Consensus Recommendations for Sick Day Medication Guidance for People With Diabetes, Kidney, or Cardiovascular Disease: A Modified Delphi Process
Bibliographic record
Abstract
RATIONALE & OBJECTIVE: Sick day medication guidance (SDMG) involves withholding or adjusting specific medications in the setting of acute illnesses that could contribute to complications such as hypotension, acute kidney injury (AKI), or hypoglycemia. We sought to achieve consensus among clinical experts on recommendations for SDMG that could be studied in future intervention studies. STUDY DESIGN: A modified Delphi process following guidelines for conducting and reporting Delphi studies. SETTING & PARTICIPANTS: An international group of clinicians with expertise relevant to SDMG was recruited through purposive and snowball sampling. A scoping review of the literature was presented, followed by 3 sequential rounds of development, refinement, and voting on recommendations. Meetings were held virtually and structured to allow the participants to provide their input and rapidly prioritize and refine ideas. OUTCOME: Opinions of participants were measured as the percentage who agreed with each recommendation, whereas consensus was defined as >75% agreement. ANALYTICAL APPROACH: Quantitative data were summarized using counts and percentages. A qualitative content analysis was performed to capture the context of the discussion around recommendations and any additional considerations brought forward by participants. RESULTS: The final panel included 26 clinician participants from 4 countries and 10 clinical disciplines. Participants reached a consensus on 42 specific recommendations: 5 regarding the signs and symptoms accompanying volume depletion that should trigger SDMG; 6 regarding signs that should prompt urgent contact with a health care provider (including a reduced level of consciousness, severe vomiting, low blood pressure, presence of ketones, tachycardia, and fever); and 14 related to scenarios and strategies for patient self-management (including frequent glucose monitoring, checking ketones, fluid intake, and consumption of food to prevent hypoglycemia). There was consensus that renin-angiotensin system inhibitors, diuretics, nonsteroidal anti-inflammatory drugs, sodium/glucose cotransporter 2 inhibitors, and metformin should be temporarily stopped. Participants recommended that insulin, sulfonylureas, and meglitinides be held only if blood glucose was low and that basal and bolus insulin be increased by 10%-20% if blood glucose was elevated. There was consensus on 6 recommendations related to the resumption of medications within 24-48 hours of the resolution of symptoms and the presence of normal patterns of eating and drinking. LIMITATIONS: Participants were from high-income countries, predominantly Canada. Findings may not be generalizable to implementation in other settings. CONCLUSIONS: A multidisciplinary panel of clinicians reached a consensus on recommendations for SDMG in the presence of signs and symptoms of volume depletion, as well as self-management strategies and medication instructions in this setting. These recommendations may inform the design of future trials of SDMG strategies.
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 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 | 0.184 | 0.171 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.012 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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.
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".