Onset of depression and anxiety among patients with gout after diagnosis: a population-based incident cohort study
Bibliographic record
Abstract
BACKGROUND: Gout may be associated with an increased incidence of mental health disorders, however, published findings have been limited and inconsistent. Therefore, our objective was to conduct a population-based cohort study to evaluate the incidence of depression and anxiety after gout diagnosis. METHODS: We used linked population-based administrative health data in British Columbia, Canada that includes information on demographics, outpatient visits, and inpatient visits from the period of January 1, 1990 to March 31, 2018. We assessed depression and anxiety using validated International Classification of Diseases, 9th and 10th Revision coding algorithms. We applied multivariable Cox proportional hazard models to evaluate incident depression and anxiety among patients with gout in comparison to non-gout controls, adjusting for age, sex, neighbourhood income quintile, residence, comorbidities, and health care utilization. RESULTS: We included 157,426 incident cases of gout (60.2% male; mean age 57.1 years) and 157,426 non-gout controls (60.2% male; mean age 56.9 years). The incidence rate of depression among individuals with gout and non-gout controls was 12.9 (95% confidence interval [CI] 12.7-13.2) and 11.1 (95% CI 10.9-11.4) per 1000 person-years, respectively. The incidence rate of anxiety for those with gout was 5.4 (95% CI 5.3-5.5) per 1000 person-years and for non-gout controls was 4.6 (95% CI 4.4-4.7) per 1000 person-years. Individuals with gout had an increased onset of depression (adjusted hazard ratio [aHR], 1.08; 95% CI 1.05-1.11) and anxiety (aHR, 1.10; 95% CI 1.05-1.14) compared to non-gout controls. CONCLUSION: Our population-based study shows an increased incidence of depression and anxiety following gout diagnosis in comparison to non-gout controls. Findings suggest the importance of considering psychiatric impacts in addition to the physical impacts of gout.
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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".