Incremental Effects of Comorbidity on Quality of Life in Patients with Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To assess the added effect of comorbidity on quality of life (QOL) in psoriatic arthritis (PsA). METHODS: Between 2006 and 2012, 631 patients were recruited from the University of Toronto PsA Clinic. Using the clinical database, we ascertained the frequency of 15 comorbidities. The Medical Outcomes Study Short Form-36 (SF-36) physical (PCS) and mental component (MCS) summary scales were used to assess QOL. Linear regression analyses were conducted to estimate the magnitude of the association between number and type of comorbidities and PCS and MCS scores, after adjustment for disease-related and sociodemographic variables. RESULTS: Prevalence of comorbidity was high, with 42% of patients having 3 or more comorbid conditions. After adjustment for inflammatory disease-related and sociodemographic factors, a history of 3 or more comorbid conditions accounted for only 2% and 1% of the R(2) value explained in PCS and MCS scores, respectively. In terms of added burden, type of comorbid condition was more significant than number of comorbidities. After adjustment for disease-related and sociodemographic factors, fibromyalgia (FM), neurological disorders, and obesity jointly accounted for 6% of R(2) value explained in PCS scores, while FM and depression/anxiety jointly accounted for about 9% of the R(2) explained in MCS scores. The point decrease in PCS and MCS scores associated with each of these disorders was clinically significant. The 11 other comorbid conditions failed to achieve statistical significance in the models. CONCLUSION: The added effect of comorbidity on patient-reported physical and mental health in PsA was more related to type of comorbidity than number of comorbidities.
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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) | 0.001 | 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".