Incidence of Depression and Associated Factors in Patients With Type 2 Diabetes in Quebec, Canada
Notice bibliographique
Résumé
It has been reported that the risk of depression is higher among people with type 2 diabetes compared with a nondiabetic population. Among diabetic patients, depression has been associated with worse self-care behaviors, poor glycemic control, and an increased risk of diabetes complications. Identifying factors associated with the occurrence of depression may help physicians identify earlier diabetic patients at a high risk of developing depression, improve prevention, and accelerate proper treatment. To our knowledge, very few population-based studies have reported on the incidence of clinically diagnosed depression as a consequence of type 2 diabetes over a long follow-up period. The objective of this study was to estimate the incidence of clinically diagnosed depression among type 2 diabetic patients newly treated with oral antidiabetic drugs (ADs) and to identify factors associated with the occurrence of depression.Administrative claims data from the public health insurance plan were used to identify a cohort of new oral AD users aged ≥18 years between 2000 and 2006. Patients were followed from oral AD treatment initiation until the diagnosis of depression, ineligibility for the public drug plan, death, or the end of the study, whichever came first. Incidence rates were determined using person-time analysis. Factors associated with depression were identified using multivariable Cox regression analysis.We identified 114,366 new oral AD users, of which 4808 had a diagnosis of depression. The overall incidence rate of depression was 9.47/1000 person-years (PYs) (10.72/1000 PYs for women and 8.27/1000 PYs for men). The incidence of depression was higher during the year after oral AD treatment initiation. Independent factors associated with depression included having had mental disorders other than depression, hospitalization, a higher number of different drugs taken and of physicians visited during the year before oral AD initiation. Moreover, we observed a statistically significant age-by-socioeconomic status interaction.The incidence of diagnosed depression is higher during the first year after oral AD treatment initiation. Clinicians could pay particular attention to women, patients starting an AD at a young age, those with a low socioeconomic status, and especially those with a history of anxiety or dementia.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».