Association of Neurocognition With Transition to Psychosis
Notice bibliographique
Résumé
IMPORTANCE: Neurocognition is a central characteristic of schizophrenia and other psychotic disorders. Identifying the pattern and severity of neurocognitive functioning during the "near-psychotic," clinical high-risk (CHR) state of psychosis is necessary to develop accurate risk factors for psychosis and more effective and potentially preventive treatments. OBJECTIVES: To identify core neurocognitive dysfunctions associated with the CHR phase, measure the ability of neurocognitive tests to predict transition to psychosis, and determine if neurocognitive deficits are robust or explained by potential confounders. DESIGN, SETTING, AND PARTICIPANTS: In this case-control study across 8 sites, baseline neurocognitive data were collected from January 2009 to April 2013 in the second phase of the North American Prodrome Longitudinal Study (NAPLS 2). The dates of analysis were August 2015 to August 2016. The setting was a consortium of 8 university-based, outpatient programs studying the psychosis prodrome in North America. Participants were 264 healthy controls (HCs) and 689 CHR individuals, aged 12 to 35 years. MAIN OUTCOMES AND MEASURES: Neurocognitive associations with transition to psychosis and effects of medication on neurocognition. Nineteen neuropsychological tests and 4 factors derived from factor analysis were used: executive and visuospatial abilities, verbal abilities, attention and working memory abilities, and declarative memory abilities. RESULTS: This study included 264 HCs (137 male and 127 female) and 689 CHR participants (398 male and 291 female). In the HCs, 145 (54.9%) were white and 119 (45.1%) were not, whereas 397 CHR participants (57.6%) were white and 291 (42.3%) were not. In the HCs, 45 (17%) were of Hispanic origin, whereas 127 CHR participants (18.4%) were of Hispanic origin. The CHR individuals were significantly impaired compared with HCs on attention and working memory abilities and declarative memory abilities. The CHR converters had large deficits in attention and working memory abilities and declarative memory abilities (Cohen d, approximately 0.80) compared with controls and performed significantly worse on these dimensions than nonconverters (Cohen d, 0.28 and 0.48, respectively). These results were not accounted for by general cognitive ability or medications. In Cox proportional hazards regression, time to conversion in those who transitioned to psychosis was significantly predicted by high verbal (premorbid) abilities (β = 0.40; hazard ratio [HR], 1.48; 95% CI, 1.08-2.04; P = .02), impaired declarative memory abilities (β = -0.87; HR, 0.42; 95% CI, 0.31-0.56; P < .001), age (β = -0.10; HR, 0.90; 95% CI, 0.84-0.97; P = .003), site, and a combined score of unusual thought content or delusional ideas and suspiciousness or persecutory ideas items (β = 0.44; HR, 1.56; 95% CI, 1.36-1.78; P < .001). CONCLUSIONS AND RELEVANCE: Neurocognitive impairment, especially in attention and working memory abilities and declarative memory abilities, is a robust characteristic of CHR participants, especially those who later develop psychosis. Interventions targeting the enhancement of neurocognitive functioning are warranted in this population.
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 | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».