Cost Outcomes of Virtual Surgical Planning in Head and Neck Reconstruction: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Virtual surgical planning (VSP) is an emerging method in head and neck reconstruction with demonstrated benefits, however, its economic viability is supported with mixed evidence. METHODS: A structured search was performed in five electronic databases. Studies that performed an economic evaluation on VSP in head and neck reconstruction were included. Data regarding VSP workflow, costs, and variables influencing costs were recorded and synthesized. RESULTS: Eighteen studies met the final inclusion criteria (n = 733). Fourteen out of 18 studies (78%) found that VSP either generated cost savings or was comparable to freehand surgery (FHS). The majority of cost savings were generated from reduced OR times and LOS/LOH. In addition, greater cost savings were associated with in-house VSP workflows compared to those that are outsourced. CONCLUSION: VSP is potentially cost-beneficial compared to traditional unplanned surgery, however, substantial heterogeneity amongst methods and outcome measures impedes the generalizability of these findings. TRIAL REGISTRATION: PROSPERO: CRD42024504398.
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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 | 0.008 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".