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Record W2910025422 · doi:10.1093/humupd/dmy044

Conventional and modern markers of endometrial receptivity: a systematic review and meta-analysis

2018· review· en· W2910025422 on OpenAlexaboutno aff
Laurentiu Craciunas, Ioannis Gallos, Justin Chu, T. Bourne, Siobhan Quenby, Jan J. Brosens, Arri Coomarasamy

Bibliographic record

VenueHuman Reproduction Update · 2018
Typereview
Languageen
FieldImmunology and Microbiology
TopicReproductive System and Pregnancy
Canadian institutionsnot available
FundersMedical Research CouncilNational Institute for Health and Care Research
KeywordsMeta-analysisGynecologyReceptivityMedicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Early reproductive failure is the most common complication of pregnancy with only 30% of conceptions reaching live birth. Establishing a successful pregnancy depends upon implantation, a complex process involving interactions between the endometrium and the blastocyst. It is estimated that embryos account for one-third of implantation failures, while suboptimal endometrial receptivity and altered embryo-endometrial dialogue are responsible for the remaining two-thirds. Endometrial receptivity has been the focus of extensive research for over 80 years, leading to an indepth understanding of the processes associated with embryo-endometrial cross-talk and implantation. However, little progress has been achieved to translate this understanding into clinically meaningful prognostic tests and treatments for suboptimal endometrial receptivity. OBJECTIVE AND RATIONALE: The objective of this systematic review was to examine the evidence from observational studies supporting the use of endometrial receptivity markers as prognostic factors for pregnancy outcome in women wishing to conceive, in order to aid clinicians in choosing the most useful marker in clinical practice and for informing further research. SEARCH METHODS: The review protocol was registered with PROSPERO (CRD42017077891). MEDLINE and Embase were searched for observational studies published from inception until 26 February 2018. We included studies that measured potential markers of endometrial receptivity prior to pregnancy attempts and reported the subsequent pregnancy outcomes. We performed association and accuracy analyses using clinical pregnancy as an outcome to reflect the presence of receptive endometrium. The Newcastle-Ottawa scale for observational studies was employed to assess the quality of the included studies. OUTCOMES: We included 163 studies (88 834 women) of moderate overall quality in the narrative synthesis, out of which 96 were included in the meta-analyses. Studies reported on various endometrial receptivity markers evaluated by ultrasound, endometrial biopsy, endometrial fluid aspirate and hysteroscopy in the context of natural conception, IUI and IVF. Associations were identified between clinical pregnancy and various endometrial receptivity markers (endometrial thickness, endometrial pattern, Doppler indices, endometrial wave-like activity and various molecules); however, their poor ability to predict clinical pregnancy prevents them from being used in clinical practice. Results from several modern molecular tests are promising and further data are awaited. WIDER IMPLICATIONS: The post-test probabilities from our analyses may be used in clinical practice to manage couples' expectations during fertility treatments (IUI and IVF). Conventionally, endometrial receptivity is seen as a dichotomous outcome (present or absent), but we propose that various levels of endometrial receptivity exist within the window of implantation. For instance, different transcriptomic signatures could represent varying levels of endometrial receptivity, which can be linked to different pregnancy outcomes. Many studies reported the means of a particular biomarker in those who achieved a pregnancy compared with those who did not. However, extreme values of a biomarker (as opposite to the means) may have significant prognostic and diagnostic implications that are not captured in the means. Therefore, we suggest reporting the outcomes by categories of biomarker levels rather than reporting means of biomarker levels within clinical outcome groups.

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)0.015
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.042
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0180.030
Bibliometrics0.0070.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.107
GPT teacher head0.346
Teacher spread0.238 · 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 designMeta-analysis
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

Citations575
Published2018
Admission routes1
Has abstractyes

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