Effectiveness of intramedullary nails in Tibiotalocalcaneal arthrodesis for Charcot neuroarthropathy: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To systematically evaluate the efficacy and safety of intramedullary nails (IMNs) in tibial-talocalcaneal arthrodesis (TTCA) for treating Charcot neuroarthropathy (CN). METHODS: A comprehensive search for relevant literature was conducted in the PubMed, Embase, Cochrane Library, Web of Science, Scopus and SinoMed databases, covering studies from 2014 to October 30, 2024. The inclusion criteria were based on the PICOS framework: the study population consisted of CN patients, the intervention was TTCA with IMNs, and the outcomes assessed included bone union rate, complication rate, and limb salvage rate. Statistical analysis was performed using Stata 17.0 software. Literature quality was assessed using the Newcastle-Ottawa Scale (NOS) for cohort studies and case series. This systematic review was prospectively registered with the International Prospective Register of Systematic Reviews (PROSPERO; registration number: CRD42025644983). RESULTS: A total of seven studies involving 147 patients with a mean follow-up of one year were included. The meta-analysis revealed a combined standardized mean difference (SMD) of -4.99 (95% CI: -6.70 to -3.28) for the AOFAS score, with high heterogeneity (I2 = 90.7%). Sensitivity analyses were conducted to assess the stability of the results. The combined estimate for the bone nonunion rate was 3.3% (95% CI: 0.1% to 8.9%), with moderate heterogeneity (I2 = 33.2%). The combined estimate for the infection rate was 12.9% (95% CI: 2.0% to 29.2%). A comparison of preoperative and postoperative scores showed significant improvements in patients' function and quality of life, highlighting the critical role of the TTCA procedure in improving prognosis. CONCLUSION: IMNs in TTCA demonstrate high efficacy for CN, with significant functional improvement, low nonunion rates, and favorable limb salvage outcomes. However, infection risks and heterogeneity across studies highlight the need for standardized protocols and larger controlled trials to optimize patient selection and postoperative management.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.037 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".