Genetic Counseling

School of Health and Human Sciences

Nikki FlemingTwin-Twin Transfusion Syndrome: A Systematic Review and Meta-Analysis
Capstone Project Committee: 
Jessica Hooks, MS, CGC, Saju Joy, MD, Courtney Stephenson, MD, Randi Stewart, MS, CGC, Scott Richter, PhD (Statistical Consultant)
Twin-Twin Transfusion Syndrome (TTTS) is a problem of unequal sharing of placental supply in monochorionic twins, often leading to fetal demise. Research on TTTS is well-represented in the scientific literature, but individualized, optimal treatment protocols have yet to be determined. In order to have the most successful neonatal outcomes, it is important to determine what presenting information will lead to the best treatment decision. Once identified, this data must be easily organized, stored, and retrieved in order to be shared within and between fetal care centers. Thus, a database consisting of theory- and research-driven data points that predict staging and intervention, diagnosis, and ultimate outcome of the disease is a necessary development in learning more about treatment for TTTS. This study is a methodical and systematic meta-synthesis of relevant research articles about TTTS to identify data points recommended for inclusion in a TTTS database. These data points were included in a survey sent to all NSGC members to confirm the accuracy and reliability of these factors based on the experience of other fetal therapy experts. Results noted many fetal care centers have databases, but almost 90% believed standardized data points would be helpful. The data also noted inconsistencies and non-consensus between genetic counselors’ responses and the literature review in respect to which data points would be most relevant to include in a database for patients with TTTS. This further emphasizes the need for standardized data points based in primary literature among fetal care centers for patients with TTTS. Suggestions for database construction are discussed. Standardizing databases as such between TTTS centers may help to answer research questions effectively and efficiently in the future.
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