Amitriptyline for Refractory Idiopathic Intractable Hiccups: A Case Report
Bibliographic record
Abstract
OBJECTIVE: Intractable hiccups, which are hiccups that can last longer than 1 month, may be very debilitating for patients. With limited evidence and a lack of treatment guidelines, refractory hiccups can be difficult to manage. We aim to present a case of refractory idiopathic intractable hiccups treated with amitriptyline in conjunction with other medications shown to produce hiccups relief. MATERIALS AND METHODS: The patient's electronic health record, direct patient care experiences, and a systematic literature review were used for this case report. We report a 53-year-old male patient with refractory idiopathic intractable hiccups. Treatment was improved with the addition of amitriptyline to his regimen of medications used for hiccups management. Medline and PubMed were searched using the key terms "hiccup" or "singultus" and "amitriptyline." RESULTS: The literature search yielded 3 unique articles, which resulted in 4 unique cases with intractable hiccups responding to amitriptyline therapy. In all cases, patients tried multiple medications before amitriptyline initiation. CONCLUSIONS: This is the first case in over 30 years providing additional evidence for amitriptyline use in the relief of intractable hiccups. Amitriptyline may be more useful in patients experiencing intractable hiccups with comorbid mood disorders and in cases of suspected psychogenic origin.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".