Trust me, I’m a validated test!?: Unseen mild (cognitive) impairment and the use of the MoCA in an old age psychiatry setting.
Notice bibliographique
Résumé
In clinical practice two seemingly distinct disorder clusters are referred to the old age psychiatry; psychiatric disorders and neurodegenerative disorders. However, both psychiatric and neurodegenerative causes can start with (mild) cognitive deficits. An elaborate neuropsychological assessment is part of the gold standard for identifying the cause. As it is expensive and burdensome for the patient to do this in specialised outpatient clinics, a triaging test before a referral is made is desirable. A fast test with discriminatory power in this group of patients with a non-uniform presentation is of great value as an increasing number of people have dementia; they are examined earlier in the process, and this interferes with regular (psychiatric) treatments and complicates diagnostics due to increasing overlapping symptom presentation. This test should be validated to allow the scores to be interpreted properly so it can help to identify or exclude (mild) cognitive impairment. The Montreal Cognitive Assessment (MoCA) is a short screening test (10 minutes long) for cognitive complaints but it was not validated in old age psychiatry. Not only did we validated the MoCA for this setting, we also show how to improve its use in clinical practice by using a double threshold. In addition to the preceding summary one must consider that patients tend not to mention all of their needs during visits. The symptoms experienced do not always have to correspond to their objective symptoms. This also applies for what close relatives report. Therefore, we must be aware of that patients are not always able to properly draw attention to their request for help or, in fact, the cause of their complaints. Screening could be a solution, but often comes with costs. To screen or not to screen – that is often the question. In this dissertation, we have provided the arguments that the MoCA can play a substantial role colouring the grey area that this question raises. Therefore allowing (part of) this discussion to be settled for cognitive impairment. This accounts especially in old age psychiatry where MCI is a frequent issue due to multiple aetiologies. What you see is not always what you get. We show that this is also true for needs, unmet needs, and the (free) concentration of valproic acid. We think that the MoCA is suitable for MCI screening in old age psychiatry, with its population at risk. However knowing its strengths and weaknesses is essential. It is faster, cheaper, and therefore easier to apply than a neuropsychological assessment; however, it will have difficulties in differentiating the aetiologies, including cognitive impairment of psychiatric origin. Therefore the MoCA should not only be used on indication (triaging) but also to get an indication (screening) in old age psychiatry. If your MMSE score is wrong, then something is really going on. If your MoCA score is right, then you should be alright. If your MoCA score is so so, active monitoring is the way to go. If your MoCA score is low, an elaborate assessment should follow. We show in this dissertation the importance of knowing the strengths and weaknesses of a screening instrument in old age psychiatry. Trust me, I‘m a validated test…….? Trust me, I’m a doctor , and know how to use a validated test!
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 | 0,008 | 0,047 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».