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Record W4283738317 · doi:10.1093/humrep/deac107.098

P-102 Progesterone luteal-phase support during IUI cycle should be added depending on women age and/or on previous mid-luteal progesterone assessment to promote live births

2022· article· en· W4283738317 on OpenAlexaff
C.H Petrovic, M Benchaib, Chloé Monnier, M Kavanagh, M Leflon, Sonia Asif, David S. Gardner, N Keates, Juan Hernandez-Medrano, M Tomlison, A. Millan de la Torre

Bibliographic record

VenueHuman Reproduction · 2022
Typearticle
Languageen
FieldMedicine
TopicOvarian function and disorders
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLuteal phaseInfertilityLive birthPregnancyFertilityGynecologyUnexplained infertilityObstetricsMedicinePregnancy rateAndrologyBiologyPopulationHormoneEndocrinology

Abstract

fetched live from OpenAlex

Abstract Study question To determine the Mid-luteal progesterone (MLP) threshold which could condition live-birth (LB) after IUI, and effects of additional progesterone luteal-phase support (LPS) in subsequent cycles. Summary answer MLP threshold is age-dependant. LPS should only be used if previous MLP is below the age related threshold, as its inappropriate use reduces LB rate. What is known already Progesterone is essential to prepare and maintain the uterus suitable for a possible pregnancy. During IUI, it is not clear if LPS is beneficial to obtain a live birth, and whether it should be introduced systematically or only in women with a low MLP assessment during a previous cycle. Study design, size, duration In an audit purpose, we performed a retrospective uni-centric analysis of 705 IUl cycles performed from January 2015 to March 2020 in couples which fertility work-up concluded to unexplained infertility, mild male infertility or PCOS with no pregnancy after 3 cycles of clomiphene citrate. Our primary outcome was LB. Participants/materials, setting, methods IUI was performed after ovarian stimulation with gonadotrophins. MLP was assessed using immuno assay method, days 7 post-IUI. LPS (Cyclogest® 200 mg/day) was added when consultant considered former cycle’s MLP was too low. MLP thresholds were defined without LPS using a ROC Curve, considering subgroups of patient’s age. LB rate was analyzed using Multivariate Gill Andersen models to take into account repetitions of IUI cycles. Prognostic factors for LBR were investigated using a Cox model. Main results and the role of chance Women were 33.6±3.9 years old. We obtained 99 (14%) LB. In women who didn’t receive LPS, regardless of their age, MLP threshold was 57.5 nmo/l (AUC=0.57). Multivariate logistic regression modeling identified MLP assessment as a significant prognostic factor for obtaining LB after IUI (OR = 1.668, CI95%[1.023; 2.721], p = 0.0402). When also considering women’s age, a cut-off of 36 years old was computed which allowed more fitted age-related MLP thresholds for obtaining LB after IUI. In women <36 years old, MLP threshold was 39.5 nmol/l (AUC=0.57) whereas it was 60.5 nmol/L (AUC=0.57) for age ≥36. Age-related thresholds were more predictive of LB than initial age independent threshold according to Akaike Criteria (1168.48 versus 1198.96, respectively). Using the whole population (i.e. receiving or not LPS), the multivariate analysis highlighted that, compared to women with MLP above their age related threshold who (appropriately) didn’t receive LPS: - Women below their age-related MLP threshold who appropriately receive LPS had similar LB rate: OR = 0.5474, CI95%[0.1857-1.6138], p = 0.2747. - Women below their age-related MLP threshold who didn’t receive LPS (inappropriately) had a significantly lower LB rate: OR = 0.4794, CI95%[0.2727-0.8427], p = 0.0106. - Women above their age-related MLP threshold who received LPS (inappropriately) had a significantly lower LB rate: OR = 0.5627, CI95%[0.3302-09587], p = 0.0433. Limitations, reasons for caution Because of the retrospective design of our study and because of the limited number of included couples, our results should be considered with caution. Confirmation is needed with further prospective studies with a larger number of participants. Wider implications of the findings Our study highlight for the first time the impact of age on the LPS strategy after IUI, and emphases the need for personalized fertility medicine based on previous MLP assessment when considering LPS. Trial registration number No needed, NHS Audit

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.054
GPT teacher head0.349
Teacher spread0.295 · 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 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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