Economic Evaluation of Venovenous Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome*
Bibliographic record
Abstract
OBJECTIVES: Venovenous extracorporeal membrane oxygenation is increasingly being used to support patients with severe acute respiratory distress syndrome, but its cost-effectiveness is unknown. We assessed the cost-utility of venovenous extracorporeal membrane oxygenation for severe acute respiratory distress syndrome in adults compared with standard lung protective ventilation from the perspective of the healthcare system. DESIGN: We conducted a cost-utility analysis with a cohort state transition decision model using a lifetime time horizon, 1.5% discount rate, and outcomes reported as cost per quality-adjusted life year. Literature reviews were conducted to inform the model variables. Deterministic and probabilistic sensitivity analyses were conducted to assess uncertainty in the model. SETTING: Canadian publicly funded healthcare system. PATIENTS: Hypothetical cohort of adults with severe acute respiratory distress syndrome. INTERVENTIONS: Venovenous extracorporeal membrane oxygenation or standard lung protective ventilation. MEASUREMENTS AND MAIN RESULTS: In our model, the use of venovenous extracorporeal membrane oxygenation compared with lung protective ventilation resulted in a gain of 5.2 life years and 4.05 quality-adjusted life years, at an additional lifetime cost of $145,697 Canadian dollars. The incremental cost-effectiveness ratio was $36,001/quality-adjusted life year. Sensitivity analyses show that the incremental cost-effectiveness ratio is sensitive to the efficacy of extracorporeal membrane oxygenation therapy and costs. CONCLUSIONS: Based on current data, venovenous extracorporeal membrane oxygenation is cost-effective for patients with severe acute respiratory distress syndrome. Additional evidence on the efficacy of venovenous extracorporeal membrane oxygenation for acute respiratory distress syndrome and in different subgroups of patients will allow for greater certainty in its cost-effectiveness.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".