Daily costs of hospitalization in non-valvular atrial fibrillation patients treated with anticoagulant therapy
Bibliographic record
Abstract
BACKGROUND: Atrial fibrillation (AF) is the most common cardiac rhythm disturbance in the US, with an estimated prevalence of 2.7-6.1 million persons in 2010. OBJECTIVE: This study evaluates the progression of daily hospitalization costs among non-valvular atrial fibrillation (NVAF) patients treated with anticoagulant therapy. METHODS: A claims analysis was conducted with Premier Perspective Comparative Hospital Database records from January 2009-March 2013. Patients of 18 years or older who were diagnosed with NVAF and used anticoagulant therapy were studied. Treatment patterns and mean daily costs of hospitalization per patient as well as total costs of hospitalization were reported. Comparisons of mean daily costs with those of the previous day were presented to identify statistical cost differences between hospitalization days. RESULTS: A total of 375,560 patients were identified; 67,017 with AF as admitting/primary diagnosis, and 308,543 with AF as a secondary diagnosis. The mean age of the overall population, primary AF diagnosis cohort, and secondary AF diagnosis cohort was 73.8, 67.9, and 75.0 years, while their proportion of females was 46.3%, 45.6%, and 46.5%, respectively. The mean length of stay was 6.8 days, 3.7 days, and 7.5 days for the overall population, the primary AF diagnosis cohort, and the secondary AF diagnosis cohort, respectively. For all cohorts, mean daily costs stabilized on the third day (overall population: $2103; primary AF diagnosis cohort: $1505; secondary AF diagnosis cohort: $2208). LIMITATIONS: Claims data may have contained inaccuracies or omissions in coded procedures, diagnoses, or pharmacy claims. CONCLUSION: The study showed that daily hospitalization costs for NVAF patients stabilized on the third day of hospitalization and that any reduction or prolongation in hospital length of stay could have a significant impact on the cost burden associated with AF.
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 | 0.004 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".