The Histopathology of the Hypertrophic Inferior Turbinate
Bibliographic record
Abstract
OBJECTIVE: To analyze the quantitative and qualitative characteristics of the hypertrophic inferior turbinate (IT). DESIGN: A prospective, nonrandomized, controlled, morphometric study. SETTING: University-affiliated hospital. Subjects Seventeen patients with refractory IT hypertrophy and 12 with normal ITs. INTERVENTIONS: Twenty ITs were removed from patients with refractory IT hypertrophy and 14 from patients with normal ITs. MAIN OUTCOME MEASURES: The soft tissue and bony elements and the relative proportions of the soft tissue constituents of the hypertrophic and normal ITs were measured and compared. The Bonferroni correction was used to adjust for multiple comparisons. Qualitative assessment was performed to assess possible pathologic changes in all IT tissues. RESULTS: The hypertrophic ITs were significantly wider. The medial mucosal layer, which thickened from a mean +/- SD of 1.39 +/- 0.28 mm to 2.53 +/- 0.56 mm (P</=.001), made the greatest contribution to the total increase in the width of the IT (64.4%). The enlargement in width of the lateral mucosal layer from 0.91 +/- 0.26 mm to 1.26 +/- 031 mm was of borderline statistical significance. The portion of the medial, lateral, and inferior layers of the lamina propria that houses inflammatory cells enlarged significantly in patients with IT hypertrophy compared with healthy control subjects. The relative proportion of the connective tissue, submucosal glands, and arteries remained unchanged, whereas that of venous sinusoids increased significantly in all aspects of the hypertrophic mucosa. Fibrosis, inflammation, and engorged venous sinusoids were noted in hypertrophic ITs, yet there was no evidence of tissue destruction. CONCLUSION: Understanding the histopathology of the hypertrophic IT is imperative for the development and management of IT reduction surgery.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".