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Record W2033646917 · doi:10.15273/dmj.vol40no2.4537

Using Gabapentin to Treat Chronic Cough: A Review of Literature

2014· review· en· W2033646917 on OpenAlexaffvenue
Jeremie Gauthier, Matthew J. Morrison

Bibliographic record

VenueDalhousie Medical Journal · 2014
Typereview
Languageen
FieldMedicine
TopicRespiratory and Cough-Related Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsGabapentinDiscontinuationMedicineChronic coughIntensive care medicineAnticonvulsantRefractory (planetary science)AnesthesiaEpilepsyInternal medicineAlternative medicineAsthmaPsychiatryPathology

Abstract

fetched live from OpenAlex

Chronic cough is a multifactorial symptom, and a legitimate medical concern, that often requires further investigation if resolution is not attained with initial therapeutic options. Gabapentin, an anticonvulsant used for a myriad of disease states, is suggested to have a positive effect on chronic cough. Pertinent literature was searched for, and critically appraised in order to determine the potential value of gabapentin in the treatment of chronic cough. Findings from salient literature demonstrate a decrease in both frequency and severity of chronic cough as primary endpoints. However, discontinuation of gabapentin precipitated a return of symptoms towards baseline values, which may suggest that sustained use is required to maintain such benefits. It is felt that, in light of recent literature, the use of gabapentin as an off-label treatment for chronic cough, refractory to typical treatment regimens, may be a viable option for select patients.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.085
GPT teacher head0.449
Teacher spread0.364 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2014
Admission routes2
Has abstractyes

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