Bibliographic record
Abstract
BACKGROUND: Although diabetes mellitus has a strong association with the presence of depression, it is unclear whether diabetes itself increases the risk of developing depression. The objective of our study was to evaluate whether people with diabetes have a greater incidence of depression than those without diabetes. METHODS: We conducted a population-based retrospective cohort study using the administrative databases of Saskatchewan Health from 1989 to 2001. People older than 20 years with newly identified type 2 diabetes were identified by means of diagnostic codes and prescription records and compared with a nondiabetic cohort. Depression was ascertained via diagnostic codes and prescriptions for antidepressants. Cox regression analysis was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) after adjusting for age, sex, frequency of visits to physicians and presence of comorbidities. RESULTS: We identified 31 635 people with diabetes and 57 141 without. Those with diabetes were older (61.4 v. 46.8 yr; p < 0.001), were more likely to be male (55.4% v. 49.8%; p < 0.001) and had more physician visits during the year after their index date (mean 14.5 v. 5.9; p < 0.001). The incidence of new-onset depression was similar in both groups (6.5 v. 6.6 per 1000 person-years among people with and without diabetes, respectively). Similarity of risk persisted after controlling for age, sex, number of physician visits and presence of prespecified comorbidities (adjusted HR 1.04, 95% CI 0.94- 1.15). Other chronic conditions such as arthritis (HR 1.18) and stroke (HR 1.73) were associated with the onset of depression. INTERPRETATION: Using a large, population-based administrative cohort, we found little evidence that type 2 diabetes increases the risk of depression once comorbid diseases and the burden of diabetes complications were accounted for.
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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 | 0.002 |
| 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) | 0.003 | 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".