Uterus Transplant in Women With Absolute Uterine-Factor Infertility.

Importance: Uterus transplant in women with absolute uterine-factor infertility offers the possibility of carrying their own pregnancy. Objective: To determine whether uterus transplant is feasible and safe and results in births of healthy infants. Design, Setting, and Participants: A case series including 20 participants with uterine-factor infertility and at least 1 functioning ovary who underwent uterus transplant in a large US tertiary care center between September 14, 2016, and August 23, 2019. Intervention: The uterus transplant (from 18 living donors and 2 deceased donors) was surgically placed in an orthotopic position with vascular anastomoses to the external iliac vessels. Participants received immunosuppression until the transplanted uterus was removed following 1 or 2 live births or after graft failure. Main Outcomes and Measures: Uterus graft survival and subsequent live births. Results: Of 20 participants (median age, 30 years [range, 20-36]; 2 Asian, 1 Black, and 16 White), 14 (70%) had a successful uterus allograft; all 14 recipients gave birth to at least 1 live-born infant. Eleven of 20 recipients had at least 1 complication. Maternal and/or obstetrical complications occurred in 50% of the successful pregnancies, with the most common being gestational hypertension (2 [14%]), cervical insufficiency (2 [14%]), and preterm labor (2 [14%]). Among the 16 live-born infants, there were no congenital malformations. Four of 18 living donors had grade 3 complications. Conclusions and Relevance: Uterus transplant was technically feasible and was associated with a high live birth rate following successful graft survival. Adverse events were common, with medical and surgical risks affecting recipients as well as donors. Congenital abnormalities and developmental delays have not occurred to date in the live-born children. Trial Registration: ClinicalTrials.gov Identifier: NCT02656550.

Stepwise development and expansion of an abdominal normothermic regional perfusion program for donation after circulatory determination of death organ procurement.

INTRODUCTION: Normothermic regional perfusion (NRP) represents an innovative technology that improves the outcomes for liver and kidney recipients of donation after circulatory determination of death (DCD) organs but protocols for abdominal-only NRP (A-NRP) DCD are lacking in the US. METHODS: We describe the implementation and expansion strategies of a transplant-center-based A-NRP DCD program that has grown in volume, geographical reach, and donor acceptance parameters, presented as four eras. RESULTS: In the implementation era, two donors were attempted, and one liver graft was transplanted. In the local expansion era, 33% of attempted donors resulted in transplantation and 42% of liver grafts from donors who died within the functional warm ischemic time (fWIT) limit were transplanted. In the Regional Expansion era, 25% of attempted donors resulted in transplantation and 50% of liver grafts from donors who died within the fWIT limit were transplanted. In the Donor Acceptance Expansion era, 46% of attempted donors resulted in transplantation and 72% of liver grafts from donors who died within the fWIT limit were transplanted. Eight discarded grafts demonstrated a potential opportunity for utilization. CONCLUSION: The stepwise approach to building an A-NRP program described here can serve as a model for other transplant centers.

A cost comparison of liver acquisition fees for donation after circulatory death versus donation after brain death donors.

Donation after circulatory death (DCD) donors now represent over 30% of the deceased donor pool in the United States. Compared to donation after brain death, DCD is less likely to result in transplantation. For each potential donor whose organs cannot be utilized for transplantation (ie, dry run), fees are associated with the attempted donation, which add to the overall costs of organ acquisition. To better characterize the true costs of DCD liver acquisition, we performed a cost comparison of the fees associated with organ acquisition for DCD versus donation after brain death at a single transplant institute that comprises 2 liver transplant centers. Cost, recipient, and transportation data for all cases, including fees associated with liver acquisition from July 1, 2019, to October 31, 2021, were collected. We found that the total cost of DCD liver acquisition per liver transplant was $15,029 more than that for donation after brain death donation, with 18% of the costs of the DCD transplant attributed to dry runs. Overall, the costs associated with DCD transplantation accounted for 34.5% of the total organ acquisition costs; however, DCD transplantation accounted for 30.3% of the transplantation volume. Because the expansion of DCD is essential to increasing the availability of liver grafts for transplantation, strategies need to be implemented to decrease the costs associated with dry runs, including using local recovery, transferring donors to hospitals close to transplant centers, and performing more prerecovery organ analysis. Moreover, these strategies are needed to ensure that financial disincentives to DCD procurement and utilization do not reverse the gains made by expanding the organ donor pool using machine perfusion technologies.

