Cost-effectiveness Analysis of Endoscopic Sphenopalatine Artery Ligation vs Arterial Embolization for Intractable Epistaxis
Bibliographic record
Abstract
IMPORTANCE: Intractable epistaxis is a common otolaryngology emergency. Transnasal endoscopic sphenopalatine artery ligation (TESPAL) and endovascular arterial embolization both provide excellent success rates, and therefore the decision to choose one over the other can be challenging. OBJECTIVE: To aid in decision making by evaluating the cost-effectiveness of TESPAL vs endovascular arterial embolization for intractable epistaxis. DESIGN, SETTING, AND PARTICIPANTS: Economic evaluation using a decision tree model with a 14-day time horizon for emergency department consultations for patients with intractable epistaxis defined as persistent bleeding despite bilateral anterior nasal packing. The economic perspective was the health care third-party payer. Effectiveness and probability data were obtained from the published medical literature. Costs were obtained from the published literature, the Centers for Medicare & Medicaid Services database, and the Healthcare Cost and Utilization Project database. Multiple sensitivity analyses were performed, including a probabilistic sensitivity analysis. Comparative treatment groups were (1) TESPAL and (2) embolization. INTERVENTIONS: TESPAL and endovascular arterial embolization. MAIN OUTCOME AND MEASURES: The primary outcome was the incremental cost-effectiveness ratio (ICER) for successful control of epistaxis. RESULTS: The reference case demonstrated that the embolization strategy was more effective but more costly compared with the TESPAL strategy: $22,324.70 per 0.70 effectiveness compared with $12,484.14 per 0.68 of effectiveness, respectively. The embolization vs TESPAL ICER was $492,028, which is higher than any willingness to pay (WTP), suggesting that TESPAL is the cost-effective decision. The sensitivity analysis demonstrated a 77.6% and 73.7% certainty that the TESPAL strategy is cost-effective at WTP thresholds of $10,000 and $50,000, respectively. CONCLUSIONS AND RELEVANCE: Results from this economic evaluation suggest that when both TESPAL and arterial embolization are viable options (based on patient and institutional factors), TESPAL is the more cost-effective treatment strategy for patients with intractable epistaxis.
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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 | 0.016 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.009 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".