Cognitive Profile of Adults with Sickle Cell Disease - Cluster Analysis
Notice bibliographique
Résumé
Abstract Background: Published literature on cognitive functioning in adults with sickle cell disease (SCD) is sparse when compared to children. A few reports describe deficits in processing speed and executive functioning. Some studies suggest that these deficits are more severe in patients with silent cerebral infarcts (SCI). Even in the absence of radiological evidence of ischemic injury, some cognitive deficits have been depicted in adults . We hypothesize that in SCD adults, the cognitive profile varies with the presence of ischemic injury (SCI or overt stroke). The aims of this study were 1) to describe the neuropsychological profiles of SCD adults, and 2) to characterize clusters of patients with similar cognitive profiles. Methods: We conducted a retrospective analysis of all consecutive SCD adults who underwent comprehensive neuropsychological assessment during routine care at the UMGGR clinic at Henri Mondor Hospital, Créteil (France), between January 2017 and April 2021. The Montreal Cognitive Assessment (MoCA) and Hospital Anxiety and Depression Scale (HADS) were used for cognitive disorder, anxiety and depression screening, respectively. The cognitive battery combined standardized neuropsychological tests with established clinical utility and validity. Educational attainment was scored based on the number of years of schooling for the highest completed diploma. Principal component analysis was performed. ANOVA was used to compare patients' characteristics between clusters. Results: 80 patients, median age 36.5 [range 19-63] years were included. 40 (50.0%) were male. Genotype distribution was 62 patients (77.5%) with SS/Sbeta 0, 12 (15.0%) with SC and 6 (7.5%) with Sbeta +. On Principal Component Analysis, a 5-factor model presented the best fit (Bartlett's sphericity test (χ²(171)=1174; p<0.001)), explaining 71.8% of the variance in neuropsychological scores. The first factor encompassed tests specifically assessing visual attention/visual organization (right hemisphere). The second included tests for mental/cognitive control (frontal lobe), the third tests of selective inhibition/attention (fronto-parietal), the fourth tests for language/memory (left temporal lobe) and the last referred to shifting skill (sub-cortical loop). On hierarchical classification, 3 different clusters emerged: 32 patients in cluster 1, 32 in cluster 2 and 16 in cluster 3. Cluster 1 had a lower mean educational level (F(2,77) = 15,65; p<0,001). Cluster 1 showed the lowest mean MoCA score (20.0/30.0), relative to cluster 2 and 3 (24.6 and 26.4; p<0.001 and p<0.001, respectively). Cluster 1 patients presented deficits on all five factors. Cluster 2 patients compared to cluster 3 were altered in 4 factors (factors 1-4), but to a lesser extent than cluster 1. Processing speed was slower and some frontal-executive deficits were present in cluster 2 compared to cluster 3. There was no statistical difference between clusters in terms of ethnic origins. There was a trend for the presence of more cerebral vasculopathy in cluster 1 (chi2; p=0.06). Regarding stroke, 70% occurred during childhood in cluster 1, whereas 70% during adulthood in cluster 2, and 100% during adulthood in cluster 3. Conclusions: Overall, these results suggest at least three different cognitive profiles in adults with SCD: 1) few or no cognitive deficits (cluster 3), 2) some cognitive impairment with a sub-cortical cognitive profile (cluster 2) and 3) more global cognitive impairment with cortical/sub-cortical profile and specific deficits of memory, language and constructional praxis, depending on the location of prior overt neurological events (cluster 1). To reduce the long-term cognitive morbidity of SCD, patients can be identified by their distinct cognitive profiles and neurorehabilitation tailored to their unique profile should be applied. The large proportion of childhood stroke in patients with global cognitive impairment in contrast with majority of those with milder to no cognitive impairment having had their stroke in adulthood emphasize the crucial importance of preventing early childhood stroke and implementing early neurorehabilitation. Disclosures Forté: Canadian Hematology Society: Research Funding; Pfizer: Research Funding; Novartis: Honoraria. Kuo: Pfizer: Consultancy, Research Funding; Bluebird Bio: Consultancy; Novartis: Consultancy, Honoraria; Apellis: Consultancy; Alexion: Consultancy, Honoraria; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Bioverativ: Membership on an entity's Board of Directors or advisory committees. Bartolucci: Jazz Pharma: Other: Lecture fees; AGIOS: Consultancy; Emmaus: Consultancy; GBT: Consultancy; F. Hoffmann-La Roche Ltd: Consultancy; Hemanext: Consultancy; INNOVHEM: Other: Co-founder; Bluebird: Consultancy, Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Lecture fees, Steering committee, Research Funding; Fabre Foundation: Research Funding; Addmedica: Consultancy, Other: Lecture fees, Research Funding.
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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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».