Abstract P84: Antithrombotic Treatment Patterns, Hospitalizations, and Associated Costs in Acute Coronary Syndrome (ACS) Patients
Bibliographic record
Abstract
Background: We investigated real-world patterns of use of antithrombotic therapy among ACS patients to evaluate the level of undertreatment, nonadherence to medication use, recurrence of cardiovascular events, and associated costs. Methods: We analyzed the PharMetrics Integrated Claims database from 01/2004 through 12/2009. Patients ≥18 years old with ≥1 claim for ACS during a hospitalization or emergency department visit were included. Adherence to antiplatelet therapy was estimated using proportion of days covered (PDC) by drug available. Persistence was defined as continuous drug claims without a gap of ≥30 days between refills. Major outcomes were cardiovascular disease (CVD)-related hospitalization, readmission, and length of stay. We reported all-cause and CVD-related per-patient-per-month (PPPM) healthcare costs. Incidence rates of major outcomes were calculated as number of patients with an event divided by patient-years of observation, censored at the time of the first event. Results: Among the 173,573 ACS patients, mean age was 55.4 years; 36% (62,914 of 173,573) were female. During follow-up, 36.2% (62,774 of 173,573) and 5.0% (8685 of 173,573) had antiplatelet or anticoagulant prescriptions; 3.4% (5866 of 173,573) had both. Mean duration of antiplatelet therapy was 457 days. At 1.5, 6, and 12 months, mean PDCs were 0.93, 0.78, and 0.70. Kaplan-Meier rates of persistence after 6 and 12 months were 0.66 and 0.47. The incidence rate of CVD-related hospitalization was 0.22 events per patient-year of observation. The rates of CVD-related and all-cause hospital readmissions were 0.32 and 0.41 events per patient-year; mean length of stay was 7.1 and 6.8 days per rehospitalization. All-cause healthcare cost PPPM was $2419; 63% ($1518 of $2419) of total all-cause costs PPPM were associated with claims for CVD-related hospitalization. Conclusions: This observational study suggests undertreatment in secondary prevention of ACS. Persistence with antiplatelet therapy dropped dramatically by 6 months after the initial event. ACS patients have a high risk of repeated CVD-related hospitalizations that incur high costs to the healthcare system. Interventions to improve long-term use of evidence-based therapies may improve ACS management.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".