C67A BLITZ-AF CANCER REGISTRY: BASELINE CHARACTERISTICS OF PATIENTS WITH ATRIAL FIBRILLATION AND CANCER
Bibliographic record
Abstract
Abstract Background Evidences on atrial fibrillation (AF) in patients with cancer are limited, specifically with respect to antithrombotic therapy. Methods BLITZ-AF Cancer is a prospective, non-interventional study of the epidemiology and management of AF in patients with cancer. Patients were included from 112 cardiology units in Italy, Belgium, Netherlands, Spain, Portugal, and Ireland, based on the following criteria: age ≥18 years; documented cancer other than basal-cell or squamous-cell carcinoma of the skin diagnosed within 3 years; electrocardiographically confirmed AF within 1 year; no concomitant interventional study. Follow-up is ongoing. Results From June 26th, 2019 to Sep. 30th, 2021, 1,514 subjects were enrolled. The most frequent cancer locations were lung (14.9%), colorectal (14.1%), breast (13.9%), prostate (8.8%), and non-Hodgkin lymphoma (8.1%); 463 (30.6%) of participants had metastases. AF was first-detected in 323 (21.3%), paroxysmal in 460 (30.4%), persistent in 192 (12.7%), long-standing persistent in 33 (2.2%), and permanent in 506 (33.4%); 590 (39.0%) patients had symptoms attributable to AF. Baseline characteristics are presented in the Table. Males were more than women and almost half of the subjects was >75 years-old. Cardiovascular risk factors were common and approximately 31% had heart failure or coronary artery disease. Previous thromboembolic and haemorrhagic events had occurred in 14% and 10% of subjects, respectively. The median CHA2DS2VASc score was 3. As shown in the Figure, the prescription of oral anticoagulants, especially direct-acting ones (DOACs), rose after the cardiology assessment, while the percentage of participants without any antithrombotic therapy declined. Among 1,427 patients with non-valvular AF (i.e., no mitral stenosis or prosthetic mechanical valve), 997 (69.9%) were prescribed on DOACs at discharge/after consultation. At multivariable logistic regression analysis, variables associated with DOAC use were female sex (OR 1.58, 95% CI 1.22-2.05), age (OR 2.00, 95% CI 1.39-2.88 and OR 2.63, 95%CI 1.84-3.76, respectively, for 65-74 years and ≥75 years vs <65 years), hypertension (OR 1.43, 95%CI 1.10-1.87), long-standing persistent or permanent AF (OR 1.36, 95%CI 1.05-1.78). Haemoglobin <12 g/dL (OR 0.57, 95%CI 0.45-0.73), and planned cancer treatment (OR 0.72, 95%CI 0.57-0.92) were independently associated with a lower prescription of DOACs. Conclusions BLITZ-AF Cancer provides extensive information on a large, contemporary cohort of individuals with AF and cancer. This baseline snapshot indicates that cardiologists pursue the implementation of DOACs in these patients, although residual use of other antithrombotic therapies or lack of any thrombo-prophylaxis remains substantial.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".