Comorbidities in Patients with Rheumatoid Arthritis and Their Association with Patient-reported Outcomes: Results of Claims Data Linked to Questionnaire Survey
Bibliographic record
Abstract
OBJECTIVE: To investigate the prevalence of comorbidities in a population-based cohort of persons with rheumatoid arthritis (RA) compared to matched controls and to examine their association with patient-reported outcomes in a survey sample. METHODS: Data of 96,921 persons with RA [International Classification of Diseases, 10th ed (ICD-10) M05/M06] and 484,605 age- and sex-matched controls without RA of a German statutory health fund were studied regarding 26 selected comorbidities (ICD-10). A self-reported questionnaire, comprising joint counts [(tender joint count (TJC), swollen joint count (SJC)], functional status (Hannover Functional Ability Questionnaire), effect of the disease (Rheumatoid Arthritis Impact of Disease), and well-being (World Health Organization 5-item Well-Being Index; WHO-5) was sent to a random sample of 6193 persons with RA, of whom 3184 responded. For respondents who confirmed their RA (n = 2535), associations between comorbidities and patient-reported outcomes were analyzed by multivariable linear regression. RESULTS: Compared to controls, all investigated comorbidities were more frequent in persons with RA (mean age 63 yrs, 80% female). In addition to cardiovascular risk factors, the most common were osteoarthritis (44% vs 21%), depression (32% vs 20%), and osteoporosis (26% vs 9%). Among the survey respondents, 87% of those with 0-1 comorbidity but only 77% of those with ≥ 8 comorbidities were treated by rheumatologists. Increasing numbers of comorbidities were associated with poorer values for TJC, SJC, function, and WHO-5. CONCLUSION: Compared to a matched population, persons with RA present with increased prevalence of numerous comorbidities. Patients with RA and multimorbidity are at risk of insufficient rheumatological care and poorer patient-reported outcomes.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 0.000 |
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.
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".