The Cost-Effectiveness of Continuous Pressure Measurement in the Diagnosis of Acute Compartment Syndrome
Bibliographic record
Abstract
BACKGROUND: The diagnosis of acute compartment syndrome (ACS) using a single-point pressure measurement device has demonstrated low specificity. Recently, sensors that allow for continuous monitoring of compartment pressure have been introduced, with improved specificity and sensitivity compared with single-point measurement. In this article, we present an economic model used to evaluate the cost-benefits of continuous pressure measurement in patients at risk for ACS. METHODS: The model used a decision-tree structure to estimate the treatment costs of ACS at 60 days and 1 year after admission and over the patient's lifetime. It assumed systematic use of the diagnostic devices for all tibial shaft and tibial plateau fractures and estimated the cost-effectiveness of continuous pressure measurement compared with noncontinuous pressure measurement by comparing costs, quality-adjusted life-years (QALYs), and length of stay (LOS). RESULTS: The improved specificity of continuous pressure measurement reduced unnecessary fasciotomies by 94%. The inflation-adjusted cost of an uncomplicated tibial fracture averaged $57,144; the performance of an unnecessary fasciotomy increased that cost by $27,790. The gain in QALYs was 0.004 per patient, with a net health benefit of 0.06 QALYs. Over a 60-day time horizon, the model showed an estimated decrease in LOS of 2.73 days, on average, per patient. The net monetary benefit was $2,789 (range, -$1,246 to $6,151) in favor of the continuous measurement, increasing to $4,085 (range, -$745 to $8,103) over the lifetime of the patient following the most conservative scenario of equal ACS grade distribution. CONCLUSIONS: Most of the ACS economic burden lies in the lack of specificity of the current diagnostic methods. The low incidence of ACS and the high risk associated with prophylactic treatment indicate that improvement in health and economic outcomes should focus on reducing the rate of unnecessary fasciotomies. LEVEL OF EVIDENCE: Economic and Decision Analysis Level IV . See Instructions for Authors for a complete description of levels of evidence.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".