The Impact of Time of Mobilization After Split Thickness Skin Graft on Lower Extremity Wound Healing—Systematic Review and Meta-analysis
Bibliographic record
Abstract
Following split-thickness skin grafting (STSG), surgeons have used different postoperative care protocols. One area of contention is the timing of mobilization of the grafted area after STSG. The aim of this systematic review and meta-analysis is to summarize the evidence for timing of mobilization in the extremities after STSG. MedLine, Embase, and the Cochrane Library were searched to conduct a systematic review and meta-analysis evaluating the impact of early versus late mobilization after STSG in adult patients with wounds in the upper extremity (UE) or lower extremity (LE). Outcomes evaluated were graft healing, postoperative morbidity, and length of stay in hospital. A fixed-effect model was used to calculate pooled odds ratio and mean difference with 95% confidence intervals (CI). A total of seven full texts (five randomized trials and two observational studies) were included in the analysis. All wounds were in the LE. Odds of graft loss, infection, and hematoma were 0.55 (CI: 0.12–2.54), 1.66 (CI: 0.54–5.10), and 0.98 (CI: 0.25–3.85), respectively, for early versus late mobilization (n = 2). Deconditioning was more common in the late mobilization group (n = 3). Hospital length of stay was shorter in the early mobilization group (n = 3). We conclude that early mobilization may be the preferred strategy for patients treated with STSG to the LE as it provides good graft healing and prevents morbidity. High-quality studies are needed to provide more robust recommendations on mobilization in the LE. Studies are needed to provide evidence in the UE. Systematic Review registration: Prospero CRD42017070990.
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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.023 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".