Web-based processing of physiological noise in fMRI: addition of the PhysIO toolbox to CBRAIN.

Neuroimaging research requires sophisticated tools for analyzing complex data, but efficiently leveraging these tools can be a major challenge, especially on large datasets. CBRAIN is a web-based platform designed to simplify the use and accessibility of neuroimaging research tools for large-scale, collaborative studies. In this paper, we describe how CBRAIN's unique features and infrastructure were leveraged to integrate TAPAS PhysIO, an open-source MATLAB toolbox for physiological noise modeling in fMRI data. This case study highlights three key elements of CBRAIN's infrastructure that enable streamlined, multimodal tool integration: a user-friendly GUI, a Brain Imaging Data Structure (BIDS) data-entry schema, and convenient in-browser visualization of results. By incorporating PhysIO into CBRAIN, we achieved significant improvements in the speed, ease of use, and scalability of physiological preprocessing. Researchers now have access to a uniform and intuitive interface for analyzing data, which facilitates remote and collaborative evaluation of results. With these improvements, CBRAIN aims to become an essential open-science tool for integrative neuroimaging research, supporting FAIR principles and enabling efficient workflows for complex analysis pipelines.

Differential Expression of Anomalous Self-Experiences in Spontaneous Speech in Clinical High-Risk and Early-Course Psychosis Quantified by Natural Language Processing.

BACKGROUND: Basic self-disturbance, or anomalous self-experiences (ASEs), is a core feature of the schizophrenia spectrum. We propose a novel method of natural language processing to quantify ASEs in spoken language by direct comparison to an inventory of self-disturbance, the Inventory of Psychotic-Like Anomalous Self-Experiences (IPASE). We hypothesized that there would be increased similarity in open-ended speech to the IPASE items in individuals with early-course psychosis (PSY) compared with healthy individuals, with clinical high-risk (CHR) individuals intermediate in similarity. METHODS: Open-ended interviews were obtained from 170 healthy control participants, 167 CHR participants, and 89 PSY participants. We calculated the semantic similarity between IPASE items and "I" sentences from transcribed speech samples using S-BERT (Sentence Bidirectional Encoder Representation from Text). Kolmogorov-Smirnov tests were used to compare distributions across groups. A nonnegative matrix factorization of cosine similarity was performed to rank IPASE items. RESULTS: Spoken language of CHR individuals had the greatest semantic similarity to IPASE items when compared to both healthy control (s = 0.44, p < 10-14) and PSY (s = 0.36, p < 10-6) individuals, while IPASE scores were higher among PSY than CHR group participants. In addition, the nonnegative matrix factorization approach produced a data-driven domain that differentiated the CHR group from the others. CONCLUSIONS: We found that open-ended interviews elicited language with increased semantic similarity to the IPASE by participants in the CHR group compared with patients with psychosis. This demonstrates the utility of these methods for differentiating patients from healthy control participants. This complementary approach has the capacity to scale to large studies investigating phenomenological features of schizophrenia and potentially other clinical populations.

An overview of clustering methods with guidelines for application in mental health research.

Cluster analyzes have been widely used in mental health research to decompose inter-individual heterogeneity by identifying more homogeneous subgroups of individuals. However, despite advances in new algorithms and increasing popularity, there is little guidance on model choice, analytical framework and reporting requirements. In this paper, we aimed to address this gap by introducing the philosophy, design, advantages/disadvantages and implementation of major algorithms that are particularly relevant in mental health research. Extensions of basic models, such as kernel methods, deep learning, semi-supervised clustering, and clustering ensembles are subsequently introduced. How to choose algorithms to address common issues as well as methods for pre-clustering data processing, clustering evaluation and validation are then discussed. Importantly, we also provide general guidance on clustering workflow and reporting requirements. To facilitate the implementation of different algorithms, we provide information on R functions and libraries.

