Split-thickness skin graft donor-site morbidity: A systematic literature review
Bibliographic record
Abstract
The purpose of this systematic literature review is to critically evaluate split-thickness skin graft (STSG) donor-site morbidities. The search of peer-reviewed articles in three databases from January 2009 to July 2019 identified 4271 English-language publications reporting STSG donor-site clinical outcomes, complications, or quality of life. Of these studies, 77 met inclusion criteria for analysis. Mean time to donor-site epithelialization ranged from 4.7 to 35.0 days. Mean pain scores (0-10 scale) ranged from 1.24 to 6.38 on postoperative Day 3. Mean scar scores (0-13 scale) ranged from 0 to 10.9 at Year 1. One study reported 28% of patients had donor-site scar hypertrophy at 8 years. Infection rates were generally low but ranged from 0 to 56%. Less frequently reported outcomes included pruritus, wound exudation, and esthetic dissatisfaction. Donor-site wounds underwent days of wound care and were frequently associated with pain and scarring. Widespread variations were noted in STSG donor-site outcomes likely due to inconsistencies in the definition of outcomes and utilization of various assessment tools. Understanding the true burden of donor sites may drive innovative treatments that would reduce the use of STSGs and address the associated morbidities.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".