Notice bibliographique
Résumé
The US Census Bureau predicts that 20% of the US population will be 65 years or older by 2030 (1,2). In 2019, the United States had 8.6 geriatricians for every 100,000 people (3). Given this shortage, educating health care professionals on the unique aspects of aging-related care is essential. Within our current health care system, there is an emphasis on disease-specific management, which may lead to the under recognition of geriatric syndromes such as frailty, delirium, and falls—conditions that significantly impact functional status, quality of life, and mortality. A geriatric syndrome is a clinical condition in older adults that does not fit into a discrete disease category but is characterized by the inability of the body to compensate and overcome cumulative impairments in multiple systems (4). In 2017, geriatricians in Canada and the United States officially launched the Geriatric 5 Ms framework, which focuses on the following key areas: mind, mobility, medications, what matters most, and multicomplexity (5). As individuals age, their gastrointestinal (GI) system undergoes physiological changes that can increase susceptibility to common GI disorders. One of the most notable changes is the slowing of digestive processes, which can contribute to indigestion, bloating, constipation, and altered nutrient absorption. Reduced motility in the intestines can further exacerbate issues such as constipation, irritable bowel syndrome (IBS), and diverticulosis. Additionally, the aging liver and pancreas often produce fewer digestive enzymes, which can impair nutrient absorption and contribute to malnutrition or deficiencies in key vitamins and minerals. The aging process also increases the risk of more serious GI issues, such as gastroesophageal reflux disease (GERD) and colorectal cancer. In older individuals, the lower esophageal sphincter may weaken, making it easier for stomach acid to flow back into the esophagus, leading to GERD. Moreover, the risk of colorectal cancer increases significantly after the age of 50, with regular screenings becoming crucial for early detection. In terms of treatment, older patients often have multiple comorbidities and are on various medications, which can exacerbate GI issues. Medications such as NSAIDs or certain antihypertensives can irritate the stomach lining or affect bowel movements, further complicating the management of GI disorders in this age group. Despite these challenges, ageism in clinical decision-making remains a significant barrier, with older adults often remaining undertreated. To address these issues, this monograph explores 7 key areas at the intersection of aging and gastroenterology: colonic conditions, inflammatory bowel disease, vaccinations, functional GI disorders, pancreatic diseases, hepatobiliary disorders, and gastroesophageal conditions. By providing an in-depth review of these topics, we aim to equip practitioners with the knowledge needed to navigate the complexities of GI care in older adults, reduce disparities in treatment, and optimize patient outcomes. On behalf of all authors and editors of this Monograph, we would like to acknowledge and give a special thank you to Dr. Seymour Katz, whose vision and dedication inspired this important initiative. We would also like to thank David Stein for his pivotal role in securing funding, Maddie Kachurak for tirelessly and expertly guiding the process, as well as the entire ACG staff for their invaluable support in bringing this work to fruition.
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 | 0,002 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,006 | 0,004 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,477 | 0,300 |
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; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».