Depression among predictors of intermittent claudication: A cross-sectional study
Bibliographic record
Abstract
Purpose: The aim of the present cross-sectional study was to investigate the relationship between depression and intermittent claudication (IC), independently of traditional risk factors. Main methods: The sample consisted of 300 individuals (M age = 65.3 ± 8.7 years, 61.0% female) recruited from the offices of 33 general practitioners. Participants' medical history and the presence of major cardiovascular risk factors were recorded. Participants completed the Edinburgh Claudication Questionnaire. The role of depression (assessed by a shortened version of the Beck Depression Inventory) in predicting IC was examined using a binary logistic regression analysis - controlled for sex, age, hypertonia, diabetes, smoking, hypercholesterinemia, hazardous drinking, and body mass index (BMI). Results: The descriptive data indicated that the prevalence of depression was 57.9% in the IC subgroup and 16.1% in those free of IC. The bivariate analyses indicated that hypercholesterinemia, smoking, hazardous drinking, BMI, and depression were significantly associated with IC. Male sex and age showed a trend toward being a significant correlate of IC. Results of the multivariate analyses indicated that depressive symptomatology was significant in predicting IC (OR: 1.08 (1.05-1.11)), even after controlling for lifestyle and traditional risk factors such as smoking, hazardous drinking, and BMI. Among traditional risk factors, smoking (OR: 2.44 (1.26-4.74)), hazardous drinking (OR: 1.19 (1.02-1.40)), and hypercholesterinemia (OR: 2.17 (1.26-3.75)) showed a significant, positive relationship with IC. Conclusions: These results underscore the importance of a multidisciplinary approach that focuses on supporting health-related behavioral changes and managing mental health symptoms when providing care for patients with IC.
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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) | 0.000 | 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) | 0.002 | 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 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".