The Role of Sleep Disturbance, Depression and Anxiety in Frail Patients with AF–Gender Differences
Bibliographic record
Abstract
The aim of the study was to assess the link between anxiety and depression and frailty syndrome (FS) in patients with atrial fibrillation (AF) with regard to gender differences. MATERIAL AND METHODS: The study was conducted on 158 patients with AF (mean age 70.4 ± 7.6). The study used the hospital anxiety and depression scale (HADS-M), the Athens insomnia scale (AIS) and the Edmonton frailty scale to assess and compare anxiety, depression, and sleep disturbance between frail and non-frail patients with AF. RESULTS: < 0.001) in frail patients compared to non-frail patients. The analysis of the level of anxiety, depression and FS did not show any significant differences between the studied women and men. However, statistically, significant differences were observed when FS occurred, regardless of gender. Anxiety disorders were observed in 75.5% of patients with FS and in 16.7% without frailty, whereas depressive disorders were observed in 73.6% of frail patients and in 4.2% without frailty. In an analysis of the impact of cumulative variables on the level of frailty, the risk of FS in patients with anxiety/depression and sleep disturbance is almost 500 times higher compared to patients without anxiety/depression and sleep disturbance. The risk of frailty in patients with sleep disturbance only is thirteen times higher than in the reference group, i.e., in patients without depression/anxiety and sleep disturbances. CONCLUSIONS: Patients with AF and FS show deeper anxiety, depression and sleep disturbances. Gender does not influence the risk of frailty in AF patients. Frailty in patients with AF is associated with a higher risk of depression, sleep disturbances and anxiety.
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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 | 0.000 |
| 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 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".