Surgical Treatment of Trigonocephaly, Simplified Technique for Moderate Cases
Bibliographic record
Abstract
BACKGROUND: The prevalence of trigonocephaly has increased worldwide over the past 2 decades. Early identification and appropriate treatment are critical. The aim of this study is to evaluate the outcomes and the effect of metopic suture excision, perisutural frontal bone shave, and bilateral pericranial flap method on the shape of the forehead after surgical correction in infants with moderate trigonocephaly. METHODS: The present study was performed as a cross-sectional study on 40 infants of 3 to 12 months old with trigonocephalus who underwent metopic suture excision and pericardial flap surgery in Mofid Pediatric Hospital from 2016 to 2022. The definitive diagnosis of patients' trigonocephaly was made based on clinical signs and computed tomography scan findings by a plastic surgeon. RESULTS: Overall in 40 patients operated by this technique, 23 (57.5%) of cases were males, and 17 (42.5%) were females. The mean age of patients was 7.86 ± 2.22 months. Hospital stay was 2 to 4 days (mean: 3 d), intensive care unit admission was in 33 cases for 24 hours, and no intensive care unit admission for 7 cases. Blood was transfused during surgery for 25 patients, and 15 patients did not require blood transfusion use. Results were evaluated in 6 to 12 months after surgery by 3 independent plastic surgeons, with pre and postoperative photos. Satisfaction with the results of forehead shape was excellent for 60% of patients, good for 37.5%, and moderate for 2.5%. Only one female patient had a recurrence after the surgery. CONCLUSION: This study showed that the pericranial flap method after full metopic suture excision and frontal shave was very effective in the treatment of infants with moderate trigonocephaly.
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) | 0.000 | 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".