The Silent Sinus Syndrome is a form of Chronic Maxillary Atelectasis: A Systematic Review of all Reported Cases
Bibliographic record
Abstract
BACKGROUND: The terms chronic maxillary atelectasis (CMA) and silent sinus syndrome (SSS) have been used to describe spontaneous enophthalmos in association with a contracted ipsilateral maxillary sinus. Despite the use of differing taxonomy, it appears that these two terms describe the same clinical entity. Nevertheless, many reports still discuss CMA and SSS in isolation or as distinct conditions. METHODS: A systematic review of all reported cases of CMA and SSS was performed (1964-2006). Case reports were excluded if they involved facial trauma, diagnosis of mucocele, or previous surgery. Eligible cases were reviewed and entered into a database. Data were evaluated based on literature of publication, reported diagnosis, demographics, ophthalmologic examination, results of imaging, and operative findings. Only complete data sets were included in an additional analysis whereby the diagnostic criteria for CMA and SSS were applied and the data sets were compared. RESULTS: Of the 105 cases reviewed, 55 contained complete data sets. Twenty-seven of these cases met the diagnostic criteria for SSS, and 48 could be diagnosed as CMA, with 23 meeting the criteria for both conditions. Comparing the cases across diagnoses, the only difference observed was that of the presence of sinus-related symptoms, which by definition distinguishes CMA III from SSS. CONCLUSION: The entity termed SSS fits within the staging classification of CMA. We propose abandoning the term SSS and recommend universal adoption of the CMA staging system, which uses nomenclature that more accurately portrays the pathophysiology and natural history of this condition.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".