Utility of Tongue Stitch and Nasal Trumpet in the Immediate Postoperative Outcome of Cleft Palatoplasty
Bibliographic record
Abstract
BACKGROUND: Postoperative airway obstruction is a feared complication following cleft palate repair. The aim of this study was to evaluate the effectiveness of tongue stitches and nasal trumpets that have been used in an attempt to prevent this complication. METHODS: An 8-year (2005 to 2013) retrospective review of palatoplasties performed at a tertiary care center was conducted. Patients were divided into three groups: those with no airway protective measure, those with a tongue stitch only, and a group with nasal trumpet and tongue stitch. Recorded variables included sex, age, Veau classification, and comorbidities. Primary outcomes measured were postoperative respiratory distress, readmission, and reoperation rates. RESULTS: Fifty-eight patients underwent palatoplasties with no airway protective measure, 252 patients had tongue stitch only, and 87 had tongue stitch and nasal trumpet. There were no significant differences between groups with respect to comorbidities except that cleft lip was more prevalent in the no-airway protection group than in the other two groups (p = 0.04). There was no significant difference in the incidence of reintubation, intensive care unit transfer, surgery-related readmissions, or reoperation. Respiratory complications were significantly increased in the nasal trumpet group even after adjusting for age and weight. Length of stay was also significantly (p < 0.01) shortened when comparing no airway protection to those who underwent both nasal trumpet and tongue suture placement. CONCLUSIONS: The use of a tongue stitch, with or without nasal trumpet, did not correlate with improved safety and outcomes. Patients without these airway protective measures had a shorter hospital stay. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, III.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".