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Objective: To determine whether packed red blood cell (PRBC) transfusion affects post-prandial superior mesenteric artery blood flow velocities (SMA BFVs) in very-low birth weight (VLBW) neonates and if so, at what time point after transfusion restoration of previous SMA BFV patterns occurs.

Design/Methods: VLBW pre-term neonates, older than 14 days and tolerating bolus enteral feedings administered every 3?h were enrolled in this prospective observational study. Pulsed Doppler ultrasound was used to measure pre- and post-prandial (at 45?min) time-averaged mean, peak and end diastolic velocities (TAMV, PSV, EDV) immediately before and after 15?ml/kg of PRBC transfusion was given over 3?h; patent ductus arteriosus (PDA) status was also evaluated. Subsequent pre- and post-prandial SMA BFVs were recorded 24 and 48?h after the transfusion.

Results: Pre- and post-prandial measurements were obtained for 21 out of 25 enrolled infants. Post-prandial SMA BFVs were attenuated during the feedings immediately after transfusion; at 24 and 48?h after transfusion, changes in post-prandial SMA BFVs were similar to those measured prior to transfusion; the presence of the PDA did not affect results.

Conclusions: PRBC transfusion blunted SMA BFV responses to feedings immediately after the transfusion with normalization observed 24?h post-transfusion.  相似文献   
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Prevalence of osteoporosis is more than 50% in older adults, yet current clinical methods for diagnosis that rely on areal bone mineral density (aBMD) fail to detect most individuals who have a fragility fracture. Bone fragility can manifest in different forms, and a “one-size-fits-all” approach to diagnosis and management of osteoporosis may not be suitable. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides additive information by capturing information about volumetric density and microarchitecture, but interpretation is challenging because of the complex interactions between the numerous properties measured. In this study, we propose that there are common combinations of bone properties, referred to as phenotypes, that are predisposed to different levels of fracture risk. Using HR-pQCT data from a multinational cohort (n = 5873, 71% female) between 40 and 96 years of age, we employed fuzzy c-means clustering, an unsupervised machine-learning method, to identify phenotypes of bone microarchitecture. Three clusters were identified, and using partial correlation analysis of HR-pQCT parameters, we characterized the clusters as low density, low volume, and healthy bone phenotypes. Most males were associated with the healthy bone phenotype, whereas females were more often associated with the low volume or low density bone phenotypes. Each phenotype had a significantly different cumulative hazard of major osteoporotic fracture (MOF) and of any incident osteoporotic fracture (p < 0.05). After adjustment for covariates (cohort, sex, and age), the low density followed by the low volume phenotype had the highest association with MOF (hazard ratio = 2.96 and 2.35, respectively), and significant associations were maintained when additionally adjusted for femoral neck aBMD (hazard ratio = 1.69 and 1.90, respectively). Further, within each phenotype, different imaging biomarkers of fracture were identified. These findings suggest that osteoporotic fracture risk is associated with bone phenotypes that capture key features of bone deterioration that are not distinguishable by aBMD. © 2021 American Society for Bone and Mineral Research (ASBMR).  相似文献   
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