Comparison of central segment expansion with release and split skin grafting in postburn contractures of fingers
Bibliographic record
Abstract
ABSTRACT Introduction: A diverse range of therapeutic methods such as skin grafting, Z-plasty, local flaps, regional flaps, island flaps, and free flaps have been described for the treatment of postburn hand deformities. Central segment expansion (CSE) is a procedure in which the contracture is released in a manner that a well-settled segment of skin is left over the joint, and defects created on either side of the well-settled segment of skin are skin grafted. Materials and Methods: Sixty cases of postburn mild-to-moderate proximal interphalangeal joint contracture of fingers were randomized to either CSE group or release and split skin grafting (RSSG) group and were followed up for 18 months. Results: The mean age of presentation was 11.11 years. The degree of flexion contracture varied from 30° to 100° (mean = 72.6) in the CSE group, whereas it varied from 30° to 90° (mean = 70.33) in the RSSG group. The mean improvement in the range of motion was 68.33° in the CSE group and 57.83° in the RSSG group. The CSE group resulted in significantly lower values of postoperative extensor lag (12.33° vs. 3.33°; P = 0.002). The mean duration of the postoperative splint was 1.1 months in the CSE group versus 3.4 months in the RSSG group ( P = 0.00). The mean total score using the Vancouver Scar Scale for the appearance of graft scar was 4 ± 0.27 in the CSE group, whereas that for the RSSG group was 2.5 ± 0.39 ( P = 0.00). The recurrence in the two groups was comparable. Conclusion: The technique of CSE to release PBC fingers is easy to perform and shows better results than contracture release with split-thickness skin graft. It can be used as an alternative method for coverage of defects created after postburn contracture release
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 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".