Effects of <i>Asiaticosides</i> on Scar Recovery and Psychological Well-being in Patients with Scald Injuries
Bibliographic record
Abstract
Background Scar recovery in elderly burn patients is essential for wound healing and psychological well-being. Total glycosides from Centella asiatica have gained attention for their anti-inflammatory, antioxidant, and wound-healing properties, showing promise in burn care. Objectives This study investigates the synergistic effects of combined nursing interventions and Asiaticosides on scar recovery and psychological well-being in patients undergoing scald scar repair. The pharmacological properties of these glycosides, including their anti-inflammatory, anti-oxidant, and wound-healing potential, are explored in the context of clinical care to enhance patient outcomes. Materials and Methods A cohort of 184 patients treated for scald scars between April 2023 and April 2024 was divided into two groups: an observation group receiving combined nursing interventions with Asiaticosides , and a comparison group receiving standard care. Scar assessment was conducted using the Vancouver Scar Scale (VSS), pain was measured by the Visual Analogue Scale (VAS), and psychological states were evaluated using the Self-rating Anxiety Scale (SAS) and Self-rating Depression Scale (SDS). Results Statistically significant improvements were observed in the observation group, including reduced VSS and VAS scores, as well as enhanced psychological states, compared to the control group ( p < 0.05). The glycosides facilitated faster scar healing, reduced inflammation, and improved overall patient well-being. Conclusion Asiaticosides exhibit promising therapeutic potential in enhancing scar recovery and psychological health in elderly scald patients when combined with comprehensive nursing care. Further research into their mechanisms may solidify their role in integrated scald injury management.
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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 | 0.000 | 0.001 |
| 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 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".