Neonatal Outcomes after Uterus Transplantation: Dallas Uterus Transplant Study.

OBJECTIVE: Limited data are available on the outcome of infants born after uterus transplantation. Our aim was to describe the hospital course and laboratory findings in the first 2 months of life of the 12 infants born in the Dallas UtErus Transplant Study (DUETS). STUDY DESIGN: Based on the trial protocol, information about infants was collected in a prospective fashion, including infant demographics, hospital course, and laboratory values. RESULTS: Twelve infants were delivered, all by cesarean section, from 11 mothers who had undergone uterus transplantation (one mother had two pregnancies and delivered two babies). All pregnancies were singleton. The mothers received immunosuppressive therapy, and one had a rejection episode that was detected during pregnancy. The rejection episode resolved after steroid treatment. The infants had a median gestational age of 366/7 weeks (range: 306/7-380/7 weeks) and median birth weight of 2,920 g (range: 1,770-3,470 g). The lowest Apgar's score at 5 minutes was 8. All infants were appropriate size for gestational age. Two infants presented with bandemia but negative blood cultures. At 2 months of age, all infants achieved the developmental and behavioral milestones outlined by the American Academy of Pediatrics. CONCLUSION: The 12 infants born from mothers with uterus transplants had a neonatal course that reflected the gestational age at delivery. No baby was born with an identified malformation or organ dysfunction. Longer follow-up and a larger number of infants are needed to confirm these observations. KEY POINTS: · Normal fetal development after uterus transplantation.. · No baby was born with malformations or showed any organ dysfunction.. · At 2 months, all infants achieved appropriate developmental and behavioral milestones..

Site effects how-to and when: An overview of retrospective techniques to accommodate site effects in multi-site neuroimaging analyses.

Site differences, or systematic differences in feature distributions across multiple data-acquisition sites, are a known source of heterogeneity that may adversely affect large-scale meta- and mega-analyses of independently collected neuroimaging data. They influence nearly all multi-site imaging modalities and biomarkers, and methods to compensate for them can improve reliability and generalizability in the analysis of genetics, omics, and clinical data. The origins of statistical site effects are complex and involve both technical differences (scanner vendor, head coil, acquisition parameters, imaging processing) and differences in sample characteristics (inclusion/exclusion criteria, sample size, ancestry) between sites. In an age of expanding international consortium research, there is a growing need to disentangle technical site effects from sample characteristics of interest. Numerous statistical and machine learning methods have been developed to control for, model, or attenuate site effects - yet to date, no comprehensive review has discussed the benefits and drawbacks of each for different use cases. Here, we provide an overview of the different existing statistical and machine learning methods developed to remove unwanted site effects from independently collected neuroimaging samples. We focus on linear mixed effect models, the ComBat technique and its variants, adjustments based on image quality metrics, normative modeling, and deep learning approaches such as generative adversarial networks. For each method, we outline the statistical foundation and summarize strengths and weaknesses, including their assumptions and conditions of use. We provide information on software availability and comment on the ease of use and the applicability of these methods to different types of data. We discuss validation and comparative reports, mention caveats and provide guidance on when to use each method, depending on context and specific research questions.

Accommodating site variation in neuroimaging data using normative and hierarchical Bayesian models.

