Abstract B042: A survey of Neuro-Oncology (NOB) clinical providers to assess the feasibility and utility of the administration of the Montreal Cognitive Assessment (MoCA) cognition duo app in an outpatient clinic
Notice bibliographique
Résumé
Abstract Introduction: Primary brain tumor (PBT) patients experience significant cognitive decline, and early symptom detection helps clinical providers identify and manage impairments as part of routine care. The Montreal Cognitive Assessment (MoCA) is a brief screening tool consisting of standardized assessments of eight key cognitive domains. Our group previously reported the feasibility of use in telehealth and clinical care, and here we explore the feasibility and utility of a newly developed App (MoCA Duo APP) for routine patient care through provider and assessor feedback. Methods: The MoCA assessment was used for 178 examinations using the MoCA Cognition Duo APP by trained MoCA assessors, with results shared with NOB healthcare providers prior to patient visits. After five months, ten providers (Physicians = 5, Nurse Practitioners = 5) were sent a 12-item survey through SurveyMonkey that assessed the general use of the MoCA Duo APP in patient care with the utility of use reported here. Results: All ten providers completed the survey, with half reporting using the MoCA before working in the NOB clinic. Most providers (n=9) reported discussing the patient's MoCA results with their clinical teams and with patients before/after clinic visits. Seven providers endorsed being able to use the MoCA duo APP results to accurately assess cognition at all visits, with three indicating patient-specific limitations, including patient anxiety about testing, deficits impacting test completion and results (i.e., hearing, or motor deficits), and language barriers for those with English as a second language affecting utility in some cases. When asked for limitations of use over their usual exam, 3 noted using the MoCA Duo APP assessment aligned with their current exam/clinical impression, 3 reported the MoCA assessment identified a previous deficit they were aware, and 2 noted the discovery of new deficits with the MoCA Duo APP use. Qualitative descriptions included describing (‘the MoCA as the best screening tool’ and ‘deficits found on the MoCA were not found on the exam’) showed its use as a framework for further diagnostic investigations. Qualitative comments also identified relevance to clinical care and endorsement of the importance of cognitive assessment by patients and caregivers. Conclusions: Our findings demonstrate the utility of the MoCA Duo APP in PBT patients by a diverse group of healthcare providers and assessors. Implementing the MoCA Duo APP allowed providers to evaluate patients' cognitive status and confirm known deficits promptly. As reported elsewhere, the median time for completion was 10 minutes, and automatic scoring reduced post-assessment time, allowing for immediate provider use. Further research is needed to evaluate environmental impacts and deficit adaptation, use in determining interventions, and impact on health outcomes. Citation Format: Madhura V. Managoli, Jaime Garcia, Morgan Johnson, McKenzie C. Kauss, Yeonju Kim, Hope Miller, Maeve Pascoe, Elizabeth Vera, Alex R. Wollet, Vivian A. Guedes, Mark R. Gilbert, Terri S. Armstrong, Alvina Acquaye-Mallory. A survey of Neuro-Oncology (NOB) clinical providers to assess the feasibility and utility of the administration of the Montreal Cognitive Assessment (MoCA) cognition duo app in an outpatient clinic [abstract]. In: Proceedings of the AACR Special Conference on Brain Cancer; 2023 Oct 19-22; Minneapolis, Minnesota. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_1):Abstract nr B042.
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 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 | 0,008 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».