Gastrointestinal comorbidities associated with atrial fibrillation
Bibliographic record
Abstract
This observational study was conducted to describe the risk of gastrointestinal (GI) events among patients with atrial fibrillation (AF). We analyzed Thomson Reuters MarketScan® data from 2005 to 2009. Subjects aged ≥18 years with ≥ 1 AF diagnosis were selected. GI events were identified from claims with a primary or secondary diagnosis code for any GI condition. The risk of GI events was assessed using cumulative incidence (new GI events/patients with AF without GI condition at baseline) and incidence rates (IRs), calculated as the number of patients with new GI events divided by patient-years of observation. In addition, the CHADS2 score was evaluated at baseline to determine the patient's risk of stroke. A total of 557,123 AF patients were identified. The mean (median) AF patient age was 68.2 years (70); 45% were female. The cumulative incidences of any GI event and dyspepsia were 40% and 19%, respectively. The corresponding IRs were 38.8 and 14.7 events per 100 patient-years. IRs of any GI events for female and male patients were 43.6 and 35.5; for patients in the age groups <65, 65-74, 75-84, and ≥85 years, IRs were 32.3, 38.9, 44.6, and 52.7; for patients with a CHADS2 score of 0, 1-2, 3-4, and 5-6, IRs were 30.3, 41.6, 56.9, and 74.5, respectively. In this large claims database, 40% of AF patients experienced a GI event, predominantly dyspepsia. Physicians should take age and comorbidities into consideration when managing AF patients.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".