Anaesthesia
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What’s so interesting?
De Carvalho and co. show that pre-operative voice analysis can be predictive of difficult laryngoscopy.
I’d never thought about that...
The authors describe how different frequency components and acoustic qualities of the voice are, at least partly, determined by the shape and size of different anatomical areas of the vocal tract. By analysing the most intense frequencies (voice formants) within the voice spectrum they were able to correlate components with difficult laryngoscopy, namely Cormack & Lehane grade 3 or 4.
The practicalities
During pre-anaesthetic assessment, 467 elective general surgical patients were asked to pronounce each of the five vowels, corresponding to base phonemes. This was recorded on a smartphone and then later processed and analysed on a laptop computer.1
They found...
A model using voice ‘formants’ could reliably predict difficult laryngoscopy with a ROC-AUC of 0.761 (ie. 76% probability that it correctly classifies a patient as difficult or not). When combined with the modified Mallampati this improved to 92%.
The big picture
While interesting, it’s worth remembering that using voice formants (76%) did not perform as well as modified Mallampati alone (87%), and that this performance is also surprisingly much better than those from the most recent Cochrane meta-analysis (2018) of bedside airway assessment. Over 133 studies the Cochrane review reported a summary sensitivity of only 53% and specificity of 80% for the modified Mallampati (vs 100% and 75% respectively for this study).
Although this is an interesting and novel new test, it’s just not that simple... Screening for an uncommon outcome using tests with imperfect sensitivity and specificity is already problematic, but doubly so when we are not always certain which outcome we should be screening for (laryngoscopy, intubation, ventilation, oxygenation...).
As an airway screening test, voice analysis is both different and also more of the same.
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It would also be feasible for recording, analysis and reporting to occur entirely at the bedside on a smartphone. ↩
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Why should I read this?
The cuffed vs non-cuffed ETT debate for children and neonates is largely settled, demonstrating the superiority of modern cuffed tubes over their historical, uncuffed forbears. Nevertheless, despite reliable evidence to the contrary, many general anaesthetists still prefer uncuffed tubes for children.
Give me the quick overview
Shah & Carlisle explore the accumulated evidence supporting the shift to cuffed endotracheal tubes by paediatric anaesthetists, both in neonates and older children.
They challenge historical airway anatomy & physiology myths that once encouraged the use of uncuffed ETTs in children, and the questionable reliability of the widely-used Cole formula for tube size prediction (size = age/4 + 4; correct in only 50-75%).
The development of Weiss et al.'s Microcuff™ tube represents a watershed moment in addressing concerns of paediatric airway trauma from cuffed ETTs, resulting in improved ETT function without any increase in stridor.
More recently, Chamber's 2018 RCT compared cuffed and uncuffed ETTs in children undergoing elective general anaesthesia, and found that cuffed tubes improved ventilation and reduced short-term post-operative respiratory complications, in addition to decreasing tube changes.
Addressing concern for increased work-of-breathing and higher inspiratory pressures when using a 0.5 mm smaller ID tube, Shah & Carlisle note Thomas et al.'s 2018 laboratory study showing any such effect is easily compensated for with pressure support and automatic tube compensation.
Similarly, the authors also note that there has been no demonstrated evidence of an increased incidence of subglottic stenosis in children using cuffed ETTs.
Finally, Shah & Carlisle report on their updated meta-analysis, showing that cuffed tracheal tubes in children result in fewer tube changes and less sore throat, but no difference in risk of laryngospasm.
Finally word
Using a modern, Microcuff™ or equivalent cuffed ETT that is 0.5 mm smaller in size than an equivalent uncuffed tube, offers functional, ventilation and safety benefits.
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Observational Study
The effects of an aviation-style computerised pre-induction anaesthesia checklist on pre-anaesthetic set-up and non-routine events.
There is ever greater interest in mitigating medical errors, particularly through cognitive aids and checklist-system long-used in the aviation industry.
Jelacic and team instituted a computerised pre-induction checklist, using an observational before-and-after study design across 1,570 cases. This is the first study of a computerised anaesthesia checklist in a real clinical environment.
They found an absolute risk reduction of almost 4% of failure-to-perform critical pre-induction steps, along with reduction in non-routine events and several examples of pre-induction mistake identification through checklist use.
Although the researchers claim the results “strongly argue for the routine use of a pre-induction anaesthesia checklist” this overstates the case a little. This study, like many similar, struggles with confounder effects on anaesthesia vigilance that may explain some of the results, particularly as arising from observational, non-randomised, non-blinded research.
Be careful
The challenge for cognitive aid research is that commonly it must use surrogate markers (workflow step failure; behavioural deviations; efficiency; time spent on task etc.) rather than the safety outcomes that actually matter to patients: death and injury.
There is no easy way around this other than large multi-center studies focusing on outcomes, such as the WHO surgical safety checklist study – which even then, has not escaped criticism!
Thinking deeper...
There will continue to be tension between those pro-checklist and those against. The irony is that both camps share a similar rationale for their position: the advocates for routine checklists point to the safety benefits of reducing cognitive load, whereas those opposing argue that enforced use is anti-individual and itself adds additional task and cognitive burden for clinicians.
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