Comparison of Temperamental Features, Anxiety, and Depression Levels Between Non-Cardiac Angina and Acute Coronary Syndrome
Bibliographic record
Abstract
INTRODUCTION: In many studies that are aimed to determine the psychological profile of patients admitted to the emergency unit with non-cardiac angina (NCA), it was indicated that psychiatric problems, less effective problem-solving, and alexithymia are more common in NCA compared with acute coronary syndrome (ACS) patients. In this study, aiming to find predictive psychological clinical features, we compared the temperament, anxiety, and depression scores of patients with NCA and ACS. METHODS: and independent-groups t-test between the NCA and ACS groups. RESULTS: The NCA and ACS groups were similar in terms of sociodemographic variables. There was no statistical difference between groups in HDS (p=.12) and HAS (p=.39) scores and TEMPS-A scale depressive (p=.41), cyclothymic (p=.08), hyperthymic (p=.06), and anxious (p=.29) temperament scores. But, irritable temperament scores were significantly higher in the NCS group (p=.04). CONCLUSION: We believe that our findings will provide a basis for further studies in the diagnosis and treatment of NCA by contributing to the definition of NCA patients' psychological profiles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".