A Systematic Review of Complication and Recurrence Rates of Musculocutaneous, Fasciocutaneous, and Perforator-Based Flaps for Treatment of Pressure Sores
Bibliographic record
Abstract
BACKGROUND: Management of pressure sores poses a significant reconstructive challenge for plastic surgeons. Currently, there is no consensus on whether musculocutaneous, fasciocutaneous, or perforator-based flaps provide superior results for treating pressure sores. METHODS: The following databases were searched: Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, LILACS (January of 1950 to November of 2010), MEDLINE (January of 1950 to November of 2010), and EMBASE (January of 1980 to November of 2010). Only articles reporting on the use of musculocutaneous, fasciocutaneous, and perforator-based flaps were included. The primary study outcomes were complication and recurrence rates. RESULTS: Fifty-five articles were included in the final analysis (kappa = 0.78). From this total, 28 were categorized as pertaining to musculocutaneous flaps, 13 studied fasciocutaneous flaps, and 14 evaluated perforator-based flaps. The authors' review revealed recurrence and complication rates of 8.9 and 18.6 percent, respectively, following reconstruction with musculocutaneous flaps, 11.2 and 11.7 percent following reconstruction with fasciocutaneous flaps, and 5.6 and 19.6 percent following reconstruction with perforator-based flaps. Overall, statistical analysis revealed no significant difference in complication or recurrence rates among these three techniques. CONCLUSIONS: The authors' review revealed that there was no statistically significant difference with regard to recurrence or complication rates among musculocutaneous, fasciocutaneous, or perforator-based flaps. This suggests that surgeons performing such reconstructive procedures may choose to consider the advantages of a specific approach rather than the complication and recurrence rates. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, IV.
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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 | 0.010 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.020 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| 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".