Manufacturers' obligations to colour‐code prefilled syringes correctly
Bibliographic record
Abstract
I read with interest the letter from by Dr Torlot 1. The debate surrounding drug-label colour-coding in anaesthesia has been active for around 30 years, much of it taking place in this journal 2-4. In addition, an international colour-code standard for user-applied anaesthetic labels has now been adopted in the UK, the USA, Canada, Germany, Australia and New Zealand 5. It is therefore astonishing and rather alarming that a pharmaceutical manufacturer is able to bring to the market a prefilled syringe for suxamethonium that is colour-coded in a way dangerously inconsistent with the existing colour standard. The international colour-code standard has an additional safety feature specifically for potentially dangerous drugs like suxamethonium, namely the reversed lettering and background of the drug name as way of an alert to the user. Not only does the Aurum Pharmaceuticals prefilled syringe not have this reversed alert text, but the blue colour they have chosen for the syringe label is identical to that for opioids under the international colour standard. We know from a recent large-scale study of over 74 000 anaesthetics that syringe-swap errors between drug classes can be significantly reduced by using the new international colour standard because of the drug-class specific colour cues 6. Why would any manufacturer then use the same colour for two drugs from different pharmacological classes? I can imagine that the ‘legal’ response from a pharmaceutical company over such a matter might be to point out that it is the anaesthetist's responsibility to read the label (no matter how poorly labelled the drug) and that technically, the international colour-code standard is intended for ‘user-applied’ drug labels and therefore does not apply to the manufacture of a prefilled syringe which comes already labelled, hence allowing the manufacturer to make the label any colour it likes. The provision of a new prefilled syringe should be seen as an opportunity to increase patient safety by getting the details right, rather than bizarrely creating a new trap or latent system error that will in time inevitably lead to a new kind of error. Over ten years ago I pointed out that ampoule labelling standards are such that ampoule labels could carry colour-coding consistent with the international user-applied labelling standard 7. This would have significant ergonomic benefits for anyone drawing up drugs from colour-coded ampoules into similarly colour-coded syringes, and there is no reason why such consistency of colour-coding could not also apply to pre-filled syringes. In fact, in our hospital we have had consistently colour-coded prefilled syringes for over ten years 8.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".