Novel Treatment Protocol for Combined Tear Trough Ligament Stretching and Injection
Bibliographic record
Abstract
BACKGROUND: Complex anatomical changes have been the main challenges for optimal treatment results of tear trough deformities through hyaluronic acid (HA) injections. The authors present a novel technique consisting of a preinjection tear trough ligament stretching (TTLS-I) leading to its release, and compared its efficacy, safety, and patient satisfaction to tear trough deformity injection (TTDI). METHODS: This was a 4-year, retrospective, single-center cohort study of 83 TTLS-I patients, with a follow-up period of 1 year. One hundred thirty-five TTDI patients served as a comparison group. Outcome analyses included the analysis of possible risk factors for adverse outcome and comparative statistics between the complication and satisfaction rates of the two groups. RESULTS: TTLS-I patients received significantly less HA (0.3 cc; range, 0.2 to 0.3 cc) than TTDI patients did (0.6 cc; range, 0.6 to 0.8 cc; P < 0.001). The injected HA amount was a significant predictive factor for complications ( P < 0.05). Complication rates assessed during the follow-up visit for hematomas, edema, and the need for corrective hyaluronidase injection were low in both groups, with no significant differences between the groups. TTDI patients had significantly higher rates (5.1%) of lump surface irregularities during follow-up, compared with 0% in the TTLS-I group ( P < 0.05). After 1 year of follow-up, 98.8% of TTLS-I patients were satisfied, whereas 95.6% of TTDI patients were satisfied, with no significant difference between groups. CONCLUSIONS: TTLS-I is a novel, safe, and effective treatment method, necessitating significantly less HA compared with TTDI. Moreover, it leads to very high satisfaction rates and very low complication rates. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, III.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".