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Record W3213475946 · doi:10.1182/blood-2021-150689

Cognitive Profile of Adults with Sickle Cell Disease - Cluster Analysis

2021· article· en· W3213475946 on OpenAlexaffabout
Maryline Couette, Stéphanie Forté, Damien Oudin Doglioni, Kevin H.M. Kuo, Pablo Bartolucci

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversity Health Network
Fundersnot available
KeywordsNeuropsychologyMontreal Cognitive AssessmentAnxietyCognitionMedicineHospital Anxiety and Depression ScaleNeuropsychological assessmentDepression (economics)Executive functionsEffects of sleep deprivation on cognitive performanceClinical psychologyPsychiatryPediatricsPsychologyCognitive impairment

Abstract

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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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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.212
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2021
Admission routes2
Has abstractyes

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