The Difference in Scar-Related Quality of Life in Open Versus Closed Septorhinoplasty
Bibliographic record
Abstract
INTRODUCTION: The open and closed techniques are the main surgical techniques to perform septorhinoplasty. Although the open technique offers a better view of the pertinent anatomy and facilitates surgical access, it creates an external scar that could affect patients' satisfaction and quality of life (QoL). This study aims to compare the open and closed techniques using the SCAR-Q patient-reported outcome measure. METHODS: In this retrospective study, we have included patients who had their nasal surgery one year ago, in the period between April 2020 and April 2021. The SCAR-Q assessment tool to study patients' satisfaction with appearance, symptoms, and psychological impact of open and closed septorhinoplasty techniques. RESULTS: A total of 77 patients were included in this analysis. Of these, 39 (50.6%) patients underwent a closed septorhinoplasty, and 38 (49.4%) patients underwent an open approach. The mean (SD) age was 29.6 (8.1) years, and most patients were females (59.7%). The overall SCAR-Q questionnaire responses were very positive across all scales in our cohort, the median (IQR) scores were 91.0 (73.0-100.0) for the appearance scale, 89.0 (70.0-100.0) for the symptoms scale, and 100.0 (87.0-100.0) for the psychological impact scale. However, we have found no differences in SCAR-Q scores regarding appearance, symptoms, and psychological impact between open and closed septorhinoplasty. CONCLUSION: We have found no significant differences in QoL between open and closed techniques of septorhinoplasty. Larger studies are needed to further validate this finding.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".