Cost‐effectiveness analysis of preoperative transfusion in patients with sickle cell disease using evidence from the <scp>TAPS</scp> trial
Bibliographic record
Abstract
The study's objective was to assess the cost-effectiveness of preoperative transfusion compared with no preoperative transfusion in patients with sickle cell disease undergoing low- or medium-risk surgery. Seventy patients with sickle cell disease (HbSS/Sß(0) thal genotypes) undergoing elective surgery participated in a multicentre randomised trial, Transfusion Alternatives Preoperatively in Sickle Cell Disease (TAPS). Here, a cost-effectiveness analysis based on evidence from that trial is presented. A decision-analytic model is used to incorporate long-term consequences of transfusions and acute chest syndrome. Costs and health benefits, expressed as quality-adjusted life years (QALYs), are reported from the 'within-trial' analysis and for the decision-analytic model. The probability of cost-effectiveness for each form of management is calculated taking into account the small sample size and other sources of uncertainty. In the range of scenarios considered in the analysis, preoperative transfusion was more effective, with the mean improvement in QALYs ranging from 0.018 to 0.206 per patient, and also less costly in all but one scenario, with the mean cost difference ranging from -£813 to £26. All scenarios suggested preoperative transfusion had a probability of cost-effectiveness >0.79 at a cost-effectiveness threshold of £20 000 per QALY.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".