Effectiveness and Safety of Preoperative Oral Carbohydrates in Enhanced Recovery after Surgery Protocols for Patients with Diabetes Mellitus: A Systematic Review
Bibliographic record
Abstract
To evaluate the necessity and safety of preoperative oral carbohydrates in enhanced recovery after surgery (ERAS) protocols for diabetes mellitus patients. We searched PubMed, EMBASE, the Cochrane Library, Chinese Biomedical Literature Database, China National Knowledge Infrastructure, and WANFANG databases for articles published through September 2018. We used the Cochrane risk-of-bias tool to assess the methodological quality of included studies. Literature screening, data extraction, and quality evaluation were performed independently by two investigators. Of the 6328 retrieved articles, five eligible randomized controlled trials were included. Two were from China and three were from Germany, Sweden, and Canada. Preoperative oral carbohydrates may facilitate control of preoperative blood glucose, improve postoperative insulin resistance in diabetes patients, and decrease the occurrence of adverse reactions. However, the overall quality of the included studies was low. The available evidence shows that preoperative oral carbohydrates are probably beneficial for patients with diabetes mellitus. High-quality, large randomized controlled trials are needed to verify our findings and provide quantitative results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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 source (direct Gemma or distilled Codex), 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".