Transportal Tibiotalocalcaneal Nail Ankle Arthrodesis: A Systematic Review of Initial Series
Bibliographic record
Abstract
Background: There is currently a scarcity of information and consensus for transportal (arthroscopic or fluoroscopic) joint preparation during tibiotalocalcaneal (TTC) fusion, and therefore this review aims to summarize the available techniques and to evaluate the outcomes after this procedure. Methods: A systematic electronic search of MEDLINE, EMBASE, and Web of Science was performed for all English-language studies published from their inception to April 4, 2022. All articles addressing arthroscopy in TTC nailing were eligible for inclusion. The PRISMA Checklist guided the reporting and data abstraction. Descriptive statistics are presented. Result: A total of 5 studies with 65 patients were included for analysis. All studies used arthroscopic portals for tibiotalar and subtalar joint preparation (in 4 studies) prior to TTC nailing, with 4 studies using an arthroscope and 1 study using fluoroscopy. The overall major complication rate was 13.8%; however, there was only 1 instance of deep wound infection (1.5%) and 4 instances of surgical site infections (6.2%). Full fusion was achieved in 86% of patients with an average time to fusion of 12.9 weeks. The mean American Orthopaedic Foot & Ankle Society (AOFAS) ankle-hindfoot score preoperatively was 34.0 and postoperatively was 70.5. Conclusion: Although limited by the number of studies, transportal joint preparation during TTC nail ankle fusion is associated with good rates of complications and successful fusion. Level of Evidence: Level III, systematic review of Level III-IV studies.
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 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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".