Consensus Recommendations for Sick Day Medication Guidance for People With Diabetes, Kidney, or Cardiovascular Disease: A Modified Delphi Process
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,184 | 0,171 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,005 | 0,012 |
| Bibliométrie | 0,010 | 0,007 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,007 | 0,006 |
| Science ouverte | 0,005 | 0,008 |
| Intégrité de la recherche | 0,005 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».