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Record W2883879848 · doi:10.1111/anae.14362

The ‘full stomach’: full time for sloppy terminology?

2018· editorial· en· W2883879848 on OpenAlexaboutno aff
Stephen Kinsella

Bibliographic record

VenueAnaesthesia · 2018
Typeeditorial
Languageen
FieldMedicine
TopicEsophageal and GI Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsStomachMedicineGastroenterology

Abstract

fetched live from OpenAlex

Take an empty glass of volume X. Fill it with X/2 ml of your favourite liquid. It is now half full. Add another X/2 ml. It is now full. Add any more, and it will run over the sides. Let us try a different experiment. Take an empty stomach. Fill it with four pints of your favourite liquid. It is now full. Then add a kebab and chips. It is now full. Then add a glass of water with effervescent paracetamol. It is now full. The difference, of course, is that a glass is a rigid structure, and we can precisely measure its capacity and its contents. The stomach is an elastic-walled storage organ, designed to hold as much as possible nutriment when there is plenty, and then semicontinuously relay the contents for digestion in the distal alimentary tract. By its nature, therefore, the fullness of a stomach is different from the fullness of a glass. It can contain a variable amount of contents, which may comprise clear or particulate liquids, and solids in various degrees of chunkiness. We even have to consider the gas content as carbonated drinks may add significant volumes of carbon dioxide, which can increase intragastric pressure and the chance of regurgitation. Of course, this is the reason for the concern about stomach contents – the risk that these, in the unconscious state, may enter the lungs and cause asphyxia or pneumonitis. The use of the term ‘full stomach’ as a short-hand to describe a situation where there is a volume of stomach contents that might risk pulmonary aspiration is convenient 1, and long-established 2 – but may be a little too convenient and simple. This is a problem with a common model of medical decision making; a threshold value is identified, and the whole population is then dichotomised into normal or abnormal. For instance, it is clear that a change from an empty to a full stomach does not occur if the stomach antral cross-sectional area increases by 1 mm2, crossing one or other defined risk threshold 3. Further to this, the concept that all pregnant women after 16 weeks gestation have a full stomach 1 obscures important concentration on the actual degree of risk – a high risk after a large meal, or in the presence of bowel obstruction 4 or critical illness 5. The term full stomach is an over-simplistic convention. How about the dichotomised opposite, the ‘empty stomach’? This is not as inaccurate, to be sure, but it may still not be the whole truth. Gastric secretions add volume even when there is no oral input; the volume of stomach contents were found to be lower after drinking 150 ml water than after remaining nil-by-mouth 6. Furthermore, a standard nil-by-mouth period does not guarantee that the volume of stomach contents is below a defined risk threshold, at least in pregnancy. A recent paper suggested that 38% of fasted term pregnant women had stomach contents above a risk threshold of 1.5 ml.kg−1 7, although this finding conflicts with an earlier study showing a much lower rate of 1% 8 and therefore needs to be verified. Two expert groups on stomach ultrasound in Canada 3 and France 9 have called for greater use of point-of-care stomach ultrasound before general anaesthesia. This would allow much improved assessment of risk; in the obstetric theatre for instance, the Obstetric Anaesthetists' Association and Difficult Airway Society guidelines for the management of difficult and failed tracheal intubation in obstetrics suggest that the decision whether to wake a patient after failed intubation should consider, among other factors, the state of the stomach contents (for the sake of example, split into four categories) 10. This could be considered a ‘non-decision’ – the woman is pregnant, ergo she has a full stomach. However, we know that the use of both first- and second-generation supraglottic airway devices in nil-by-mouth women undergoing category 3–4 caesarean section is acceptably safe 10 – certainly acceptable in the event of failure to intubate. An estimate of the actual stomach contents would be reassuring in a labouring woman to know whether she has cleared some or all of her last meal 11, 12, and so guide the potential pathways including wake up/continue unintubated/further attempts to intubate. The practicalities of case selection, and timing are another matter. These will depend on case mix, and ultrasound operator skills. Most emergency caesarean sections are performed on women who are in labour. In England, around 14% of emergency caesarean sections are carried out using primary general anaesthesia 13, albeit with a wide variation in rates between units 14; but these are often with a degree of urgency that would preclude ultrasound except in the most expert hands 8. The huge variability in the interval from admission to the labour ward until caesarean section would call estimates of stomach volume performed early in labour into question. Furthermore, we are a long way from having experts available around the clock who could perform ultrasound on demand, although practice has changed rapidly in other situations; vis the use of ultrasound for central venous catheter insertion, for instance 15. So let us improve the accuracy of our language. Teach the first-month anaesthetic trainee that some patients ‘have a full stomach’, and require a rapid sequence induction of general anaesthesia. But thereafter, after they have learned the basics, let us have a nuanced use of terminology that fits with an up-to-date understanding of pathophysiology, what we can measure in the stomach and how 16, 17, and how we manage degrees of risk in the best interests of our patient. MK in an editor of Anaesthesia. No other competing interests.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.042
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.010
GPT teacher head0.282
Teacher spread0.272 · 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 teacher head, not a consensus.

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".

Quick stats

Citations11
Published2018
Admission routes1
Has abstractyes

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