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Record W2002588927 · doi:10.1089/jwh.2012.4180

A Randomized Trial Comparing the VIPON Tampon and Ibuprofen for Dysmenorrhea Pain Relief

2013· article· en· W2002588927 on OpenAlexaboutno aff
Jacki Witt, Julie Strickland, An‐Lin Cheng, Charlotte Curtis, John W. Calkins

Bibliographic record

VenueJournal of Women s Health · 2013
Typearticle
Languageen
FieldMedicine
TopicMenstrual Health and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIbuprofenRandomized controlled trialPain reliefGynecologyPhysical therapyAnesthesiaSurgeryPharmacology

Abstract

fetched live from OpenAlex

BACKGROUND: This study was conducted to evaluate the therapeutic efficacy of a device designed to deliver high-frequency vibratory stimulation through direct intravaginal tampon application (VIPON) compared with a low-dose over-the-counter pharmacologic treatment of dysmenorrhea. METHODS: A randomized, open-label, prospective study comparing the investigational device to an oral self-administration of the over-the-counter dose of 200-400 mg of ibuprofen with the onset of menstrual discomfort was conducted at two academic medical centers in the Midwest region of the United States. Women age 18 and older with self-reported dysmenorrhea were treated with either VIPON or a single dose of 200-400 mg of ibuprofen, randomized for each of the next four menstrual cycles, and pain reduction from baseline was measured according to the Melzack-McGill pain scale. RESULTS: Overall, both ibuprofen and VIPON have significant effects on pain reduction according to the Melzack-McGill pain scale. However, the VIPON group achieved statistically significant greater, and more rapid, pain relief at every time point when compared with the ibuprofen. CONCLUSION: VIPON tampon is a viable, nonpharmacologic option to traditional low-dose over-the-counter pharmacologic therapies for menstrual pain management with more rapid onset of action.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.034
GPT teacher head0.344
Teacher spread0.310 · 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 designRandomized trial
Domainnot available
GenreEmpirical

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

Citations6
Published2013
Admission routes1
Has abstractyes

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Same venueJournal of Women s HealthSame topicMenstrual Health and DisordersFrench-language works237,207