Effectiveness of Physiotherapeutic Interventions in a Post-Surgical Burn Patient - A Case Study
Bibliographic record
Abstract
Introduction: Burn injuries are a major cause of morbidity and mortality in children. In India, the figure constitutes about one-fourth of the total burn accidents. Burn injuries can lead to scar tissue formation that further leads to functional limitations. Each paediatric burn case is unique, and a tailored approach is necessary for effective physiotherapy management. Therefore, the aim of this study is to explore the effects of physiotherapeutic interventions on range of motion, scar quality, pain and anxiety in post-surgical patient with a 20% second degree superficial partial-thickness flame burn. Case Presentation: A 9-years old female patient, admitted to Plastic surgery and Burn Unit, was recruited for the study. She had undergone skin grafting following the burn. Physiotherapeutic interventions were provided in two phases over 8 weeks, including exercises adjunct with ultrasound therapy and application of transcutaneous electrical nerve stimulation for 8 weeks lasted the treatment session for 60 minutes. The outcome measures used in this study were range of motion of following joints- right shoulder, right elbow joint and left shoulder joint, scores of Vancouver scar scale and scores of specific burn pain and anxiety scale. The assessments were taken at pre intervention 0 week, mid-intervention 4th and 8th week post intervention. Results and Conclusion: The findings of this study showed improvements in ROM of affected joint- right shoulder joint and right elbow joint and left shoulder joint, scar tissue quality, pain and anxiety reduction. Further research is needed to establish the relationship and determine optimal interventions for burn subjects. This study concluded the effectiveness of physiotherapy in burn rehabilitation.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".