Extremity Mobilization After Split-Thickness Skin Graft Application
Bibliographic record
Abstract
PURPOSE: To determine the current postoperative mobilization care practice patterns of burn surgeons after split-thickness skin grafting and to assess potential inconsistencies in management strategies. METHODS: A cross-sectional study of active burn surgeons was conducted with an online questionnaire (SurveyMonkey) comprising 7 demographic and 22 mobilization-related questions. RESULTS: Seventy-three (22%) of the 337 members of the American Burn Association mailing list consented to participate in the study, of whom 71 completed the demographic questions and 59 completed the mobilization-related questions. The majority of respondents had more than 10 years of burn care experience (68%) and practiced in an American Burn Association-verified center (70%). Standardized postoperative autograft mobilization protocols were used by 68% of respondents. Most (66%) never or rarely immobilized the upper extremity without joint involvement. When the elbow or wrist was involved, 73% always or very often immobilized. Similarly, 63% never or rarely immobilized the lower extremity without joint involvement. Most immobilized when the knee (70%) or ankle (63%) was involved. Immobilization duration was most commonly 3 or 5 days. Most respondents (71%) reported following Nedelec and colleagues' recommendation that "early postoperative ambulation protocol should be initiated immediately after lower extremity grafting," although there was practice variability. CONCLUSIONS: Our findings reveal that the majority of survey respondents do not immobilize the extremities after autograft without joint involvement. When grafts cross major joints, most surgeons immobilize for 3 or 5 days. Despite some practice variability, surveyed burn surgeons' current lower extremity ambulation practices generally align with the 2012 guidelines of Nedelec et al.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".