The potential of normative modeling to make individualized predictions from neuroimaging data has enabled inferences that go beyond the case-control approach. However, site effects are often confounded with variables of interest in a complex manner and can bias estimates of normative models, which has impeded the application of normative models to large multi-site neuroimaging data sets. In this study, we suggest accommodating for these site effects by including them as random effects in a hierarchical Bayesian model. We compared the performance of a linear and a non-linear hierarchical Bayesian model in modeling the effect of age on cortical thickness. We used data of 570 healthy individuals from the ABIDE (autism brain imaging data exchange) data set in our experiments. In addition, we used data from individuals with autism to test whether our models are able to retain clinically useful information while removing site effects. We compared the proposed single stage hierarchical Bayesian method to several harmonization techniques commonly used to deal with additive and multiplicative site effects using a two stage regression, including regressing out site and harmonizing for site with ComBat, both with and without explicitly preserving variance caused by age and sex as biological variation of interest, and with a non-linear version of ComBat. In addition, we made predictions from raw data, in which site has not been accommodated for. The proposed hierarchical Bayesian method showed the best predictive performance according to multiple metrics. Beyond that, the resulting z-scores showed little to no residual site effects, yet still retained clinically useful information. In contrast, performance was particularly poor for the regression model and the ComBat model in which age and sex were not explicitly modeled. In all two stage harmonization models, predictions were poorly scaled, suffering from a loss of more than 90% of the original variance. Our results show the value of hierarchical Bayesian regression methods for accommodating site variation in neuroimaging data, which provides an alternative to harmonization techniques. While the approach we propose may have broad utility, our approach is particularly well suited to normative modeling where the primary interest is in accurate modeling of inter-subject variation and statistical quantification of deviations from a reference model.

Early outcomes of kidney transplant recipients from donors with severe SARS-CoV-2 pneumonia: A report of 5 cases.

BACKGROUND: Transplanting kidneys from donors with a recent history of severe SARS-CoV-2 pneumonia is uncommon due to concerns about the risk of viral transmission and the quality of kidneys from these donors. To date, there are no conclusive data on viral transmission from extrapulmonary solid organ transplants. Given the prevalence of SARS-CoV-2 infections in potential donors, shortage of kidneys available for transplantation, and low risk of viral transmission, we developed a clinical protocol for accepting kidneys from donors with recent severe SARS-CoV-2 pneumonia who demonstrate preserved kidney function. MATERIALS AND METHODS: We collected data on early outcomes of 5 kidney transplant recipients from 4 deceased donors hospitalized for severe SARS-CoV-2 infection. RESULTS: Donor creatinine ranged from 0.51 to 0.60 mg/dL and kidney donor profile index (KDPI) from 14 to 52%. Three of the five kidneys were from donation after circulatory death. All recipients were fully vaccinated, and 4/5 received post-exposure prophylactic monoclonal antibody treatment. While 3 recipients had delayed graft function, all had excellent graft function at 3 or 4 weeks post-operatively. None of the recipients displayed signs or symptoms of SARS-CoV-2 infection post-transplant. CONCLUSION: Our findings suggest that kidney grafts from donors with a recent history of severe SARS-CoV-2 infection but with preserved kidney function can be safely used and have good early outcomes.

Charting brain growth and aging at high spatial precision.

Defining reference models for population variation, and the ability to study individual deviations is essential for understanding inter-individual variability and its relation to the onset and progression of medical conditions. In this work, we assembled a reference cohort of neuroimaging data from 82 sites (N=58,836; ages 2-100) and used normative modeling to characterize lifespan trajectories of cortical thickness and subcortical volume. Models are validated against a manually quality checked subset (N=24,354) and we provide an interface for transferring to new data sources. We showcase the clinical value by applying the models to a transdiagnostic psychiatric sample (N=1985), showing they can be used to quantify variability underlying multiple disorders whilst also refining case-control inferences. These models will be augmented with additional samples and imaging modalities as they become available. This provides a common reference platform to bind results from different studies and ultimately paves the way for personalized clinical decision-making.

Robotic Donor Hysterectomy Results in Technical Success and Live Births After Uterus Transplantation: Subanalysis Within the Dallas Uterus Transplant Study (DUETS) Clinical Trial.

Minimally invasive procurement of uterine grafts for transplantation can decrease living donor recovery time. We examined recipient outcomes for grafts procured by robotic-assisted donor hysterectomies with transvaginal extraction in the Dallas UtErus Transplant Study (DUETS). All 5 grafts were successfully transplanted. Recipients had a median 4.5-hour surgical time, 0.25 L estimated blood loss, and 4-day hospital stay. Four recipients had grade III surgical complications and three had acute cellular rejection. At 18 months, graft viability was 100%, with an 80% live birth rate. This report demonstrates the feasibility and reproducible success of using uterus grafts from living donors who underwent robotic-assisted donor hysterectomy.

