Minimally Symptomatic Atrial Fibrillation Patients Derive Significant Symptom Relief Following Rate Control or Rhythm Control Therapy
Bibliographic record
Abstract
BACKGROUND: It can be challenging to convince asymptomatic to minimally symptomatic patients to pursue treatment of their atrial fibrillation (AF). We hypothesized that once in sinus rhythm, asymptomatic to minimally symptomatic patients would realize they were compensating for moderate symptoms, and that we could quantify this via the Canadian Cardiovascular Society Severity of AF (CCS-SAF) score. METHODS: All patients in our study come from the Symptom Mitigation in Atrial Fibrillation (SMART) study. Upon enrollment all patients were assigned a CCS-SAF score. Patients receiving a CCS-SAF score of 0 or 1 that elected to pursue intervention were contacted by phone and asked about their symptoms post-intervention as compared to pre-intervention. Paired t-test was used for analysis. RESULTS: Out of 800 patients in the SMART study to date, 48 patients have qualified for our phone survey and presented for follow-up in our clinic. In our cohort, the revised pre-intervention CCS-SAF score was 1.69 ± 1.36 and the post-intervention CCS-SAF score was 0.52 ± 0.80. Thirty-seven patients reported symptom improvement; those who improved were on average 72.4% improved from baseline. CONCLUSIONS: We conclude asymptomatic to minimally symptomatic AF patients benefit from therapy and should be offered intervention despite lack of symptoms.
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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".