Management of Diabetes Mellitus in Adults at the End of Life: A Review of Recent Literature and Guidelines
Bibliographic record
Abstract
Abstract Background: The prevalence of diabetes mellitus (DM) is rising with an increased risk of developing it as a person ages. Therefore, more persons will have comorbid DM throughout their health journey and are potentially prone to unpleasant symptoms associated with poor glycemic control at the end of life (EOL). We performed an in-depth literature review to examine evidence-based recommendations on DM management at the EOL. Design: A librarian-assisted systematic and gray literature search was performed in electronic clinical databases and Google™ for diabetes management articles (DMAs). National and international diabetes, palliative care, and general guideline websites were searched for clinical practice guidelines (CPGs). Inclusion criteria: adults ≥18 years with terminal illnesses, articles published between 2007 and 2017 with blood sugar target, monitoring frequency, and management recommendations for type 1 and type 2 DM. Exclusion criteria: conference poster abstracts and CPGs without published year or references. Two independent appraisers evaluated the CPGs using the “Rigour of Development” domain of the Appraisal of Guideline Research and Evaluation II (AGREE II) instrument. Results: Nine full-text DMAs were included for review from 2476 screened articles. Twenty-one CPG websites were searched. For the six included CPGs, the AGREE II “Rigour of Development” domain scores ranged from 6% to 34%. We found no high-quality evidence for DM management at the EOL. Treatment recommendations were based primarily on expert opinion (level IV evidence). Conclusions: Higher quality studies are required to inform a standardized approach to the management of DM at the EOL.
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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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".