P183 Cognitive function in polymyalgia rheumatica
Bibliographic record
Abstract
Abstract Background/Aims Over the past decade our understanding of the prevalence, and indeed impact, of cognitive impairment in rheumatic diseases has increased. An aging population coupled with systemic inflammation have been postulated as key drivers of increased cognitive decline in these conditions. Intact cognitive function is imperative not only for quality of life and maintenance of one’s functional capacity, but also for the successful therapeutic management of disease, namely the adherence to treatment regimens. The prevalence of cognitive impairment in community dwelling adults above the age of 65 in Ireland has been estimated at 13%.1 To date, the prevalence of cognitive impairment in PMR has not been studied. The aim of this research is therefore to explore the prevalence and potential associated factors of cognitive impairment in those with PMR. Methods Patients with a diagnosis of PMR (fulfilling the 2012 EULAR/ACR Provisional Classification Criteria) who were in clinical remission and on active treatment with glucocorticoids were recruited from two centres. Patients were >3 months and <12 months from diagnosis. Cognitive function was evaluated using the Montreal Cognitive Assessment (MoCA) test which was conducted by trained interviewers. Cognitive impairment was defined by the previously validated MoCA cut-off score of < 26. Demographics, clinical and laboratory data, in addition to patient reported outcomes (PROs) were collected. PROs included anxiety using the Generalised Anxiety Disorder Assessment (GAD-7), mood using the Patient Health Questionnaire (PHQ-9), fatigue using the Functional Assessment of Chronic Illness Therapy-Fatigue Scale (FACIT-F), pain using the visual analogue scale (VAS) and overall health-related quality of life using the Health Assessment Questionnaire-Disability Index (HAQ-DI). The associations between categorical variables were compared using the -test or Fishers exact test. The association between continuous variables and categorical variables were assessed using the Kruskal-Wallis test. Correlations were calculated using Pearson’s r. All analyses were conducted using R (R Core Team, 2022). A p-value of < 0.05 was considered as statistically significant. Results 51 consecutive patients with PMR were recruited, of which 56.9% (n = 29) were female. 70.6% (n = 36) of patients were cognitively impaired, with visuo-spatial, delayed recall and abstraction the most commonly affected cognitive domains. Interestingly, those with cognitive impairment had a younger age, versus those without (p = 0.514). Although not statistically significant, median BMI, anxiety, depression and pain scores were all higher in those who were cognitively impaired. Moreover, median fatigue scores were also worse in the cognitively impaired group. No statistically significant difference in serum markers was observed. Conclusion This study demonstrates that the burden of cognitive impairment in PMR is significant, and is markedly higher than that observed usually at population level. Future studies exploring specific etiologic contributors are needed. Disclosure P. Harkins: Grants/research support; British Society for Rheumatology. S. Cowley: None. R. Harrington: None. D. Kane: None. R. Conway: None.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".