Empty Sella in Neuro-Ophthalmology Patients Without Raised Intracranial Pressure
Bibliographic record
Abstract
BACKGROUND: Empty sella often supports a diagnosis of raised intracranial pressure (ICP) but is also seen in normal individuals. This study's objective was to determine the prevalence of empty and partially empty sella in neuro-ophthalmology patients undergoing MRI for indications other than papilledema or raised ICP. METHODS: Consecutive patients without papilledema or suspected raised ICP who underwent brain MRI between August 2017 and May 2021 were included in this study. Sagittal T1 images were evaluated by 2 independent, blinded neuroradiologists who graded the sella using the published criteria (Categories 1-5, with 1 being normal and 5 showing no visible pituitary tissue). Clinical parameters were also collected. RESULTS: A total of 613 patients (309 men; average age 56.69 ± 18.06 years) were included in this study with optic neuropathy as the most common MRI indication. A total of 176 patients had moderate concavity of the pituitary gland (Category 3), 81 had severe concavity (Category 4), and 26 had no visible pituitary tissue (Category 5). Sella appearance was mentioned in 92 patients' radiology reports (15%). There was a statistically significant difference in age between composite Categories 1 and 2 (mean 52.89 ± 18.91; P < 0.001) and composite Categories 4 and 5 (mean 63.41 ± 15.44), but not the other clinical parameters. CONCLUSION: Empty sella is common in neuro-ophthalmology patients without raised ICP; 17.4% of patients have severe concavity or no pituitary tissue visible. An isolated finding of empty or partially empty sella on imaging is therefore of questionable clinical value in this patient population.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".