RESUMO
The association between Medically Assisted Reproduction (MAR) and thromboembolic complications has been reported widely in multiple published studies. Although venous thromboembolism (VTE) is not thought to be a common complication of MAR, it is associated with high morbidity and is often preventable. Since VTE usually occurs after completion of MAR treatment and is often managed outside of the treating fertility unit, these complications are likely to be underreported and there may be limited awareness of the risks among clinicians. As we continue to see a rise in the total number of MAR treatment cycles, particularly in women over 40 years of age, along with a steady increase in the number of fertility preservation cycles for both medical and social indications, it is likely that we will see an increase in absolute numbers of VTE complications. Currently, there is a lack of management guidance and reporting of VTE events associated with assisted conception treatment. The aim of this guidance is to provide clinicians with information on VTE risk factors, guidance on assessing VTE risk and the best practice recommendations on risk reducing strategies for individuals at risk of VTE undergoing ovarian stimulation and embryo transfer cycles.
Assuntos
Técnicas de Reprodução Assistida , Tromboembolia Venosa , Feminino , Humanos , Fatores de Risco , Reino Unido , Tromboembolia Venosa/prevenção & controle , Sociedades Médicas/normasRESUMO
PURPOSE: Utilising non-invasive imaging parameters to assess human oocyte fertilisation, development and implantation; and their influence on transcriptomic profiles. METHODS: A ranking tool was designed using imaging data from 957 metaphase II stage oocytes retrieved from 102 patients undergoing ART. Hoffman modulation contrast microscopy was conducted with an Olympus IX53 microscope. Images were acquired prior to ICSI and processed using ImageJ for optical density and grey-level co-occurrence matrices texture analysis. Single-cell RNA sequencing of twenty-three mature oocytes classified according to their competence was performed. RESULT(S): Overall fertilisation, blastulation and implantation rates were 73.0%, 62.6% and 50.8%, respectively. Three different algorithms were produced using binary logistic regression methods based on "optimal" quartiles, resulting in an accuracy of prediction of 76.6%, 67% and 80.7% for fertilisation, blastulation and implantation. Optical density, gradient, inverse difference moment (homogeneity) and entropy (structural complexity) were the parameters with highest predictive properties. The ranking tool showed high sensitivity (68.9-90.8%) but with limited specificity (26.5-62.5%) for outcome prediction. Furthermore, five differentially expressed genes were identified when comparing "good" versus "poor" competent oocytes. CONCLUSION(S): Imaging properties can be used as a tool to assess differences in the ooplasm and predict laboratory and clinical outcomes. Transcriptomic analysis suggested that oocytes with lower competence may have compromised cell cycle either by non-reparable DNA damage or insufficient ooplasmic maturation. Further development of algorithms based on image parameters is encouraged, with an increased balanced cohort and validated prospectively in multicentric studies.