B.05 Hemi-laryngopharyngeal spasm (HELPS) syndrome: The discovery, cure, and characterization of a new neurological condition
Bibliographic record
Abstract
Background: We published the world’s first case of hemi-laryngpharyngeal spasm (HELPS) syndrome cured by microvascular decompression (MVD) of the Xth cranial nerve in 2016. We now present a small cohort of patients (n=3) successfully treated with surgery in order to better delineate the common characteristics of this syndrome, diagnostic tests of choice, nuances of their surgical care and outcomes of their treatment. Methods: The history and physical examination of three patients with HELPS syndrome are presented. Pre-operative laryngoscopy, neuroimaging, response to botox and intra-operative videos are detailed. Post-operative outcome and complications are presented. Results: Each patient reported similar motor (choking) and sensory (coughing) features in their history. Episodic choking relentlessly progressed over the years until it occurred while sleeping and with frightening severity prompting tracheostomy in one patient and intubation in another. A “tickling” sensation deep in the throat triggered episodic coughing that worsened over the years until it occurred while sleeping and with frightening severity (syncope and incontinence). Conclusions: A review of the literature suggests that patients with similar symptoms, often called episodic laryngospasm in the past, have been treated with psychotherapy or antacids. With the recognition that a clearly defined subset of these patients have HELPS syndrome, we can offer them the potential of a neurosurgical cure.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".