SUNCT, SUNA and pituitary tumors: Clinical characteristics and treatment
Bibliographic record
Abstract
BACKGROUND: Short-lasting unilateral neuralgiform headache attacks with conjunctival injection and tearing (SUNCT) and short-lasting unilateral neuralgiform headache attacks with cranial autonomic symptoms (SUNA) are rare types of trigeminal autonomic cephalalgias (TACs). Objective To describe a series of patients with SUNCT and SUNA including relationship to pituitary tumors. METHOD: All patients diagnosed with SUNCT or SUNA in the Calgary Headache Assessment and Management Program were reviewed. RESULTS: Six patients (five SUNCTs and one SUNA) were identified. The pain was severe, sharp, showed fixed-laterality, involved mainly the orbito-fronto-temporal region and was associated with autonomic symptoms. Attack duration ranged from 3 to 300 seconds and frequency was 1-200 paroxysms/day. MRI showed ipsilateral pituitary adenomas to the pain in five out of five of the SUNCT patients. Patients with adenomas underwent surgery. Pathology included three prolactinomas, and one mixed adenoma and gangliocytoma. One patient has remained headache free for 4 years after surgery. One was pain free for a year, and then headaches returned with tumor recurrence. Another had major improvement, and two have not improved. Patients were generally refractory to medications. CONCLUSION: All five of our patients with typical SUNCT had pituitary tumors, with headache ipsilateral to the pituitary tumors in all cases. Tumor removal provided major improvement in three out of five patients. Medical treatment was only partially effective.
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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".