Symptoms of Depression and Anxiety in Patients With Type 2 Diabetes in a Canadian Outpatient Cardiac Rehabilitation Program
Bibliographic record
Abstract
PURPOSE: The objective of this study was to determine whether type 2 diabetes status is associated with an increased likelihood of depressed mood and anxiety in patients attending cardiac rehabilitation (CR) and to explore predictors of depression and anxiety after CR completion in patients with diabetes. METHODS: A retrospective analysis was conducted in patients who completed a 12-wk CR program between 2002 and 2016. Patients were classified as reporting normal-to-mild or moderate-to-severe symptoms of depression and anxiety using the Hospital Anxiety and Depression Scale (HADS). Logistic regression models were used to compare predictors of depression and anxiety prior to CR enrollment and investigate predictors of post-CR HADS scores among a subset of patients with diabetes. RESULTS: Data from 6746 patients (mean age 61 ± 11 yr, 18% female, 18% with diabetes) were analyzed. After controlling for known predictors of depression, patients with diabetes were not more likely to report moderate-to-severe levels of depression prior to or after completing CR. In patients with diabetes, younger age predicted moderate-to-severe depression post-CR (OR = 0.95: 95% CI, 0.93-0.98). Patients with diabetes were also more likely to report moderate-to-severe levels of anxiety after completing CR (OR = 1.45: 95% CI, 1.02-2.07). Younger age (OR = 0.93: 95% CI, 0.88-0.97) and smoking status (OR = 3.3: 95% CI, 1.15-7.06) predicted moderate-to-severe post-CR anxiety in patients with diabetes. CONCLUSIONS: Patients with diabetes, particularly younger patients who currently smoke or recently quit, are more likely to report having anxiety following CR. These patients may therefore require additional management of anxiety symptoms during CR. Larger studies of CR patients with diabetes and more variable depression and anxiety levels are needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".