Platform Session C�4:00 p.m.-6:00 p.m.
Notice bibliographique
Résumé
Churlsu Kwon*, A. Metcalfe†,‡, Mingfu Liu‡, H. Quan‡, S. Wiebe†,‡ and Nathalie Jette†,‡*University College of London, London, United Kingdom; †Clinical Neurosciences, University of Calgary, Calgary, AB, Canada and ‡Community Health Sciences, University of Calgary, Calgary, AB, Canada Rationale: Defining comorbidity associated with epilepsy is necessary in order to adequately manage this patient population, and to ensure proper resources are in place for these individuals. There are no population-based studies addressing both somatic and psychiatric comorbidity pre and post epilepsy diagnosis to address the following questions: (1) Is the prevalence of comorbidity higher in those with epilepsy compared to those without epilepsy before the epilepsy diagnosis and (2) Does the prevalence of comorbidity increase in those with epilepsy after their epilepsy diagnosis? The objective of this study was to determine the prevalence of comorbidity in those with and without epilepsy in the two years before diagnosis and in the year after diagnosis. Somatic and Psychiatric Comorbidity Pre and Post Epilepsy Diagnosis. 95% CI – 95 percent confidence interval. Only the comorbidity which were significantly increased post epilepsy diagnosis are shown above. Methods: Data was obtained on 26,235 individuals from the following linked administrative databases between the years 1996/1997 to 2003/2004: a provincial health care insurance plan registry, a hospital discharge abstract database, an emergency room visits database and a physician claims database in a large Canadian health region. A case was defined as anyone who had 2 physician claims or 1 hospitalization or 1 emergency room visit in two years for epilepsy. Four-to-one matching was used, and controls were matched on age and sex. Results: Our sample consisted of 5,247 subjects with epilepsy and 20,988 subjects without epilepsy, with a mean age of 37.4 ± 22.6 years (S.D.) (range 0.01–96.4 years). In the two years prior to epilepsy diagnosis and in the year following diagnosis there was a statistically significant higher rate of all comorbidity studied (heart disease, peripheral vascular disorders, chronic pulmonary disease, renal failure, liver disease, diabetes, peptic ulcer disease excluding bleeding, AIDS/HIV, cancer, CNS tumor, rheumatoid arthritis/collagen vascular disease, stroke, pneumonia, dementia, hypertension, traumatic brain injury, multiple sclerosis, cerebral palsy, anoxic brain injury, encephalopathy, alcohol abuse, drug abuse, psychoses, depression, fractures, and Crohn's disease/colitis). The relative risk (RR) of having any comorbidity in epilepsy was 1.77 (95% CI 1.72–1.81) pre-diagnosis and 2.11 (95% CI 2.04–2.18) post diagnosis. The following comorbidity were significantly more prevalent in the one year post epilepsy diagnosis than in the two years preceding diagnosis (see Table): heart disease, cancer (excluding brain tumors), dementia, drug abuse, depression, pneumonia, and fractures. Conclusions: This study indicates that epilepsy is associated with a higher likelihood of having comorbidity pre- and post-epilepsy diagnosis, and that the prevalence of comorbidity increases after the diagnosis of epilepsy. The temporal association does not imply causation, but raises important questions in this regards. As this population is likely to have more contact with the health care system to manage their various conditions, there should be more opportunities to emphasize the prevention of the development of new comorbidity.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,801 | 0,678 |
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 ».