Utilization of a SARS-CoV-2-positive donor for liver transplantation.

Liver transplantation rates have been negatively affected by the pandemic caused by coronavirus disease 2019 (COVID-19), the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Current practice in the liver transplant community is to avoid utilizing SARS-CoV-2-positive donors for liver transplantation unless there is a compelling reason such as recipient illness severity. In this case, we report the use of a donor who had a positive exposure to and symptom history for COVID-19 and tested positive for SARS-CoV-2 on admission for a liver transplant recipient with primary sclerosing cholangitis and a Model of End-Stage Liver Disease score of 23 with no known COVID-19 exposures. We focus on the decision to accept this particular organ, as well as the discussion with the recipient about the unknowns of disease transmission and risk associated with this donor. The current case argues that transplant programs should begin to consider low-risk donors with positive SARS-CoV-2 testing for recipients who have the potential to benefit from liver transplantation, which may not only be those with the most severe illness.

Cost Analysis of Liver Acquisition Fees Before and After Acuity Circle Policy Implementation.

Importance: Acuity circles (AC) liver allocation policy was implemented to eliminate donor service area geographic boundaries from liver allocation and to decrease variability in median Model of End-stage Liver Disease (MELD) score at transplant and wait list mortality. However, the broader sharing of organs was also associated with more flights for organ procurements and higher costs associated with the increase in flights. Objective: To determine whether the costs associated with liver acquisition changed after the implementation of AC allocation. Design, Setting, and Participants: This single-center cost comparison study analyzed fees associated with organ acquisition before and after AC allocation implementation. The cost data were collected from a single transplant institute with 2 liver transplant centers, located 30 miles apart, in different donation service areas. Cost, recipient, and transportation data for all cases that included fees associated with liver acquisition from July 1, 2019, to October 31, 2020, were collected. Exposures: Primary liver offer acceptance with associated organ procurement organization or charter flight fees. Main Outcomes and Measures: Specific fees (organ acquisition, surgeon, import, and charter flight fees) and total fees per donor were collected for all accepted liver donors with at least 1 associated fee during the study period. Results: Of 213 included donors, 171 were used for transplant; 90 of 171 (52.6%) were male, and the median (interquartile range) age of donors was 41.0 (30.0-52.8) years in the pre-AC period and 36.9 (24.0-48.8) years in the post-AC period. There was no significant difference in the post-AC compared with pre-AC period in median (range) MELD score (24 [8-40] vs 25 [6-40]; P = .27) or median (range) match run sequence (15 [1-3951] vs 10 [1-1138]; P = .31), nor in mean (SD) distance traveled (155.83 [157.00] vs 140.54 [144.33] nautical miles; P = .32) or percentage of donors requiring flights (58.5% [69 of 118] vs 56.8% [54 of 95]; P = .82). However, costs increased significantly in the post-AC period: total cost increased 16% per accepted donor (mean [SD] of $52 966 [13 278] vs $45 725 [9300]; P < .001) and 55% per declined donor (mean [SD] of $15 865 [3942] vs $10 217 [4853]; P < .001). Contributing factors included more than 2-fold increases in the proportions of donors incurring import fees (31.4% [37 of 118] vs 12.6% [12 of 95]; P = .002) and surgeon fees (19.5% [23 of 118] vs 9.5% [9 of 95]; P = .05), increased acquisition fees (10% increase; mean [SD] of $43 860 [3266] vs $39 980 [2236]; P < .001), and increased flight expenses (43% increase; mean [SD] of $12 904 [6066] vs $9049 [5140]; P = .002). Conclusions and Relevance: The unintended consequences of implementing broader sharing without addressing organ acquisition fees to account for increased importation between organ procurement organizations must be remedied to contain costs and ensure viability of transplant programs.

Centering inclusivity in the design of online conferences-An OHBM-Open Science perspective.

