The Serpentine Sign: A Reliable Endoscopic and Radiographic Finding in Empty Nose Syndrome
Bibliographic record
Abstract
OBJECTIVE: Empty nose syndrome (ENS) is a relatively uncommon disease that greatly impacts the quality of life and presents diagnostic challenges. We sought to identify objective clinical findings unique to patients with ENS, and in doing so identified compensatory mucosal hypertrophy in an alternating, undulating swelling on endoscopy and coronal computerized tomography (CT) that we have termed the "Serpentine Sign." Here, we investigated whether this radiographic finding is a reliable manifestation in ENS patients. METHODS: Retrospective review was undertaken to identify ENS patients with past turbinoplasty, an ENS6Q score of at least 11/30, and symptomatic improvement with the cotton placement test. Control patients without complaints of ENS symptoms (ENS6Q < 11) were identified for comparison. ENS and control patients had coronal CT imaging available to evaluate for the Serpentine Sign, as well as ENS6Q scores, and histologic analysis of nasal tissue. RESULTS: 34 ENS and 74 control patients were evaluated for the presence of the Serpentine Sign. Of the 34 patients with ENS, 18 exhibited this radiographic finding on CT imaging (52.9%) compared to 0 of the 74 control patients (p < 0.0001). Further analysis demonstrated that ENS patients with the Serpentine Sign had lower median scores on ENS6Q than ENS patients without (17.5 vs. 22, p = 0.033). Histology revealed disorganized subepithelium rich in seromucinous glands similar to the nasal septum swell body. CONCLUSION: The "Serpentine Sign" is a unique presentation of hypertrophic change to the nasal septum soft tissue that is specific to ENS patients and may serve as a reliable radiographic and endoscopic finding in diagnosis. LEVEL OF EVIDENCE: 4 Laryngoscope, 134:1089-1095, 2024.
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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 | 0.002 |
| 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".