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Record W2223517489 · doi:10.1093/humrep/dev099

Effects of over-the-counter analgesic use on reproductive hormones and ovulation in healthy, premenopausal women

2015· article· en· W2223517489 on OpenAlexaff
Rebecca A. Matyas, Sunni L. Mumford, Karen C. Schliep, Katherine A. Ahrens, Lindsey A. Sjaarda, Neil J. Perkins, Amanda C. Filiberto, Donald R. Mattison, Shvetha M. Zarek, Jean Wactawski‐Wende, Enrique F. Schisterman

Bibliographic record

VenueHuman Reproduction · 2015
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsUniversity of Ottawa
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human DevelopmentU.S. Public Health ServiceNational Institutes of HealthUniversity of Oxford
KeywordsMedicineAnovulationAnalgesicLuteal phaseFollicular phaseMenstrual cycleOvulationMenstruationLuteinizing hormoneConfoundingOdds ratioGynecologyHormoneObstetricsPhysiologyInternal medicineAnesthesiaPolycystic ovaryObesity

Abstract

fetched live from OpenAlex

STUDY QUESTION: Does use of commonly used over-the-counter (OTC) pain medication affect reproductive hormones and ovulatory function in premenopausal women? SUMMARY ANSWER: Few associations were found between analgesic medication use and reproductive hormones, but use during the follicular phase was associated with decreased odds of sporadic anovulation after adjusting for potential confounders. WHAT IS KNOWN ALREADY: Analgesic medications are the most commonly used OTC drugs among women, but their potential effects on reproductive function are unclear. STUDY DESIGN, SIZE, DURATION: The BioCycle Study was a prospective, observational cohort study (2005-2007) which followed 259 women for one (n = 9) or two (n = 250) menstrual cycles. PARTICIPANTS, SETTING, METHODS: Two hundred and fifty-nine healthy, premenopausal women not using hormonal contraception and living in western New York state. Study visits took place at the University at Buffalo. MAIN RESULTS AND THE ROLE OF CHANCE: During study participation, 68% (n = 175) of women indicated OTC analgesic use. Among users, 45% used ibuprofen, 33% acetaminophen, 10% aspirin and 10% naproxen. Analgesic use during the follicular phase was associated with decreased odds of sporadic anovulation after adjusting for age, race, body mass index, perceived stress level and alcohol consumption (OR 0.36 [0.17, 0.75]). Results remained unchanged after controlling for potential confounding by indication by adjusting for 'healthy' cycle indicators such as amount of blood loss and menstrual pain during the preceding menstruation. Moreover, luteal progesterone was higher (% difference = 14.0, -1.6-32.1, P = 0.08 adjusted) in cycles with follicular phase analgesic use, but no associations were observed with estradiol, LH or FSH. LIMITATIONS, REASONS FOR CAUTION: Self-report daily diaries are not validated measures of medication usage, which could lead to some classification error of medication use. We were also limited in our evaluation of aspirin and naproxen which were used by few women. WIDER IMPLICATIONS OF THE FINDINGS: The observed associations between follicular phase analgesic use and higher progesterone and a lower probability of sporadic anovulation indicate that OTC pain medication use is likely not harmful to reproduction function, and certain medications possibly improve ovulatory function. STUDY FUNDING/COMPETING INTERESTS: This work was supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health (contract # HHSN275200403394C). The authors have no conflicts of interest to disclose.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.039
GPT teacher head0.320
Teacher spread0.281 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations18
Published2015
Admission routes1
Has abstractyes

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