As the global health crisis unfolded, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical, and legal barriers and effectively enabled many individuals from groups that have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.g., caregiving responsibilities. Yet, the mere existence of online conferences is no guarantee that everyone can attend and participate meaningfully. In fact, many elements of an online conference are still significant barriers to truly diverse participation: the tools used can be inaccessible for some individuals; the scheduling choices can favour some geographical locations; the set-up of the conference can provide more visibility to well-established researchers and reduce opportunities for early-career researchers. While acknowledging the benefits of an online setting, especially for individuals who have traditionally been underrepresented or excluded, we recognize that fostering social justice requires inclusivity to actively be centered in every aspect of online conference design. Here, we draw from the literature and from our own experiences to identify practices that purposefully encourage a diverse community to attend, participate in, and lead online conferences. Reflecting on how to design more inclusive online events is especially important as multiple scientific organizations have announced that they will continue offering an online version of their event when in-person conferences can resume.

Brainhack: Developing a culture of open, inclusive, community-driven neuroscience.

Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open, inclusive environment. This NeuroView describes the myriad benefits for participants and the research community and how Brainhacks complement conventional formats to augment scientific progress.

Selective screening imaging of the aortoiliac arterial system in kidney transplant candidates with non-contrast pelvic computed tomography.

Non-contrast pelvic computed tomography (CT) can detect severe iliac artery calcifications that present technical contraindications to kidney transplantation (TCT). We screened 454 asymptomatic patients with a history of any of the following: hemodialysis >10 years, diabetes mellitus >20 years, coronary artery disease (CAD) with percutaneous or surgical interventions, carotid disease, diabetes with below-/above-knee amputations, and heart-kidney transplantation candidacy. Patients with normal dorsalis pedis and/or tibialis posterior pulses were not screened. A total of 8.4% had severe calcifications with TCT; CT determined laterality for implantation in 13.9%. No patients with the following characteristics were classified as TCT: age <40 years, hemodialysis >10 years, carotid arterial disease, prior lower extremity amputation, or heart-kidney transplantation candidacy. CAD was associated with TCT in univariate though not multivariate analysis. Limiting screening to patients >40 years, with DM >20 years, or with CAD, 9.8% had a TCT and CT determined transplant laterality in 14.2%. Screening for severe iliac artery calcifications is useful for selected kidney transplantation candidates over age 40. It can assist with laterality choice or surgeon determination of TCT. Cost and radiation exposure risks should be weighed against the morbidity risks from unnecessary surgery.

Twelve Live Births After Uterus Transplantation in the Dallas UtErus Transplant Study.

OBJECTIVE: To describe aggregated pregnancy outcomes after uterus transplantation from a single, experienced center. METHODS: This prospective study reports on live births among 20 women who received a uterus transplant from 2016 to 2019 at Baylor University Medical Center at Dallas. These live births occurred between November 2017 and September 2020. The main measures were live birth, maternal complications, and fetal and newborn outcomes. RESULTS: There were six graft failures (four surgical complications and two with poor perfusion postoperatively). Of the 14 technically successful transplants, at least one live birth occurred in 11 patients. Thus far, the live birth rate per attempted transplant is 55%, and the live-birth rate per technically successful transplant is 79%. Ten uteri were from nondirected living donors and one uterus was from a deceased donor. In vitro fertilization was performed to achieve pregnancy. Ten recipients delivered one neonate, and one recipient delivered two neonates. One organ rejection episode was detected during pregnancy and was resolved with steroids. The median birth weight was 2,890 g (range 1,770-3,140 g [median 68th percentile]). Maternal weight gain was higher than Institute of Medicine recommendations. Maternal medical complications were observed in five recipients (elevated creatinine level, gestational diabetes, gestational hypertension [n=2], and preeclampsia). In five recipients, maternal medical or obstetric complications led to an unplanned preterm delivery (elevated creatinine level, preeclampsia; preterm labor [n=3]). The median gestational age at delivery was 36 6/7 weeks (range 30 6/7-38 weeks). All neonates were liveborn, with Apgar scores of 8 or higher at 5 minutes. CONCLUSION: Over the first 3 years, our program experienced a live-birth rate per attempted transplant of 55% and a live-birth rate per technically successful transplant of 79%. In our experience, uterus transplantation resulted in a third-trimester live birth in all cases in which pregnancies reached 20 weeks of gestation. Maternal medical and obstetric complications can occur; however, these were manageable by applying principles of generally accepted obstetric practice. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, NCT02656550.

