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Record W2781769883 · doi:10.1159/000484514

Reduced Protein C Global Assay Levels in Infertile Women with in vitro Fertilization Failure: A Pilot Study

2018· article· en· W2781769883 on OpenAlexaff
Sally El Masry, Hanan Fahmy Azzam, Maha Othman, Mohamed M. Awad

Bibliographic record

VenueActa Haematologica · 2018
Typearticle
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsQueen's University
Fundersnot available
KeywordsIn vitro fertilisationMedicineAssisted reproductive technologyAndrologyInfertilityEtiologyGynecologyInternal medicineLogistic regressionEndocrinologyBiologyPregnancyGenetics

Abstract

fetched live from OpenAlex

Protein C global is a global dotting assay that evaluates abnormalities in the protein C anticoagulant pathway. A few studies have examined this assay in relation to assisted reproductive technology (ART), but its role in infertile women with in vitro fertilization (IVF) failure remains unclear. In this study, we assessed protein C in infertile women with a history of IVF failure who were undergoing ART. We examined 45 healthy fertile women who conceived naturally, and 45 infertile women with 2 or more implantation failures undergoing ART. Both protein C and activated protein C resistance (APC-R) were evaluated. The results showed that mean protein C expressed as a normalized ratio (PCAT-NR) was significantly lower in the study group compared to the control group (0.76 ± 0.15 vs. 0.91 ± 0.14, respectively; p = 0.0001). Follow-up on ART outcomes showed that women who failed ART had significantly lower PCAT-NR compared to successful cases. PCAT-NR did not correlate with APC-R levels in the study (r = 0.125, p < 0.5) or failed ART subgroups. Using logistic regression analysis, patients with lower PCAT-NR levels showed an elevated risk of implantation failure (p = 0.04, OR 0.50, 95% CI 0.26-0.84). In conclusion, protein C global assay may play a role in the etiology of IVF failure, which might be independent of APC-R. Larger studies are encouraged to validate these findings and explore the underlying pathophysiological mechanisms.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.050
GPT teacher head0.300
Teacher spread0.250 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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