Factors associated with lingual tonsil hypertrophy in Canadian adults
Bibliographic record
Abstract
BACKGROUND: Hypertrophy of the lingual tonsil tissue in the adult patient is thought to contribute to the pathophysiology of obstructive sleep apnea. The underlying etiology of lingual tonsil hypertrophy (LTH) in the adult patient is unclear and likely multifactorial. Previous studies have suggested that the lingual tonsils may undergo compensatory hyperplasia post-tonsillectomy in children, although it is unknown if this occurs or persists into adulthood. The purpose of this study was to determine what factors are associated with LTH in a population of Canadian adults. METHODS: Adult patients presenting for consultation to an academic Rhinology/General Otolaryngology practice were eligible for enrollment. Demographic data including age, body mass index (BMI), Reflux Symptom Index (RSI), history of allergy, and history of tonsillectomy was collected via questionnaire. Endoscopic photographs of the base of tongue and larynx were captured. These were graded for LTH and Reflux Finding Scale (RFS) by blinded examiners. Statistical analysis was performed by comparing the mean LTH value to the variables of interest using two-tailed T-test. P < .05 was considered significant. RESULTS: One hundred two subjects were enrolled. Age ranged from 18 to 78. 28 patients had previous tonsillectomy. This was not associated with a significant increase in lingual tonsil tissue (r = -0.05, p = 0.61). RFS >7 or RSI >13 was considered positive for laryngopharyngeal reflux. There was no difference in LTH based on RSI positivity (p = 0.44). RFS positivity correlated with increased lingual tonsil tissue (p < 0.05). BMI >30 was associated with increased lingual tonsil hypertrophy (p < 0.05). CONCLUSIONS: An elevated body mass index and positive Reflux Finding Score are associated with lingual tonsil hypertrophy in adults. Reflux symptom index, history of allergy and history of childhood tonsillectomy are not associated with LTH.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".