The identification of persons with epilepsy in a population-based cohort
Notice bibliographique
Résumé
Estimating the prevalence and incidence of epilepsy in the absence of physician assessment is challenging. In Canada, the incidence of epilepsy is unknown while two reports of the estimated lifetime prevalence are based on a subject’s response to a single unvalidated question to screen for epilepsy. The Canadian Longitudinal Study of Aging (CLSA) is a nationwide population study of 50,000 people aged 45-85 years at baseline which presently also relies on a similar unvalidated question to identify persons with epilepsy.The purpose of this research is threefold: (a) to systematically review non-physician administered screening tools reported in the scientific literature designed to identify persons with epilepsy (PWE) in population-based cohorts; (b) to design a screening questionnaire and disease-ascertainment algorithm to identify PWE in a population-based cohort; (c) to investigate the performance of this disease-ascertainment algorithm in a consecutive sample of CLSA participants alongside a consecutive sample of individuals from an epilepsy-enriched general neurology clinic at the Montreal Neurological Institute and Hospital.This thesis centres on two manuscripts. The first presents the results of a systematic review of screening questionnaires. In it, we concluded that 10 studies were eligible for inclusion. The estimated sensitivity and specificity of these tools in identifying persons with a lifetime history of epilepsy ranged from 61.5% to 100% and 65.6% to 99.2%, respectively. The sensitivity and specificity of these tools in identifying persons with active epilepsy ranged from 48.6% to 100% and 73.9% to 99.9%, respectively. Overall we found that there was high risk of bias in patient selection, the index test and flow/timing in the majority of studies while six studies used an affected case vs. unaffected control study design creating the potential for spectrum bias and subsequently inflated accuracy estimates.The second manuscript presents the Canadian Longitudinal Study on Aging – Epilepsy Algorithm (CLSA-EA), a questionnaire and disease-ascertainment algorithm, as well as the results of a validation study. In this validation study, we recruited 242 participants, 34 of whom were diagnosed with epilepsy by one of our study neurologists. The sensitivity and specificity of the CLSA-EA for a lifetime history of epilepsy were 97.1% and 98.1%, and for active epilepsy were 100% and 98.6%.It is important from a clinical, epidemiologic and public policy perspective to accurately ascertain the incidence and prevalence of epilepsy in population-based cohorts. After a systematic review of the literature, careful design and final validation to assess its diagnostic accuracy, we present the CLSA-EA. Plans are underway to apply the CLSA-EA to all 50,000 participants in the CLSA cohort with the aim to provide a valid estimate of the incidence and prevalence of epilepsy in those aged greater than 45 years in Canada.
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 | 0,029 | 0,091 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,004 |
| Bibliométrie | 0,007 | 0,006 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 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 ».