Desflurane – balancing the environmental costs and cognitive benefits. A reply
Bibliographic record
Abstract
I thank Dr. Freeman for an important comment about the recent Association of Anaesthetists’ Guidelines for the peri-operative care of people with dementia, which correctly pointed out the incorrect referencing of our assertion that desflurane may be preferable to sevoflurane or isoflurane for general anaesthesia in people with cognitive impairment 1. The correct reference should have been attributed to Jiang and Jiang, who recently reviewed the evidence for the effects of inhaled anaesthetic agents on the neuropathogenesis of Alzheimer's disease 2. In experimental (tissue and mouse) studies, isoflurane and sevoflurane, more so than desflurane, have been found to activate capsases, increasing the synthesis and accumulation of β-amyloid protein, and to induce hyperphosphorylation of tau protein, both of which mechanisms are involved in the neuropathogenesis of Alzheimer's disease. Dr. Freeman is absolutely correct to challenge the clinical relevance of this experimental research in the context of imminent environmental collapse 3. Personally, I fully agree with Dr. Freeman that the marginal (if any) benefits of desflurane compared with sevoflurane or isoflurane administration in this (or any other) instance are far outweighed by the very significant environmental impact of desflurane 4, 5. Inhalational anaesthetic agents are chlorofluorocarbons, ‘greenhouse gases’ that have between 349 (sevoflurane) and 3714 (desflurane) times the global warming potential over a 20 year time horizon of carbon dioxide (isoflurane 1401), equivalent to driving a car 18 (sevoflurane) to ~350 miles (desflurane) per hour of anaesthetic use (isoflurane 30 miles); these figures do not account for the additional carbon cost of heating desflurane vaporisers. Together with nitrous oxide, inhalational anaesthetic agents contribute ~2.5% of the 22.8 million tonnes of carbon dioxide equivalents the NHS produces annually 6, but their use is not proscribed by the 2016 Kigali amendment to the 1987 Montreal protocol for reducing hydrofluorocarbon use, on the grounds of medical necessity 7. Given that effective waste gas scavenging, although available (with an energy cost), is not currently used (or even practical) during patient transfer to or recovery within the recovery area, and that even low-flow anaesthesia used throughout an anaesthetist's career contributes significantly to global warming 8, as individuals and as a profession we have to consider whether the continued use of inhalational anaesthetic agents supports the ‘triple bottom line’ of accounting for people, place and finance when considering the global impact of any technology, or whether it now represents cultural and professional baggage; safe, reliable alternatives to inhalational anaesthesia exist (total intravenous anaesthesia, regional anaesthesia) and their use may have environmental as well as clinical benefits for people with dementia who require surgery.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".