Leveraging Cognitive and Speech Ecological Momentary Assessment in Individuals With Phenylketonuria: Development and Usability Study of Cognitive Fluctuations in a Rare Disease Population
Notice bibliographique
Résumé
BACKGROUND: Phenylketonuria (PKU) is a rare, hereditary disease that causes disruption in phenylalanine (Phe) metabolism. Despite early intervention, individuals with PKU may have difficulty in several different cognitive domains, including verbal fluency, processing speed, and executive functioning. OBJECTIVE: The overarching goal of this study is to characterize the relationships among cognition, speech, mood, and blood-based biomarkers (Phe, tyrosine) in individuals with early treated PKU. We describe our initial optimization pilot results that are guiding this study while establishing the feasibility and reliability of using ecological momentary assessment (EMA) in this clinical population. METHODS: In total, 20 adults with PKU were enrolled in this study between December 2022 and March 2023 through the National PKU Alliance. Of the total, 18 participants completed an extended baseline assessment followed by 6 EMAs over 1 month. The EMAs included digital cognitive tests measuring processing speed, sustained attention, and executive functioning, as well as speech (semantic fluency) and mood measures. Participants had 60 minutes to complete the assessment. RESULTS: Completion rates of EMAs were above 70% (on average 4.78 out of 6 EMAs), with stable performances across baseline measures and EMAs. Between-person reliability (BPR) of the EMAs, representing the variance due to differences between individuals versus within individuals, is satisfactory with values close to (semantic fluency BPR: 0.7, sustained attention BPR: 0.72) or exceeding (processing speed: 0.93, executive functioning: 0.88) data collected from a large normative database (n=5039-10,703), as well as slightly below or matching a previous study using a clinical group (n=18). As applicable, within-person reliability was also computed; we demonstrated strong reliability for processing speed (0.87). A control analysis ensured that time of day (ie, morning, afternoon, and evening) did not impact performance; performance on tasks did not decrease if tested earlier versus later in the day (all P values >.09). Similarly, to assess variability in task performance over the course of all EMAs, the coefficient of variability was computed; 28% for the task measuring sustained attention, 37% for semantic fluency, 15.8% for the task measuring executive functioning, and 17.6% for processing speed. Performance appears more stable in tasks measuring processing speed and executive functioning than on tasks of sustained attention and semantic fluency. CONCLUSIONS: Preliminary results of this study demonstrate strong reliability of cognitive EMA, indicating that EMA is a promising tool for evaluating fluctuations in cognitive status in this population. Future work should refine and expand the utility of these digital tools, determine how variable EMA frequencies might better characterize changes in functioning as they relate to blood-based biomarkers, and validate a singular battery that could be rapidly administered at scale and in clinical trials to determine the progression of disease.
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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 | 0,007 | 0,013 |
| 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 | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| 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 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 ».