Four‐year outcomes of palatal implants for primary snoring treatment: A prospective longitudinal study
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: The objective of this study was to evaluate the long-term effectiveness of palatal implants as the treatment of primary snoring. STUDY DESIGN: Prospective longitudinal cohort study. METHODS: This study compared snoring outcomes before and after soft palate implantation for patients diagnosed with primary snoring (no sleep apnea). Snoring severity was obtained by the subjects' sleep partners on a 10-point Likert scale. A paired Student t test compared the mean scale values preoperatively at week 52 and at the current 4-year follow-up. Body mass index for each patient was also compared to evaluate for any significant confounders. RESULTS: Data were obtained from 23 patients out of 26 who were followed for the full study term. The follow-up time was on average 4 years following palatal implantation. A statistically (P < .016) and clinically significant improvement in the snoring scale was noted when comparing snoring severity between the preoperative and 4-year period and between the 52-week and 4-year scores. Although statistically significant improvement was found between the preoperative period and 52 weeks, there was a clinical deterioration in snoring scale scores between 52 weeks and 4 years. The mean (standard deviation) preoperative score was 9.5 (0.5), mean week-52 score was 5.0 (1.6), and mean 4-year score was 7.0 (1.8). Body mass index did not change through the observation interval. CONCLUSIONS: Soft palate implantation is a possible surgical technique with which to attempt to achieve subjective improvement of primary snoring severity. Subjective improvement, however, deteriorates significantly over time, and is only minimally sustained at 4 years postoperatively. This study provides new information on long-term palatal implant effectiveness.
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 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".