Cost‐utility analysis of radiofrequency ablation versus optimal medical therapy in managing supraventricular tachycardia among Filipinos
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Bibliographic record
Abstract
Background: Radiofrequency ablation (RFA) is the standard of care in the management of supraventricular tachycardia (SVT). Its cost-effectiveness in an emerging Asian country has not been studied. Objectives: A cost-utility analysis of RFA versus optimal medical therapy (OMT) among Filipinos with SVT was conducted using the public healthcare provider's perspective. Methods: A simulation cohort using a lifetime Markov model was constructed using patient interviews, a review of literature, and expert consensus. Three basic health states were defined: stable, SVT recurrence, and death. The incremental cost per quality-adjusted life year (ICER) was determined for both arms. Utilities for the entry states were derived from patient interviews using the EQ5D-5L tool; utilities for other health states were taken from publications. Costs were assessed from the healthcare payer perspective. A sensitivity analysis was done. Results: Base case analysis showed that RFA versus OMT is both highly cost-effective at 5 years and over a lifetime. RFA at 5 years costs about PhP276,913.58 (USD5,446) versus OMT of PhP151,550.95 (USD2,981) per patient. Discounted lifetime costs were PhP280,770.32 (USD5,522) for RFA, versus PhP259,549.74 (USD5,105) for OMT. There was improved quality of life with RFA (8.1 vs. 5.7 QALYs per patient). The 5-year and lifetime incremental cost-effectiveness ratios were PhP148,741.40 (USD2,926) and Php15,000 (USD295), respectively. Sensitivity analysis showed 56.7% of simulations for RFA fell below a GDP-benchmarked willingness-to-pay (WTP) threshold. Conclusion: Despite the initial higher cost, RFA versus OMT for SVT is highly cost-effective from the Philippine public health payer's perspective.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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 it