Coronary Slow Flow Is Associated with Anxiety and Depression but Not Adverse Childhood Experiences and Alexithymia
Bibliographic record
Abstract
Objective: The literature concerning the association between coronary slow flow (CSF) and anxiety and depression is controversial. Furthermore; there is no existing data in the literature on the potential association between CSF and adverse childhood experiences or alexithymia. Methods: The participants underwent coronary angiography through femoral access. Coronary artery blood flow rate was evaluated quantitatively for each coronary artery according to the Thrombolysis in Myocardial Infarction frame count (TFC) method. CSF was diagnosed as a corrected TFC value >27 in at least one coronary artery during the imaging. Symptoms of anxiety and depression were assessed through the Hospital Anxiety and Depression Scale (HADS). Alexithymia and ACE were evaluated by the Twenty-item Toronto Alexithymia Scale (TAS-20) and the Childhood Trauma Questionnaire (CTQ). Results: The study participants were categorized into two groups: normal coronary flow (n = 58) and CSF (n = 18). Total HADS score; HADS anxiety subscale (HADS-A) score; and HADS depression subscale (HADS-D) score were determined as significant factors associated with CSF in univariate logistic regression analysis. However; the TAS-20 and CTQ scores showed no significant association with CSF. Multivariate regression analysis performed in separate models demonstrated that total HADS score (OR: 1.27; 95 CI%: 1.08–1.50; p = 0.003); HADS-A score (OR: 1.25; 95 CI%: 1.03–1.51; p = 0.019); and HADS-D score (OR: 1.36; 95 CI%: 1.06–1.74; p = 0.014) were independently associated with CSF in multivariate logistic regression analysis. Conclusions: Neither alexithymia nor ACE was associated with CSF. On the other hand; measures of both anxiety and depression assessed through HADS were independently associated with CSF. Future studies should address the major limitations of this study; such as the limited sample size; lack of structured diagnostic interview by a psychiatrist; and the lack of establishment of causality
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".