Potential lifetime cost-effectiveness of catheter-based renal sympathetic denervation in patients with resistant hypertension
Bibliographic record
Abstract
AIMS: Recent studies have demonstrated the safety and efficacy of catheter-based renal sympathetic denervation (RDN) for the treatment of resistant hypertension. We aimed to determine the cost-effectiveness of this approach separately for men and women of different ages. METHODS AND RESULTS: A Markov state-transition model accounting for costs, life-years, quality-adjusted life-years (QALYs), and incremental cost-effectiveness was developed to compare RDN with best medical therapy (BMT) in patients with resistant hypertension. The model ran from age 30 to 100 years or death, with a cycle length of 1 year. The efficacy of RDN was modelled as a reduction in the risk of hypertension-related disease events and death. Analyses were conducted from a payer's perspective. Costs and QALYs were discounted at 3% annually. Both deterministic and probabilistic sensitivity analyses were performed. When compared with BMT, RDN gained 0.98 QALYs in men and 0.88 QALYs in women 60 years of age at an additional cost of €2589 and €2044, respectively. As the incremental cost-effectiveness ratios increased with patient age, RDN consistently yielded more QALYs at lower costs in lower age groups. Considering a willingness-to-pay threshold of €35 000/QALY, there was a 95% probability that RDN would remain cost-effective up to an age of 78 and 76 years in men and women, respectively. Cost-effectiveness was influenced mostly by the magnitude of effect of RDN on systolic blood pressure, the rate of RDN non-responders, and the procedure costs of RDN. CONCLUSION: Renal sympathetic denervation is a cost-effective intervention for patients with resistant hypertension. Earlier treatment produces better cost-effectiveness ratios.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".