Best Evidence Summary for PerioperativeBlood Glucose Management in Patients Undergoing Pancreatectomy
Bibliographic record
Abstract
BackgroundBlood glucose disorder is a common perioperative problem in patients with pancreatectomy. However, current perioperative blood glucose management for pancreatic resection patients in China is mostly based on experience and lack of evidence-based basis.ObjectiveTo summarize the best evidence for perioperative blood glucose management in patients undergoing pancreatectomy.MethodsA systematic literature search of BMJ Best Practice, Up to Date, Guideline International Network, International Diabetes Federation, World Health Organization, National Guideline Clearinghouse, American Diabetes Association, the National Institute for Health and Care Excellence, New Zealand Guidelines Group, Canadian Diabetes Association, Australian Diabetes Society, Scottish Intercollegiate Guidelines Network, PubMed, Web of Science, EMBase, CINAHL Database, Cochrane Library, the Joanna Briggs Institute Evidence-based Health Care Center, Medlive.cn, Wanfang Data, CNKI, and Chinese Biomedical Database was conducted to screen the literature on perioperative blood glucose management in patients with pancreatectomy published from inception to December 2020. The AGREE Ⅱ scale updated in 2009 by the International AGREE Collaboration Organization was used to assess the quality of guidelines. The quality assessment of the expert consensus used the 2017 version of the expert consensus evaluation standard of the Australian JBI Evidence-based Health Care Center. The Jadad scale was used to assess the quality of randomized controlled trials (RCTs) .ResultsA total of 6 637 studies were retrieved, and 13 of them were finally included, of which 7 were clinical practice guidelines, 4 were expert consensus, and 2 were RCTs. The results of quality assessment showed that 3 of the 7 clinical practice guidelines were rated grade A, and the remaining 4 were rated grade B. In assessing the quality of the 4 expert consensuses, the answers of raters for all items were "yes" , except that their answers for the item "Is there a reasonable explanation for the point of view inconsistent with other literature?" were "unclear" . Both the two RCTs were rated high. A total of 62 pieces of best evidence were collected, mainly related to perioperative organization and management, admission evaluation and treatment, blood glucose control goals, blood glucose monitoring, preoperative, intraoperative and postoperative blood glucose management strategies, management of emergency conditions, and discharge guidance.ConclusionClinical medical workers can develop individualized and holistic perioperative blood glucose management plans for patients with pancreatectomy, based on the above-mentioned 9 aspects of best evidence.
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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 | 0.008 | 0.058 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 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 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".