Symptoms and quality of life in patients with coexistent atrial fibrillation and atrial flutter
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIMS: Atrial fibrillation (AF) and atrial flutter (AFL) are two of the most common atrial arrhythmias and often coexist. Many patients with AF or AFL are symptomatic, which impacts their quality of life (QoL). The purpose of this study was to determine whether coexistent AFL represents an added burden for AF patients. METHODS: All participants had a clinical examination and a resting ECG. Symptom burden and QoL at the baseline examination were compared between patients with and without coexistent AFL using multivariable adjusted regression models. RESULTS: Overall, 809 (20.6%) patients had a history of AFL. Patients with coexistent AFL more often had history of heart failure (28% vs 23%, p = 0.01), coronary artery disease (30% vs 26%, p = 0.007), failed therapy with antiarrhythmic drugs (44% vs 29%, p < 0.001), and more often underwent AF-related interventions (36% vs 17%, p < 0.001). They were more often symptomatic (70% vs 66%, p = 0.04) and effort intolerant (OR: 1.14; 95% CI: 1.01-1.28; p = 0.04). Documented AFL on the baseline ECG was associated with more symptoms (OR: 2.30; 95% CI: 1.26-4.20; p = 0.007). CONCLUSION: Our data indicates that patients with coexistent AF and AFL are more often symptomatic and report poorer quality of life compared to patients suffering from AF only.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it