Evolution of depression during rehabilitation program in patients with cardiovascular diseases
Bibliographic record
Abstract
Background: Cardiovascular diseases represent the main cause of death in the world. Rehabilitation through exercise is more and more used in cardiac patients. Given that these patients suffer from depressive symptoms, the risk of having recurrent cardiovascular problems increases. Thus, the aim of this study is to identify the effects of a rehabilitation program on the physiological and psychological parameters; with a particular attention on the depression scores between the scales.Methods: Twenty-eight cardiac patients participated in this study during a cardiovascular rehabilitation program. They are tested at their entry and at their exit with an evaluation of their physical fitness on an electromagnetic cycle ergometer and by four depression scales (Beck Depression Inventory, Hospital Anxiety and Depression Scale (HADS), Center for Epidemiologic Studies – Depression and Geriatric Depression Screening).Results: We observe that 21.4–50% of these patients have depressive symptoms, according to depression scales. The women have depression scores significantly higher than the men. The rehabilitation program improves their maximal oxygen consumption and their maximal aerobic power. At the end of the rehabilitation program, our analysis identifies a significant decrease in the depression score for the HADS. Regardless of the physical deconditioning level and of the improvement of the maximal oxygen consumption, our results show an effect of the rehabilitation program on the depression scores. No correlation between the physical deconditioning and the different depression scores is observed.Conclusions: This study shows the importance of measuring depression and its severity to improve the care of patients. Our findings show that between 21.4% and 50% of patients have depressive symptoms which challenges the categorical approach of the self-report depression scales.Implications for rehabilitationDepression and cardiovascular diseases have an impact on the patients’ physical fitness.The rehabilitation program, primarily based around exercise, reduces depressive symptoms.As soon as cardiovascular diseases patients enter in a rehabilitation program, the depression should be measured by a psychologist.Taking into account the depressive symptoms of the patients as soon as their cardiac event occurs makes it possible to improve the care of patients.
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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 | 0.002 |
| 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) | 0.001 | 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".