Pilot Study of Speech and Ventilation Quality of Life After Cleft Palate Repair in Chinese Patients
Bibliographic record
Abstract
OBJECTIVE (S): This pilot study aimed to assess the quality of life (QoL) in Chinese patients with velopharyngeal competence (VPC) after primary cleft palate surgery or after secondary posterior pharyngeal flap (PPF) surgery. METHODS: A two-center cross-sectional study was conducted in two stomatological hospitals in China between December 2021 and December 2022. A total of 68 patients and healthy volunteers were enrolled in this study, categorized into the control group, the group of patients with VPC after primary cleft palate repair, and the group of patients with VPC after secondary PPF. The Velopharyngeal Insufficiency (VPI) Effects on Life Outcomes (VELO) instrument and the Quebec Sleep Questionnaire (QSQ) were used for the assessment of speech-related QoL and ventilation-impairment-related QoL. RESULTS: Healthy subjects had better VELO total scores (speech-related QoL) than patients with VPC. Patients who reached VPC by secondary PPF surgery had better VELO scores in the domain of perception by others, compared with patients who reached VPC after the primary cleft palate surgery. Ventilation-impairment-related QoL assessment showed that patients who underwent secondary PPF surgery had worse QSQ total scores and domain scores than those who only had primary surgery. Surgical age only had a negative correlation with VELO scores of swallowing problems in patients who underwent PPF surgery. CONCLUSIONS: Despite achieving VPC after both primary and secondary surgery, patients could still exhibit worse speech-related QoL than healthy individuals. Among patients with VPC, patients who underwent secondary PPF could have worse ventilation-impairment-related QoL than those who only had primary cleft palate surgery. LEVEL OF EVIDENCE: 3 Laryngoscope, 135:2367-2374, 2025.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".