Mortality in depressed and non-depressed primary care Swedish patients: a 12-year follow-up cohort study
Bibliographic record
Abstract
BACKGROUND: Data regarding mortality among depressed patients in Swedish primary care is limited. OBJECTIVES: We compared mortality in a cohort of depressed and non-depressed patients at long-term follow-up and compared these values with standardized mortality rates (SMRs) in the Swedish population. Hazards ratios (HRs) for the relationship between death and depression, psychosocial factors and lifestyle were analysed, and we explored the proportion of unnatural causes of deaths. METHODS: Mortality was studied in a cohort of 124 depressed and 280 non-depressed patients 12 years after being diagnosed with depression in primary care. Mortality and the mortality rates and SMRs in depressed and non-depressed patients were compared by gender. Cox regression was applied to calculate HRs for the risk of dying for explanatory variables, including depression, psychosocial factors and lifestyle. RESULTS: A larger number of depressed patients, 11% (n = 14), compared with non-depressed patients, 4% (n = 12), died (P = 0.008), with significantly higher values among depressed men (P = 0.014). SMRs did not differ from those of the Swedish population. Depression was the only variable associated with a significantly elevated risk of death (HR, 3.34; 95% CI, 1.38-8.08). Nearly one-third of deaths had unnatural causes when alcohol-related deaths were included. CONCLUSION: This study underlines the importance of careful follow-up of all depressed patients' mental and physical health and the intervention on unhealthy lifestyles. Large primary care database studies are needed to explore the association between depression, co-morbid somatic diseases, lifestyle and mortality.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".