Objective: In this study, we aim to evaluate trends in the condition of fetuses and neonates with hemolytic disease at the time of first intrauterine transfusion (IUT) and at birth, in relation to routine first-trimester antibody screening, referral guidelines, and centralization of fetal therapy.
Method: We conducted a 30-year cohort study including all women and fetuses treated with IUT for red cell alloimmunization at the Dutch national referral center for fetal therapy.
Results: Six hundred forty-five fetuses received 1852 transfusions between 1 January 1987 and 31 December 2016. After the introduction of routine first-trimester antibody screening, the hydrops rate declined from 39% to 15% (OR 0.284, 95% CI, 0.19-0.42, P < 0.001). In the last time cohort, only one fetus presented with severe hydrops (OR 0.482, 95% CI, 0.38-0.62, P < 0.001). Infants are born less often <32 weeks (OR 0.572, 95% CI, 0.39-0.83, P = 0.004) and with higher neonatal hemoglobin (P < 0.001). Neonatal hemoglobin was positively independently associated with gestational age at birth, fetal hemoglobin, and additional intraperitoneal transfusion at last IUT.
Conclusion: Severe alloimmune hydrops, a formerly often lethal condition, has practically disappeared, most likely as a result of the introduction of routine early alloantibody screening, use of national guidelines, and pooling of expertise in national reference laboratories and a referral center for fetal therapy.
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http://dx.doi.org/10.1002/pd.5355 | DOI Listing |
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December 2024
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GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macao Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou Laboratory, Guangzhou Medical University, Guangzhou, China.
Cell type deconvolution methods can impute cell proportions from bulk transcriptomics data, revealing changes in disease progression or organ development. But benchmarking studies often use simulated bulk data from the same source as the reference, which limits its application scenarios. This study examines batch effects in deconvolution and introduces SCCAF-D, a computational workflow that ensures a Pearson Correlation Coefficient above 0.
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Imaging flow cytometry allows image-activated cell sorting (IACS) with enhanced feature dimensions in cellular morphology, structure, and composition. However, existing IACS frameworks suffer from the challenges of 3D information loss and processing latency dilemma in real-time sorting operation. Herein, we establish a neuromorphic-enabled video-activated cell sorter (NEVACS) framework, designed to achieve high-dimensional spatiotemporal characterization content alongside high-throughput sorting of particles in wide field of view.
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