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Record W2921608072 · doi:10.1111/anae.14618

Doubt about pre‐operative carbohydrate supplementation

2019· letter· en· W2921608072 on OpenAlexaff
S. Scott, André Lupp Mota, Carol Loffelmann, G. Fettke, Catherine Crofts

Bibliographic record

VenueAnaesthesia · 2019
Typeletter
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsMedicineContext (archaeology)Lactic acidosisIngestionDistressIntensive care medicinePhysiologyInternal medicine

Abstract

fetched live from OpenAlex

We commend Fawcett and Thomas for their review of pre-operative fasting recommendations 1 and applaud their candid acknowledgement of the mounting evidence of lack of clinical benefit for oral pre-operative carbohydrate loading (preCHO), considered an essential element of the enhanced recovery after surgery (ERAS) programme 2. We wish to mount further direct challenges to the concept of preCHO, on several grounds. The subjective benefits of preCHO, namely the reduction in anxiety, distress, thirst and hunger 1-3, are relative to the dietary habit of the subject during the preceding weeks, as much as they are to the immediate duration of restriction of food and water. A predominantly carbohydrate-based ‘standard’ diet (such as has been advised by national advisory bodies for several decades) accentuates these symptoms, whereas the widespread adoption of reduced fasting times for both food and water (6 h and 2 h, respectively), reduces the impact of this acute deprivation. Indeed, preCHO has been shown to be of benefit only when compared with fasting without water, but negligible when compared with water 1. The analogy drawn between surgical stress and exercise, with respect to lactate production and carbohydrate loading, is both false and out-dated. In the context of exercise, lactic acid is produced when glycolysis outstrips mitochondrial capacity for aerobic metabolism, whereas intra-operative lactic acidosis is likely to represent hypoperfusion. This does not imply a primary substrate lack and therefore is not improved by preCHO. The objective metabolic benefit of preCHO is purported to be a reduction in peri-operative insulin resistance, as evidenced by an improvement of insulin sensitivity assessed by the hyperinsulinaemic euglycaemic clamp test (HIEG) 3. We contend that this appears to be based on a divergence from the metabolic standards of that test. When the HIEG was first described in 1979 4, the pre-conditions required that all subjects not exercise for 48 h and all consume ‘at least 200 g of carbohydrate per day for 3 days before study’, implying that some standardisation of carbohydrate consumption is necessary. However, in all of the preCHO-studies’ application of the HIEG 3, precisely the opposite occurs: the preCHO group is administered 150 g maltodextrin within 12 h of the pre-operative test, whereas the fasted control group is not. It is our contention that this preCHO augments the disposal of glucose during subsequent HIEG, through mechanisms that are not yet fully understood. By way of analogy, this is akin to comparing sprint time-trial performance between those that are sprinting at the start, vs. a stationary-start control. Since preCHO has no significant demonstrable clinical benefit compared with placebo, we propose that it be relegated to be an optional, rather than obligatory, component of ERAS. Furthermore, in light of current understanding of the incidence and consequences of peri-operative hyperglycaemia 5 and the growing recognition of the incidence and implications of covert primary hyperinsulinaemia 6 in the population, we would caution against preCHO in the majority of surgical patients.

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)0.009
metaresearch head score (Gemma)0.027
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: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0060.012
Insufficient payload (model declined to judge)0.0040.002

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 head0.014
GPT teacher head0.282
Teacher spread0.267 · 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
GenreCommentary

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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Citations2
Published2019
Admission routes1
Has abstractyes

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