Validitation of the Rowland Universal Dementia Assessment Scale (RUDAS) for the Detection of Cognitive Impairment Among Adults with Sickle Cell Disease
Notice bibliographique
Résumé
Background Adults with sickle cell disease (SCD) are at higher risk of cognitive disorder compared to the general population. The American Society of Hematology recommends cognitive screening; however, optimal surveillance strategies have not been established. The Rowland Universal Dementia Assessment Scale (RUDAS) is a short questionnaire that was specifically developed in culturally diverse populations. Objective To determine whether the RUDAS is a valid screening tool to detect cognitive disorder among adults with SCD. Methods This cross-sectional study was conducted between 2018 and 2023 in 3 large centres of excellence of SCD (Centre Hospitalier de l'Université de Montréal [CHUM] in Montréal, and University Health Network [UHN] in Toronto, Canada, and APHP-Henri Mondor French Red Blood Cell Coordinating Referral Center, Créteil, France). All outpatients (pts), ≥18 years-old, of all SCD genotypes, with documented RUDAS screening were included, unless they were unable to provide informed consent. The French or the English versions of the RUDAS were used for cognitive screening, according to pts' preference. RUDAS was adjusted for education (+1 point) if the number of years of education was ≤12. At CHUM, pts were assessed comprehensively by a multidisciplinary neurovascular team. Diagnosis of major or mild cognitive disorder was determined according to VasCog diagnostic criteria. Multistep validation was performed by an expert in measures (SB), and included reliability of repeat testing and interrater reliability, the partial credit model, and “gold standard” (criterion) validation of the RUDAS against formal diagnosis of cognitive disorder. Sensitivity (Ss), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV) were calculated. For reliability testing, only 145 pts had repeat testing within 3-6 months and 92 had repeat scoring by an independent assessor. For the criterion validation, only the 117 pts evaluated at the CHUM were included in the analysis. Results A total of 440 pts met the inclusion criteria: 173 (39.3%) from CHUM, 171 from UHN (38.9%) and 96 from APHP-Henri Mondor (21.8 %); 248 were women (56.4 %) and the median [range] age was 34 [18-75] years old. Median [range] RUDAS score was 26 [16-30]. For reliability testing, the correlation coefficient for repeat RUDAS testing after 3 to 6 months was 0.6. Scores improved from a median of 26.0 [16-30] to 28.0 [19-20], suggesting a potential learning effect. The interrater reliability coefficient was 1.0 Latent class analyses using 2 classes had the best fit, compared to 3 or 4 classes, based on lowest Akaike information and Bayes information criterion values. The entropy value for this model was acceptable (0.89). RUDAS was able to discriminate two clinically distinct groups. Pts in one group had overall lower RUDAS performance (median=22 [16-27] vs. 27[18-30]), were also older, more likely to have a history of stroke, common vascular risk markers and factors, lower kidney function, lower educational attainment and higher unemployment. Clinical validity was tested by comparing the RUDAS to formal neurological and cognitive assessment in the CHUM group. The subgroup of patients who had a formal cognitive evaluation (N = 117) was divided into two groups: those with (N=42) and those without (N=75) a confirmed diagnosis of major or minor cognitive disorder. The mean RUDAS scores differed significantly in those two groups (26.5 ± 2.8 vs. 28.5 ± 2.6, t=3.5, p<0.001). A RUDAS cut-off of <27/30 detected cognitive disorder with a 50% Ss, 83% Sp, 62% PPV and a 75% NPV. When adjusted for education level, a RUDAS score of <27/30 had a 45% Ss, 89% Sp, 70% PPV and 74% NPV. Conclusion The RUDAS is an accessible, valid, and scalable screening tool for systematic cognitive surveillance of adults with SCD. It can be administered in 6 minutes by health care professionals (e.g., nurses, physicians). It has modest sensitivity, but good specificity, especially when adjusted for educational level. It could therefore assist healthcare professionals caring for adults with SCD in the detection of patients in need of specific interventions, comprehensive neurocognitive assessment, and educative or professional accommodations. Future research should evaluate the utility of the RUDAS for longitudinal surveillance of cognitive disorders and whether adaptations could improve its sensitivity in adults with SCD.
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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 | 0,003 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».