A Comparison Between Piezosurgery and Conventional Osteotomies in Rhinoplasty on Post-Operative Oedema and Ecchymosis: A Systematic Review
Bibliographic record
Abstract
Piezosurgery use has become increasingly prevalent in osteotomies. Piezoelectric ultrasound waves can cut bone effectively, and some studies have shown reduced post-operative morbidities compared to conventional osteotomies. Oedema and ecchymosis are common complications of rhinoplasty and can impact patient satisfaction, wound healing, and recovery. We aim to provide an up-to-date comparison of post-operative oedema and ecchymosis in piezosurgery and conventional osteotomies. A literature search was conducted using the following online libraries; Pubmed, Cochrane, Science Direct, and ISRCTN (International Standard Randomised Controlled Trial Number). English publications between 2015 and 2020 were included. A systematic review was completed, and a comparison of oedema and ecchymosis in piezosurgery and conventional osteotomies was examined alongside other outcomes such as pain, mucosal injury, and surgery time. Eight randomised controlled trials (RCTs) met our criteria with a combined total of 440 patients: 191 male and 249 female. Piezosurgery had statistically significant (p < 0.05) reduction in short-term oedema compared to conventional osteotomies in 75% of the papers included, and in 50% this persisted across the whole follow-up period. Similarly, ecchymosis scoring was initially statistically lower (p < 0.05) in piezosurgery in 87.5% of the RCTs, and in 75% this persisted across the whole follow-up period. A reduction in pain (p < 0.05) and mucosal injury (p < 0.05) was also seen in piezoelectric osteotomies. The length of surgery time varied. Piezoelectric osteotomies reduce oedema and ecchymosis compared to conventional osteotomies, in addition to improving pain and mucosal injury. However, disadvantages such as length of surgery time and cost have been reported. LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".