Epidemiological and quality of life analysis of patients with ANOCA
Bibliographic record
Abstract
Introduction: A portion of patients affected by angina has ANOCA (angina with non-obstructive coronary arteries). Objectives: To determine the epidemiological and quality of life aspects of individuals with angina without coronary obstruction. Material and methods: This is an observational cross-sectional study, conducted by applying questionnaires (SAQ-7 and SF-36) in patients undergoing catheterization in a single hospital from September 2021 to June 2022, and who did not have significant coronary artery obstructions (≥50%). Results: Patients had a mean age of 59.2 years and 60.47% of the sample was female. The main comorbidities found were dyslipidemia (81.4%); hypertension (81.4%); and anxiety (55.81%). Regarding lifestyle habits, 67.44% of patients were sedentary and 34.88% were smokers. According to SAQ-7, for physical limitation, 34.88% patients were in the poor to fair grade. The quality of life had the worst results, with 86.05% of the sample presenting poor to fair. For SF-36, limitations for physical and emotional aspects had median of zero and functional capacity of 25. Discussion: ANOCA patients presented impacts mainly on quality of life, functional capacity, physical limitations, and limitations due to emotional problems, which is in agreement with literature data. Conclusion: Despite de absence of obstructive coronary lesions, patients with ANOCA have significant comorbidities and quality of life impairment, requiring atention from their physicians.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".