Economic Evaluation of Intraoperative Cone Beam CT-Based Navigation for the Placement of Spinal Pedicle Screws: A Patient Level Cost Effectiveness Analysis
Bibliographic record
Abstract
Introduction Pedicle screws are routinely used in contemporary spinal surgery. Screw misplacement is however correlated with potential adverse events. The goal of this study is to perform an economic evaluation looking specifically at the misplaced screws leading to reoperation secondary to neurological deficits or biomechanical concerns. Material and Methods A patient-level data cost-effectiveness analysis from the hospital perspective was conducted based on a single center observational study of prospectively collected data to determine the value of a navigation system coupled with intraoperative 3D imaging (O-arm Imaging and the StealthStation S7 Navigation Systems, Medtronic, Louisville, CO) in adult spinal surgery. The data source was a consecutive series of patients treated with the aid of computer-assisted surgery (treatment group) compared with a matched historical cohort of patients treated with conventional methods (control group). The primary effectiveness measure studied was the number of reoperations for misplaced screws. Results A total of 5,132 pedicle screws were inserted in 502 patients during the study period; 2,682 screws in 253 patients in the treatment group, and 2,450 screws in 249 patients in the control group. Overall accuracy rates were 95.2% for the treatment group and 86.9% for the control group. Two patients (0.8%) required a revision surgery in the treatment group (both within the same admission) compared with 15 patients (6%) in the control group (nine within the same admission and six within 1 year during a subsequent admission). Costs of the different alternatives were assessed based on the annuitization of capital expenditures method. Using this methodology, an incremental cost effectiveness ratio of $15,961/reoperation avoided was calculated for the computer-assisted surgery group. On the basis of a reoperation cost of $12,618, this new technology becomes cost saving for centers performing more than 254 instrumented spinal procedures per year. Conclusion Computer-assisted spinal surgery has the potential to reduce reoperation rates and thus to have serious cost-effectiveness implications. High acquisition and maintenance costs of this technology can be offset by equally high reoperation costs. Our cost-effectiveness analysis showed that for high-volume centers, this technology is economically justified.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".