Feasibility of Validating a Screening Tool for Neurocognitive Function in Adults with SCD
Notice bibliographique
Résumé
Introduction: Sickle cell disease (SCD) is an inherited hematological disorder with high rates of neurological complications, including ischemic stroke and silent cerebral infarction. Even without brain injury, individuals with SCD may experience progressive neurocognitive impairment. Executive dysfunction and processing speed deficits are particularly common in patients with SCD, negatively impacting medical adherence, educational and occupational outcomes, and the transition from pediatric to adult care. The latest guidelines recommend neurocognitive surveillance and screening in adult patients with SCD, with referral for formal evaluation as needed. However, no cognitive screening measures have been validated in SCD. The Montreal Cognitive Assessment (MoCA) and the Rowland Universal Dementia Assessment Scale (RUDAS) were previously studied in adults with SCD with promising results. An easily accessible, clinically validated cognitive screening tool is urgently needed for the adult SCD population. This pilot study aimed to assess the performance of the MoCA and RUDAS while evaluating the feasibility of virtual neurocognitive screening in an adult SCD population. Methods: Participants were recruited at a SCD clinical center. Individuals over 18 years of age with all types of SCD and any past medical history, including stroke, were included in the pilot study. After obtaining informed consent, the MoCA and RUDAS were administered to patients by a research coordinator. The participants then completed a virtual or in-person neuropsychological battery administered by a neuropsychological associate supervised by a licensed neuropsychologist. MRIs were obtained in participants if they did not have prior imaging within the last 6 months. Self-reported measures of mood, fatigue and pain were also collected. Statistical analyses included summary data and Spearman correlations given our small sample size. Results: A total of 33 participants, ages 22 to 64 years (mean 39.97 years), were consented for the study. Thirty-one completed the MoCA and RUDAS testing and twenty-three completed the neuropsychology testing. The study sample was primarily female (61%) with SCD genotypes SS (76%), S-beta null thalassemia (3%), SC (18%), and S-beta plus thalassemia (3%) included. The median hemoglobin level was 9.5 g/dL (range 6 to 13.5). The majority of the participants (78.2%) completed the formal neuropsychological testing virtually. All but two of the remaining participants completed in-person testing with another in-person component of the study (e.g. MRIs). Participants' median scores were all in the reference average range, except for the Oral Symbol Digits Modalities Test, a measure of processing speed, which was in the low average range. Certain participants' scores on measures of vocabulary (WASI Vocabulary), working memory (WAIS Digit Span) and executive functioning (DKEFS) were in the low average and borderline ranges. The MoCA and RUDAS scores had a strong significant correlation with each other (rho=0.5, p=0.005). The MoCA had strong significant correlations with the WASI Vocabulary scores (rho=0.5, p=0.02) and the WASI Full Scale IQ (rho=0.51, p=0.02). The RUDAS also had strong significant correlations with the WASI Vocabulary scores (rho=0.47, p=0.03) and the WASI Full Scale IQ (rho=0.52, p=0.01). There was a very strong significant correlation between RUDAS scores and hemoglobin (rho 0.74, p=0.004). Relationships were not seen between MoCA and RUDAS scores and age, sex, and SCD type. A limited number of study MRIs (12) were completed and not included in analyses at this time. Discussion/Conclusions: Pilot results are promising regarding feasibility of virtual neuropsychological testing and relationships between cognitive screening tests and gold-standard neuropsychological testing. Despite overlap between the measures, they may have different relationships with various SCD characteristics, such as anemia. Future study is needed with expanded populations for generalizability and validation.
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 | 0,007 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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 | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».