Exploring the Distribution of Prescription for Sulfonylureas in Patients with Type 2 Diabetes According to Cardiovascular Risk Factors Within a Canadian Primary Care Setting.
Notice bibliographique
Résumé
BACKGROUND: A growing body of evidence generated from observational studies and meta-analyses has begun to illustrate the potential adverse cardiovascular (CV) risk profile associated with sulfonylurea (SU) use. Specifically, the use of an SU has been demonstrated to be associated with increased mortality and a higher risk of stroke with more CV events associated with SU use having been reported in subgroups of patients with a history of CV disease, elderly and a higher body mass index. OBJECTIVE: The objective of the current study was to explore the distribution of established atherosclerotic CV disease and CV risk factors amongst patients with diabetes on an SU using a Canadian primary care dataset for the 2013 calendar year. METHODS: The Canadian Primary Care Sentinel Surveillance Network (CPCSSN), which is a multi-disease surveillance system based on primary care electronic medical record data, was utilized for this research study. Patients with a diagnosis of diabetes and exposure to an SU were identified. Distribution/prevalence of CV risk profile amongst this sub-cohort was explored. RESULTS: In analyzing the CPCSSN database for the 2013 calendar year, 6150 patients were identified as having diabetes, at least one visit with their family doctor, and on an SU. For this sub-cohort, demographic data was as follows: age [mean (SD)] 65.4(12.8) years-old; 56.4% male and mean BMI 31.3(10.0). Established atherosclerotic CV disease was observed in 16.8% of the patients with the following distribution: 13.2% had ischemic heart disease/myocardial infarction or coronary artery disease; 2.4% had stroke; and 2.3% had peripheral vascular disease. Regarding the aggregation of CV risk factors, a large proportion (65%) of patients without established atherosclerotic CV disease presented with 2 or more CV risk factors including: hypertension (62%), dyslipidemia (33%), active smoking (13%), and obesity (43%). Almost half of the cohort (45%) were males older than 55 years of age or females older than 60 years of age with at least one of the following risk factors: dyslipidemia, hypertension or current smoking, but without established cardiovascular disease. A large proportion of patients (19.5%) had a diagnosis of cardiac-specific issues including ischemic heart disease/myocardial infarction/coronary artery disease, heart failure (not due to ischemic heart disease/myocardial infarction/coronary artery disease), or arrhythmia. Almost 82% of patients had either established atherosclerotic CV disease or 2 or more CV risk factors without established atherosclerotic CV disease. CONCLUSION: This study illustrated that in this dataset of Canadian patients with diabetes in a primary care setting, a substantial proportion of patients treated with an SU in 2013 had established CV disease and/or an aggregation of multiple CV risk factors. In light of recent data reporting on an association between SU utilization and CV events and increased mortality, pharmacovigilance programs should actively monitor SU utilization in patients with diabetes and a high risk CV profile in real world clinical settings.
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 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,003 | 0,009 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».