Comparative effectiveness analysis of deep low heat burns in the shin surgical approaches: Outcomes and cost for wound rehabilitation
Bibliographic record
Abstract
A variety of surgical techniques exist for deep burn wounds in the shin at low temperature reconstruction after appropriate debridement, but limited high-quality data exist to inform treatment strategies. Using multi-institutional data, the authors evaluated the length of healing time, cost, and outcomes of three common surgical reconstructive modalities. All subjects with deep burn wounds in the shin caused by low temperature who received direct suture repair, skin grafting, or local flap reconstruction were retrospectively reviewed (from 2015.01 to 2021.03). Mean operation time, mean blood loss in operation, postoperative healing time, whether there is scar depression after operation were the primary outcomes; patient satisfaction score, Vancouver scar scale (VSS) score and average costs were secondary outcomes. Two hundred subjects (68 suture, 87 skin-grafting, and 45 local flap coverage patients) were evaluated. Matched patients (n = 200; 3/groups) were analysed. The average operation time, average operation blood loss, and postoperative healing time were statistically significant differences (P < 0.05). Readmissions and reoperations were greater for direct suture and local flaps, if achievable, direct suture provided success at low cost. Skin grafting was effective with large burn wounds but at higher costs and longer length of stay. Local flaps successfully treated smaller burn wounds unable to suture directly, with less pigmentation and scars, even suitable for older patients. Deep low heat burn wounds in the shin healing can be performed effectively using multiple modalities with varying degrees of success and costs. Direct suture or local skin flap reconstruction, if achievable, provides successful coverage at minimal costs, no skin contractures, and reducing length of hospital stay.
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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 | 0.001 | 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) | 0.000 | 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".