Dallas UtErus Transplant Study: Early Outcomes and Complications of Robot-assisted Hysterectomy for Living Uterus Donors.

BACKGROUND: Uterus transplantation is a treatment for absolute uterine infertility and can be performed with living and deceased donors. Given the safety and increased utilization of robotic assistance with other gynecologic and transplant donor operations, we adopted a robot-assisted approach to donor hysterectomy. This study compared early outcomes and morbidity of the robot-assisted approach to donor hysterectomy with the traditionally performed open approach and addressed whether the robot-assisted approach is safe and offers advantages for the donor. METHODS: Our institution has performed 18 living donor hysterectomies for uterus transplantation. This retrospective review compared the last 5 cases utilizing a robot-assisted technique and vaginal extraction of the uterus graft with the first 13 cases performed with an open laparotomy technique. Demographic, intraoperative, and postoperative data were examined. RESULTS: There were no differences between the robot-assisted and the open living donor group with respect to age, body mass index, or gynecological history. Although the median operative time was shorter for the open approach (6.27 versus 10.46 h), the donors' median estimated blood loss, length of hospital stay, and length of sick leave were less with the robot-assisted approach. There was no conversion to open hysterectomy in the robot-assisted cases, and the incidence of complications was similar between the 2 groups. There was no difference in early graft function. CONCLUSIONS: These preliminary results show that robot-assisted living donor hysterectomy is feasible and safe for the donors; it allows a faster postoperative recovery and the same early graft function.

Prospective Multicenter Study of Early Antiviral Therapy in Liver and Kidney Transplant Recipients of HCV-Viremic Donors.

BACKGROUND AND AIMS: Organs from hepatitis C virus (HCV)-viremic donors have been used in HCV-uninfected recipients (D+/R-), but the optimal treatment approach has not been defined. We evaluated the kinetics of HCV infection following transplant in D+/R- kidney-transplant (KT) and liver-transplant (LT) recipients when a preemptive antiviral strategy was used. APPROACH AND RESULTS: Six US transplant programs prospectively treated D+/R- primary LT and KT recipients with sofosbuvir-velpastasvir for 12 weeks starting once viremia was confirmed following transplant and the patients were judged to be clinically stable, including estimated glomerular filtration rate >30 mL/min. Primary endpoints were sustained virologic response at 12 weeks following transplant and safety (assessed by proportion of treatment-related adverse and serious adverse events). Of the 24 patients transplanted (13 liver, of whom 2 had prior-treated HCV infection; 11 kidney), 23 became viremic after transplant. The median (interquartile range) time from transplant to start of antiviral therapy was 7.0 (6.0, 12.0) versus 16.5 (9.8, 24.5) days, and the median (interquartile range) HCV-RNA level 3 days after transplant was 6.5 (3.9, 7.1) versus 3.6 (2.9, 4.0) log10  IU/mL in LT versus KT recipients, respectively. By week 4 of treatment, 10 of 13 (77%) LT, but only 2 of 10 (20%) KT, had undetectable HCV RNA (P = 0.01). At the end of treatment, all LT recipients were HCV RNA-undetectable, whereas 3 (30%) of the kidney recipients still had detectable, but not quantifiable, viremia. All achieved sustained virologic response at 12 weeks following transplant (lower 95% confidence interval bound: 85%). Serious adverse events considered possibly related to treatment were antibody-mediated rejection, biliary sclerosis, cardiomyopathy, and graft-versus-host disease, with the latter associated with multiorgan failure, premature treatment discontinuation, and death. CONCLUSIONS: Despite differing kinetics of early HCV infection in liver versus non-liver recipients, a preemptive antiviral strategy is effective. Vigilance for adverse immunologic events is warranted.