Objective. Screening for cognitive impairment in systemic lupus erythematosus (SLE) conventionally relies on the American College of Rheumatology (ACR) neuropsychologic battery (NB), which is not universally available. To develop a more accessible screening approach, we assessed validity of the Automated Neuropsychological Assessment Metrics (ANAM). Using the ACR NB as the gold standard for cognitive impairment classification, the objectives were 1) to measure overall discriminative validity of the ANAM for cognitive impairment versus no cognitive impairment, 2) to identify ANAM subtests and scores that best differentiate patients with cognitive impairment from those with no cognitive impairment, and 3) to derive ANAM composite indices and cutoffs. Methods. A total of 211 consecutive adult patients, female and male, with SLE were administered the ANAM and ACR NB. 1) For overall discriminative validity of the ANAM, we compared patients with cognitive impairment versus those with no cognitive impairment on 4 scores. 2) Six ANAM models using different scores were developed, and the most discriminatory subtests were selected using logistic regression analyses. The area under the receiver operating characteristic curve (AUC) was calculated to establish ANAM validity against the ACR NB. 3) ANAM composite indices and cutoffs were derived for the best models, and sensitivities and specificities were calculated. Results. Patients with no cognitive impairment performed better on most ANAM subtests, supporting ANAM's discriminative validity. Cognitive impairment could be accurately identified by selected ANAM subtests with top models, demonstrating excellent AUCs of 81% and 84%. Derived composite indices and cutoffs demonstrated sensitivity of 78-80% and specificity of 70%. Conclusion. This study provides support for ANAM's discriminative validity for cognitive impairment and utility for cognitive screening in adult SLE. Derived composite indices and cutoffs enhance clinical applicability.
Objective To phenotype SLE based on symptom burden (disease damage, system involvement and patient reported outcomes), with a specific focus on objective and subjective cognitive function. Methods SLE patients aged 18–65 underwent objective cognitive assessment using the ACR Neuropsychological Battery (ACR-NB) and data was collected on demographic and clinical variables, disease burden/activity, health related quality of life (HRQoL), depression, anxiety, fatigue and perceived cognitive deficits. Similarity network fusion (SNF) was used to identify patient subtypes. Differences between the subtypes were evaluated using Kruskal-Wallis and chi-square tests. Results Of the 238 patients, 90% were female, mean age 41 ± 12 and disease duration 14 ± 10 years at the study visit. The SNF analysis defined two subtypes (A and B) with distinct patterns in objective and subjective cognitive function, disease burden/damage, HRQoL, anxiety and depression. Subtype A performed worst on all significantly different tests of objective cognitive function (p < 0.03) compared with subtype B. Subtype A also, had greater levels of subjective cognitive function (p < 0.001), disease burden/damage (p < 0.04), HRQoL (p < 0.001) and psychiatric measures (p < 0.001) compared with subtype B. Conclusion This study demonstrates the complexity of cognitive impairment (CI) in SLE and that individual, multi-factorial phenotypes exist. Those with greater disease burden, from SLE specific factors or other factors associated with chronic conditions, report poorer cognitive functioning and perform worse on objective cognitive measures. By exploring different ways of phenotyping SLE we may better define CI in SLE. Ultimately, this will aid our understanding of personalised CI trajectories and identification of appropriate treatments.
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