Economic Analysis of Open Approach Versus Conventional Methods of Zygoma Fracture Repair
Bibliographic record
Abstract
BACKGROUND: As resource allocations in health care are being increasingly guided by cost containment issues, surgical professionals must consider the costs associated with various procedures. The present study identifies the financial costs attributed to the two principal treatment options available for zygoma fractures: the Gillie's method and open reduction and internal fixation (ORIF). METHODS: Patients were included if they sustained an isolated zygoma fracture and were treated within 10 days of injury using either ORIF or the Gillie's method. Those who suffered concomitant injuries or required orbital floor exploration and repair were excluded. The end point, which consisted of the total cost required to bring a patient to preinjury facial appearance and function, incorporated the cost of primary treatment and that of any secondary procedures required to correct unfavourable outcomes. RESULTS: In total, 45 patients were included: 25 were treated with Gillie's method and 20 were treated with ORIF. The cost associated with the primary treatment of zygoma fractures was found to be higher for ORIF than Gillie's method, amounting to $1,811 and $715, respectively. However, when taking into account potential repair of unsatisfactory results, the final sum totalled $1,930 and $3,725, respectively. This difference was statistically significant. CONCLUSION: To the authors' knowledge, this is the first study to objectively examine the cost of the Gillie's method and ORIF in the repair of zygoma fractures. Although the initial cost of ORIF is higher, the final cost of the Gillie's method is greater. Thus, surgeons should not allow higher initial costs to deter them from using more extensive and accurate techniques.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".