<scp>U</scp>pper and lower extremity reconstructive applications utilizing free flaps from the medial genicular arterial system: A systematic review
Bibliographic record
Abstract
BACKGROUND: Free flaps derived from the medial genicular artery (MGA) system, including the medial femoral condyle (MFC) and medial femoral trochlear (MFT) flaps, are potential reconstructive options to address upper and lower extremity bony pathology. Our primary aim was to comprehensively search the literature to describe the spectrum of pathology treated with these flaps, and to assess patient outcomes to improve our understanding of expected union and complication rates. METHODS: Following PRISMA guidelines, a systematic review using Pubmed and Embase databases with citation cross-referencing was performed to identify all original clinical articles characterizing MGA flap treatment of upper and lower extremity pathology. RESULTS: The initial search identified 173 articles which was narrowed down to 40 meeting inclusion criteria, representing a total of 248 cases: 174 and 74 in the upper and lower extremities, respectively. Sixteen distinct recipient sites were identified with union rates ranging from 66 to 100% (98.7% overall). The majority (83.9%) of patients had undergone prior failed surgery. Major complications (those with limb/flap loss or requiring unplanned reoperation) were more frequent for lower versus upper extremity applications (17.1% vs. 6.2%, respectively). Donor site femoral fracture or persistent knee dysfunction occurred in 0.8% and 0.4% of patients, respectively. CONCLUSIONS: MGA free flaps are a versatile option for upper and lower extremity osseous reconstruction, offering high rates of union with minimal complications for a complex patient population. This study furthers our understanding of patient outcomes following MGA flap reconstruction, which previously was limited to case reports and small case series.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".