CT-Verified Union Rate Following Arthrodesis of Ankle, Hindfoot, or Midfoot: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Ankle, hindfoot, and midfoot arthrodesis surgeries are standard procedures performed in orthopaedics to treat pain and functional disabilities. Although fusions can effectively improve pain and quality of life, nonunions remain a significant concern for surgeons. With the increased availability of computed tomography (CT), more surgeons rely on this modality for increased accuracy in determining whether a fusion was successful. The objective of this study was to report the rates of CT-confirmed fusion following ankle, hindfoot, or midfoot arthrodesis. METHODS: A systematic review was performed using EMBASE, Medline, and Cochrane central register from January 2000 to March 2020. Inclusion criteria included studies with adults (<18 years) that received 1 or multiple fusions of the ankle, hindfoot, or midfoot. At least 75% of the study cohort must have been evaluated by CT postoperatively. Basic information was collected, including journal, author, year published, and level of evidence. Other specific information was collected, including patient risk factors, fusion site, surgical technique and fixation, adjuncts, union rates, criteria for successful fusion (%), and time of CT. Once data were collected, a descriptive and comparative analysis was performed. RESULTS: Included studies (26, n = 1300) had an overall CT-confirmed fusion rate of 78.7% (69.6-87.7). Individual joints had an overall fusion rate of 83.0% (73-92.9). The highest rate of union was in the talonavicular joint (TNJ). CONCLUSION: These values are lower than previous studies, which found the same procedures to have greater than 90% fusion rates. With these updated figures, as confirmed by CT, surgeons will have better information for clinical decision making and when having informed consent conversations.
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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 | 0.007 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 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".