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Record W1973906578 · doi:10.1213/ane.0000000000000310

A Twitch in Time

2014· letter· en· W1973906578 on OpenAlexaff
Richard P. Dutton, François Donati

Bibliographic record

VenueAnesthesia & Analgesia · 2014
Typeletter
Languageen
FieldMedicine
TopicAnesthesia and Sedative Agents
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHarmMedicineCurarePerioperativeDo no harmPatient safetyMortality rateMedical emergencyAnesthesiaSurgeryLawPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

Primum non nocere is the first thing taught in medical schools, the motto of our profession. Yet, as anesthesiologists we are conflicted every day by the concept of “first, do no harm.” We start IV lines to administer potent, and potentially poisonous, medications to our patients, and we take away both respiratory and cardiovascular control. We instrument airways and block nerves and scramble memories. All in pursuit of a greater good: that the patient will survive the even more substantial invasions of the surgeon. In recognition of this central paradox of our existence, anesthesiologists have ever been at the forefront of promoting patient safety. Todd et al.,1 writing in this issue of Anesthesia & Analgesia, present another chapter in this illustrious history. In 1954, Beecher and Todd2 published a landmark paper on mortality in the perioperative period, based on 599,548 anesthetics collected from 10 academic hospitals over 6 years. This study, a precursor of today’s “big data,” found an overall mortality of >1 in 2000 patients but noted a rate of 1 in 370 when curare was used for muscle relaxation. Their conclusion: “There seems to be an important increase in ‘anesthesia death rate’ when the muscle relaxants are added to the situation.” The work of Beecher and Todd2 identified an important patient safety risk, suggested solutions, and urged the profession to do better. In the 6 decades since that time, we have made enormous improvements in patient safety, but the work is not yet done. Spurred by an ongoing patient safety problem in their institution, 2 to 4 unplanned reintubations per year in their postanesthesia care unit (PACU) attributed to inadequate reversal of neuromuscular blockade, Dr. Michael Todd (former Editor-in-Chief of Anesthesiology) undertook an effort to improve. The first step was installation of a state-of-the-art quantitative neuromuscular blockade monitor in every operating room accompanied by an extensive educational effort targeted to every provider in the department. As so often happens, however, their proposed change in policy ran afoul of the entrenched inertia of institutional culture. Six months later, the unplanned reintubations were still occurring and a spot audit revealed that the new monitors were used in <50% of cases. The goal of their present report was to describe the process by which this problem was addressed. The authors began, as all such projects should, by gathering data; they decided not to look at adherence to the new rules but rather at outcomes directly related to the problem. In other words, the focus was not on the use of nerve stimulators but on residual blockade in the PACU. The literature suggests strongly that the risk of complications and patient discomfort from residual neuromuscular blockade increase sharply if the measured train-of-four ratio (TOF ratio) is <0.9,3–5 so the first step in the investigation by Todd et al.1 was to use their quantitative monitoring system in patients who newly arrived to the PACU. They documented a 31% rate of inadequate reversal (TOF ratio <0.9), with half of these patients <0.8 and a handful <0.5. These results are not very different from those reported in various clinical studies (approximately 40% of patients with residual blockade).3,6 Had a previous assessment been made a year earlier, the situation might have been worse. These results were presented to the department, along with pointed discussion of the patients who required reintubation. Subsequent audits demonstrated gradual improvement in these numbers over the next 2 years: 16 months after the initial evaluation, residual blockade was seen in only 15% of cases, and this improvement was sustained 6 months later (17% inadequate reversal). The authors report a subsequent 2 years with no further PACU reintubations attributable to inadequate reversal of blockade. Over the past 3 decades, a compelling body of evidence has accumulated, showing that clinically significant residual neuromuscular blockade (1) may occur when TOF ratio at the adductor pollicis is <0.93–5; (2) may go unnoticed using clinical signs alone3,7; and (3) may be missed by peripheral nerve stimulators when the response is seen or felt.4,7 The obvious response to these consistent literature findings would be to use quantitative neuromuscular monitoring on a routine basis, but as Todd et al.1 show, this is more easily said than done. One of the problems is making neuromuscular monitoring a habit. At the start of their study, a variety of quantitative and qualitative nerve stimulations were available from the anesthesia workroom. No doubt, having equipment in a faraway location