Macroglossia in neurosurgery
Bibliographic record
Abstract
Abstract Macroglossia, an abnormal swelling of the tongue, is a rare post-operative complication often associated with serious airway obstruction and prolonged intubations. Currently, there is a paucity of information on the true incidence, aetiology, and complications associated with macroglossia. A thorough review of the literature was carried out so as to summarise the characteristics of reported cases of macroglossia and to present potential treatments and preventive strategies. A literature search was conducted in PubMed to identify human case reports of macroglossia after neurosurgical procedures including spine, published in English from 1974 to December 2015. A total of 26 reports with 36 cases of macroglossia were identified. Macroglossia was most commonly reported after sub-occipital and/or posterior fossa craniotomies and spine surgeries in prone or park-bench positions. It is more common after procedures lasting >8 h. The aetiology of macroglossia is multi-factorial and possible mechanisms included local mechanical tongue compression interfering with venous and/or lymphatic drainage, regional venous thrombosis and/or local trauma. Complications included airway obstruction, re-intubation, difficult re-intubation, prolonged intubation and Intensive Care Unit stay and tongue necrosis. Prevention, awareness of the possibility, and early recognition are the best forms of treatment.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".