on a consistent basis, leading to the increased risk of complications postoperatively. These complications can include poor patient experience, increased PACU recovery times, postoperative pulmonary complication, and ICU admissions (Anesthesiology 1997;86:765-71; Br J Anaesth 2010;105:304-9; Br J Anaesth 2020;124:63-72; Anesth Analg 2014;119:323-31). Given this information, one may subsequently ask why aren’t more anesthesiologists using quantitative twitch monitoring?

The answer to this question is much more challenging. The old adage of “change takes time” cannot be overstated, and adoption of new medical equipment can take upward of 10 to 15 years. Cost is one major barrier to the use of quantitative twitch monitoring. Depending on the device company, each setup can cost thousands of dollars per anesthetizing location, not to mention ongoing increased costs of special arrays/electrodes that must be used for each new patient. In a time of compromised hospital margins due to the COVID-19 pandemic, increased labor wages, and decreased reimbursement (i.e., Medicare’s 2% cut for anesthesia reimbursement), convincing those who control monetary funds for capital upgrades has become harder and harder. Secondly, there is a general misconception that the status quo of qualitative twitch monitoring works just fine and there is no need for upgrading to a more expensive piece of equipment. Others may say that the availability of sugammadex has eliminated the need for precise neuromuscular monitoring, which would be a false assumption ( Literature has demonstrated that despite the use of sugammadex, patients still had inadequate neuromuscular blockade reversal (Br J Anaesth 2020;124:553-61).

The biggest challenge to quantitative neuromuscular monitoring conversion beyond equipment acquisition may be consistent usage by anesthesia providers once the proper equipment has been obtained. There are two very good articles about this exact challenge – the first being by Todd et al. and the second by Weigel et al. (Anesth Analg 2014;119:323-31; Anesthesiology 2022;136:901-15). Todd demonstrated that in a large academic setting, it takes extensive effort in the form of education and re-education to promote a change to quantitative twitch monitoring (as referenced by the paper, at least one year). Following successful implantation, they reduced the number of reintubations in the PACU from two a year to four a year, and to zero in the subsequent year. Interestingly, in a follow-up article published by Todd et al. a year later, they experienced two reintubations from the time the above article was accepted to the time it was published (Anesth Analg 2015;121:836-8). Both involved cases where quantitative monitoring was not successfully utilized.

The article published by Weigel et al. was excellent in that it provided a roadmap for implementation expectations but also clear benefits of using quantitative monitoring. Again, in a medium to large academic setting, conversion to quantitative monitoring took time and extensive educational resources, and even the threat of punishment was required (quantitative neuromuscular monitoring adherence was added to their ongoing professional practice evaluations) to achieve over 90% compliance with use of the monitoring equipment. Observed benefits from this conversion included decreased postoperative pulmonary complications and decreased hospital length of stay. Those findings, along with several other studies that found reduction in complications, are key to justifying the initial capital purchase costs to administrators. Lower complications and decreased hospital length of stays not only benefit the patient, they benefit the hospital’s bottom line as well.

Personal experiences at our institutions couldn’t emphasize enough the importance of a solid educational plan and constant practice reinforcement when implementing quantitative twitch monitoring. Whatever equipment you choose will have a learning curve. Leadership of this initiative starts with the anesthesiologist and the willingness to take that extra step at the beginning of the case to ensure that the quantitative twitch monitor is set up and ready for use, just like the blood pressure, EKG, and pulse oximetry monitors. We as a profession strive to keep our patients safe and improve outcomes. Quantitative twitch monitoring can be a key instrument to realizing the above statement. If you are at an institution that already uses quantitative twitch monitoring, pat yourself on the back. You’re ahead of the curve.