was a disincentive. Acceptance improved once a unit was readily available in each anesthetic location. The other problem to overcome was to teach providers how to use the new monitoring units. Broadly speaking, commercially available quantitative neuromuscular monitors depend on 1 of the 3 theories of operation: acceleromyography, kinemyography, or electromyography (EMG), each with its own characteristics.4 As a result, each monitor type has to be handled in a different way. The acceleromyography sensor can be placed on the thumb relatively easily, but the unit needs to be handled carefully, requires a stable and free thumb to function properly, and cannot be interfaced with most anesthesia information management systems (AIMSs). When measuring deformation of a piezoelectric sensor shaped as a strip placed between the thumb and the index finger (kinemyography), an AIMS interface is possible. However, the system is sensitive to hand positioning, and frequent users often complain of malfunction after months of use. Todd et al.1 decided to use EMG units instead, which were interfaced with their particular AIMS. An additional advantage of the technique is reduced sensitivity to hand displacement. However, correct application of the electrodes is a must, and recordings are influenced by electrical interference caused by electrocautery. The use of neuromuscular monitoring has always been seen as a personal decision, just as the choice of any drug or airway device is made by the anesthesiologist to suit the patient’s needs. The story told by Todd et al.1 suggests that neuromuscular monitoring might be implemented as department policy, and strong leadership is likely to influence not only practice but outcome as well. All existing quantitative monitoring systems have their flaws; however, only 1 device was adopted for all operating rooms, thus increasing the chance that all providers would become familiar with it. In addition, the team decided to display the raw EMG signal, which required a technical modification of the units, with the expected benefit of closing the gap between data acquisition and interpretation. The advantages of seeing the original signal also applies to pulse oximetry, and we have learned over the years to look at the curve before interpreting the number. It is unfortunate that manufacturers of quantitative neuromuscular monitoring systems chose to display only numbers. Todd et al.1 showed that it was worth going through the trouble of restoring the initial signal. The Anesthesia Patient Safety Foundation (APSF) was founded in 1985 with the purpose “that no patient shall be harmed by anesthesia.”a Since then, the volunteer members of APSF have worked tirelessly to identify, analyze, and eliminate risks to our patients. The work of the APSF has encompassed physical solutions (e.g., gas-specific fittings for the hoses of our anesthesia machines), education (the recent video on operating room fire safety), and even cognition (a 2013 conference on how to train providers in the use of technology). The safe use of neuromuscular blocking medications, including assessment of adequate reversal before extubation, is a long-standing theme. Todd et al.1 have provided further evidence of the importance of this issue, illustrated with comparative effectiveness research in their own practice, and reached the noteworthy conclusion that this risk can be completely avoided, if a sufficient effort is put forward. While technology was important to their efforts, the real key was the ability to change department culture. This required recognition of a problem, documentation with clinical data, changes in policy, and ongoing education until cultural resistance was overcome. These are the tools of quality management, whether dressed up as Lean methodology, Six Sigma, or Change Management,8 and learning them will be as important to the next generation of anesthesiologists as learning the physiology of the neuromuscular junction. The Maintenance of Certification in Anesthesiology Program of the American Board of Anesthesiology includes a requirement for Practice Performance Assessment and Improvement in every cycle,9 a requirement that would be perfectly met by a project such as Dr. Todd’s. If we wish as a profession to push the safety of anesthesia to the next level, this is the kind of work we must all eagerly embrace. DISCLOSURES Name: Richard P. Dutton, MD, MBA. Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript. Attestation: Richard P. Dutton approved the final manuscript. Name: Francois Donati, PhD, MD. Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript. Attestation: Francois Donati approved the final manuscript. This manuscript was handled by: Maxime Cannesson, MD, PhD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.099
Threshold uncertainty score0.332

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0050.007
Scholarly communication0.0090.012
Open science0.0010.008
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0990.061

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.258
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2014
Admission routes1
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