Glycemic Control in Long Term Care: Considerations for more Appropriate Individualized Care.
Notice bibliographique
Résumé
Diabetes, specifically type 2 diabetes (T2DM), is a metabolic disease that is highly correlated with increasing age. Diabetes is prevalent in about a quarter of residents in LTC, where its management in elderly residents is complicated by the presence of multiple comorbidities, a high level of vulnerability and risk of death. Despite this, evidence for the benefit of tight blood glucose control in preventing cardiovascular and other geriatric outcomes in the frail elderly is inconclusive. Although many clinical practice guidelines (CPG) call for more relaxed blood glucose control in the frail elderly, evidence for relaxed blood glucose targets is mostly based on expert consensus, resulting in variable recommendations among different CPG’s. Furthermore, the current literature suggests that blood glucose values are generally below the recommended lower threshold (an A1C <7.0%) in LTC residents. However, it is not conclusive as to whether lower A1C values are a reflection of the clinical characteristics of the frail elderly in LTC, or a result of stringent blood glucose control. Finally, research in Canada regarding the management of diabetes in LTC homes is greatly lacking. \nThis study conducted a mixed method design (convergent parallel design) in order to explore the current practices, processes, and opinions of blood glucose control in Ontario LTC homes. This study conducted a provincial survey exploring opinions of blood glucose control and treatment among LTC medical directors and attending physicians across Ontario. Alongside the survey, this study also conducted in-depth phone interviews with medical directors, attending physicians, and nurses of varying educational and managerial positions, in order to explore the experiences of managing blood glucose in LTC residents with diabetes. \nThe findings of this study illustrate the growing appreciation of less stringent blood glucose control in elderly LTC residents among LTC physicians and nurses. Frailty, a limited life expectancy and dementia, are common factors that promote less stringent blood glucose control. However, there is still variance in what blood glucose targets physicians are willing to consider. Furthermore, there appears to be two approaches to managing hyperglycemia in LTC. Whereas some physicians are mainly concerned with preventing acute symptoms of hyperglycemia in LTC residents with a less stringent approach, other physicians are of the opinion that hyperglycemia is still related to multiple short term illnesses and complications in LTC residents, and are less willing to consider the more extreme opinions of less stringent control that exist. Barriers to optimal blood glucose control within LTC homes include the presence of dementia and managing a resident’s diet, including unpredictable intake and poor diet choices by the resident or family. Physicians limited their consideration of sliding scale and complex insulin regimens in LTC residents when possible. However, attempts to reduce monitoring parameters was complicated by the presence of unstable blood glucose levels as a result of frailty, dementia, and variable diet intake. The study also identified the role for increased communication between health professionals within LTC and a need for continuing education, especially for the nursing staff, in order to facilitate optimal management. \nFuture research should explore the perceptions and experiences of other key professionals and individuals that are essential to informing the experiences of blood glucose control and overall diabetes management in LTC. Studies should also address the current practices of diabetes management in LTC residents, in order to highlight any potential differences between what physicians and nurses report versus actual practice. Finally, future studies should explore the effect of hyperglycemia on short term complications and geriatric outcomes, in order to better inform management that improves the quality of life of residents.
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 | 0,018 | 0,045 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,004 |
| Communication savante | 0,010 | 0,007 |
| Science ouverte | 0,003 | 0,007 |
| Intégrité de la recherche | 0,006 | 0,013 |
| 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 ».