Cost-effectiveness of craniotomy versus decompressive craniectomy for UK patients with traumatic acute subdural haematoma
Bibliographic record
Abstract
OBJECTIVE: To estimate the cost-effectiveness of craniotomy, compared with decompressive craniectomy (DC) in UK patients undergoing evacuation of acute subdural haematoma (ASDH). DESIGN: Economic evaluation undertaken using health resource use and outcome data from the 12-month multicentre, pragmatic, parallel-group, randomised, Randomised Evaluation of Surgery with Craniectomy for Patients Undergoing Evacuation-ASDH trial. SETTING: UK secondary care. PARTICIPANTS: 248 UK patients undergoing surgery for traumatic ASDH were randomised to craniotomy (N=126) or DC (N=122). INTERVENTIONS: Surgical evacuation via craniotomy (bone flap replaced) or DC (bone flap left out with a view to replace later: cranioplasty surgery). MAIN OUTCOME MEASURES: In the base-case analysis, costs were estimated from a National Health Service and Personal Social Services perspective. Outcomes were assessed via the quality-adjusted life-years (QALY) derived from the EuroQoL 5-Dimension 5-Level questionnaire (cost-utility analysis) and the Extended Glasgow Outcome Scale (GOSE) (cost-effectiveness analysis). Multiple imputation and regression analyses were conducted to estimate the mean incremental cost and effect of craniotomy compared with DC. The most cost-effective option was selected, irrespective of the level of statistical significance as is argued by economists. RESULTS: In the cost-utility analysis, the mean incremental cost of craniotomy compared with DC was estimated to be -£5520 (95% CI -£18 060 to £7020) with a mean QALY gain of 0.093 (95% CI 0.029 to 0.156). In the cost-effectiveness analysis, the mean incremental cost was estimated to be -£4536 (95% CI -£17 374 to £8301) with an OR of 1.682 (95% CI 0.995 to 2.842) for a favourable outcome on the GOSE. CONCLUSIONS: In a UK population with traumatic ASDH, craniotomy was estimated to be cost-effective compared with DC: craniotomy was estimated to have a lower mean cost, higher mean QALY gain and higher probability of a more favourable outcome on the GOSE (though not all estimated differences between the two approaches were statistically significant). ETHICS: Ethical approval for the trial was obtained from the North West-Haydock Research Ethics Committee in the UK on 17 July 2014 (14/NW/1076). TRIAL REGISTRATION NUMBER: ISRCTN87370545.
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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 | 0.004 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".