Objective: This study aimed to determine the safety and clinical effect of artificial shrinkage (AS) in terms of assisted hatching of fresh blastocysts. Also, we evaluated the correlation between patient age and the effect of AS on clinical outcome.
Methods: Two AS methods, using a 29-gauge needle and laser pulse, were compared. Seventy-three blastocysts were shrunk using a 29-gauge needle and the same number of other blastocysts were shrunk by a laser pulse. We evaluated the shrunken blastocysts hourly and considered them viable if they re-expanded >70%. Blastocyst transfer cycles (n=134) were divided into two groups: a control group consisted of the cycles whose intact embryos were transferred (n=100), while the AS group consisted of the cycles whose embryos were replaced following AS (n=34). The implantation and pregnancy rates of the control group and AS group were compared (p<0.05).
Results: The re-expansion rates of the 29-gauge needle and laser pulse AS groups were similar (56 [76.7%] vs. 62 [84.9%], respectively). All of the remaining shrunken blastocysts were re-expanded within 2 hours. There was no degeneration of shrunken blastocysts. The total and clinical pregnancy rate of the AS group (23 [67.6%]; 20 [58.8%], respectively) was significantly higher than that of the control group (47 [47.0%]; 39 [39.0%], respectively). In the older patient group, there was no difference in the clinical outcomes between the AS and control groups.
Conclusion: These results suggest that AS of blastocoele cavity, followed by the transfer, would be a useful approach to improve the clinical outcome in cycles in which fresh blastocyst stage embryos are transferred.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3283060 | PMC |
http://dx.doi.org/10.5653/cerm.2011.38.2.87 | DOI Listing |
J Endovasc Ther
January 2025
Department of Vascular Surgery, Rijnstate, Arnhem, The Netherlands.
Purpose: The goal of the study described in this protocol is to build a multimodal artificial intelligence (AI) model to predict abdominal aortic aneurysm (AAA) shrinkage 1 year after endovascular aneurysm repair (EVAR).
Methods: In this retrospective observational multicenter study, approximately 1000 patients will be enrolled from hospital records of 5 experienced vascular centers. Patients will be included if they underwent elective EVAR for infrarenal AAA with initial assisted technical success and had imaging available of the same modality preoperatively and at 1-year follow-up (CTA-CTA or US-US).
Int J Med Inform
January 2025
Background: Obesity, now the fifth leading global cause of death, has seen a dramatic rise in prevalence over the last forty years. It significantly increases the risk of diseases such as type 2 diabetes and cardiovascular disease. Early identification of obesity risk allows for preventative actions against obesity-related factors.
View Article and Find Full Text PDFSci Rep
January 2025
Emergency Medicine Laboratory and the Department of Emergency, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, Sichuan, China.
To develop and evaluate a predictive model for intensive care unit (ICU) admission among patients with acute sedative-hypnotic overdose. We conducted a retrospective analysis of patients admitted to the emergency department of West China Hospital, Sichuan University, between October 11, 2009, and December 31, 2023. Patients were divided into ICU and non-ICU groups based on admission criteria including the need for blood purification therapy, organ support therapy (ventilatory support, vasoactive drugs, renal replacement therapy, artificial liver), or post-cardiopulmonary resuscitation.
View Article and Find Full Text PDFAnal Biochem
January 2025
Rehabilitation Medicine College, Henan University of Chinese Medicine, Zhengzhou, Henan, China. Electronic address:
Background: Multiple sclerosis (MS) is an autoimmune inflammatory disorder that causes neurological disability. Dysregulated lipid metabolism contributes to the pathogenesis of MS. This study aimed to identify lipid metabolism-related gene markers and construct a diagnostic model for MS.
View Article and Find Full Text PDFJ Orthop Surg Res
January 2025
Department of Orthopedic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Background: Osteoarthritis (OA), characterized by progressive degeneration of cartilage and reactive proliferation of subchondral bone, stands as a prevalent condition in orthopedic clinics. However, the precise mechanisms underlying OA pathogenesis remain inadequately explored.
Methods: In this study, Random Forest (RF), Least Absolute Shrinkage and Selection Operator (LASSO), and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) machine learning techniques were employed to identify hub genes.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!