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Record W2124045568 · doi:10.1186/1477-7827-11-7

Nimodipine, a calcium channel blocker, delays the spontaneous LH surge in women with regular menstrual cycles: a prospective pilot study

2013· article· en· W2124045568 on OpenAlexaff
Dan Nayot, S. Klachook, Robert F. Casper

Bibliographic record

VenueReproductive Biology and Endocrinology · 2013
Typearticle
Languageen
FieldMedicine
TopicOvarian function and disorders
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMenstrual cycleNimodipineMedicineSurgeInternal medicineAnesthesiaEndocrinologyHormoneCalciumPhysics

Abstract

fetched live from OpenAlex

BACKGROUND: Currently GnRH analogue injections are used to prevent premature LH surges in women undergoing assisted reproductive technology. This was a pilot study to determine the safety and effectiveness of nimodipine, an oral calcium channel blocker, to delay the mid-cycle spontaneous LH surge in women with regular menstrual cycles. METHODS: Eight women with regular menstrual cycles self-monitored three consecutive cycles for the day of an LH surge by daily urine assay. The first and third cycles were observatory. In the second cycle, subjects took nimodipine 60 mg by mouth three times daily for four days, starting two days prior to the expected LH surge day based on cycle one. RESULTS: The LH surge day in cycle 2 (nimodipine) was significantly delayed in comparison to both observatory cycle 1 (15.5+/-3.4 vs 14.0+/-2.8 days; p=0.033) and cycle 3 (15.1+/-3.5 vs 13.1+/-2.4 days; p=0.044). There was no difference in the LH surge day between the two observatory cycles (13.4+/-2.4 vs 13.1+/-2.4 days; p=0.457). Three patients experienced a mild headache. CONCLUSIONS: There was a statistically significant delay in the spontaneous LH surge day in the treatment cycle in comparison to both observatory cycles. Nimopidine should be further investigated as an oral alternative to delay a spontaneous LH surge.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.019
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.020
GPT teacher head0.260
Teacher spread0.241 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

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