Mastering the technical skills required to perform pediatric cardiac valve surgery is challenging in part due to limited opportunity for practice. Transformation of 3D echocardiographic (echo) images of congenitally abnormal heart valves to realistic physical models could allow patient-specific simulation of surgical valve repair. We compared materials, processes, and costs for 3D printing and molding of patient-specific models for visualization and surgical simulation of congenitally abnormal heart valves. Pediatric atrioventricular valves (mitral, tricuspid, and common atrioventricular valve) were modeled from transthoracic 3D echo images using semi-automated methods implemented as custom modules in 3D Slicer. Valve models were then both 3D printed in soft materials and molded in silicone using 3D printed "negative" molds. Using pre-defined assessment criteria, valve models were evaluated by congenital cardiac surgeons to determine suitability for simulation. Surgeon assessment indicated that the molded valves had superior material properties for the purposes of simulation compared to directly printed valves (p < 0.01). Patient-specific, 3D echo-derived molded valves are a step toward realistic simulation of complex valve repairs but require more time and labor to create than directly printed models. Patient-specific simulation of valve repair in children using such models may be useful for surgical training and simulation of complex congenital cases.
ImportanceMeropenem is a widely prescribed β-lactam antibiotic. Meropenem exhibits maximum pharmacodynamic efficacy when given by continuous infusion to deliver constant drug levels above the minimal inhibitory concentration. Compared with intermittent administration, continuous administration of meropenem may improve clinical outcomes.ObjectiveTo determine whether continuous administration of meropenem reduces a composite of mortality and emergence of pandrug-resistant or extensively drug-resistant bacteria compared with intermittent administration in critically ill patients with sepsis.Design, Setting, and ParticipantsA double-blind, randomized clinical trial enrolling critically ill patients with sepsis or septic shock who had been prescribed meropenem by their treating clinicians at 31 intensive care units of 26 hospitals in 4 countries (Croatia, Italy, Kazakhstan, and Russia). Patients were enrolled between June 5, 2018, and August 9, 2022, and the final 90-day follow-up was completed in November 2022.InterventionsPatients were randomized to receive an equal dose of the antibiotic meropenem by either continuous administration (n = 303) or intermittent administration (n = 304).Main Outcomes and MeasuresThe primary outcome was a composite of all-cause mortality and emergence of pandrug-resistant or extensively drug-resistant bacteria at day 28. There were 4 secondary outcomes, including days alive and free from antibiotics at day 28, days alive and free from the intensive care unit at day 28, and all-cause mortality at day 90. Seizures, allergic reactions, and mortality were recorded as adverse events.ResultsAll 607 patients (mean age, 64 [SD, 15] years; 203 were women [33%]) were included in the measurement of the 28-day primary outcome and completed the 90-day mortality follow-up. The majority (369 patients, 61%) had septic shock. The median time from hospital admission to randomization was 9 days (IQR, 3-17 days) and the median duration of meropenem therapy was 11 days (IQR, 6-17 days). Only 1 crossover event was recorded. The primary outcome occurred in 142 patients (47%) in the continuous administration group and in 149 patients (49%) in the intermittent administration group (relative risk, 0.96 [95% CI, 0.81-1.13], P = .60). Of the 4 secondary outcomes, none was statistically significant. No adverse events of seizures or allergic reactions related to the study drug were reported. At 90 days, mortality was 42% both in the continuous administration group (127 of 303 patients) and in the intermittent administration group (127 of 304 patients).Conclusions and RelevanceIn critically ill patients with sepsis, compared with intermittent administration, the continuous administration of meropenem did not improve the composite outcome of mortality and emergence of pandrug-resistant or extensively drug-resistant bacteria at day 28.Trial RegistrationClinicalTrials.gov Identifier: NCT03452839
Background Pulmonary insufficiency is a consequence of transannular patch repair in Tetralogy of Fallot (ToF) leading to late morbidity and mortality. Transcatheter native outflow tract pulmonary valve replacement has become a reality. However, predicting a secure, atraumatic implantation of a catheter‐based device remains a significant challenge due to the complex and dynamic nature of the right ventricular outflow tract (RVOT). We sought to quantify the differences in compression and volume for actual implants, and those predicted by pre‐implant modeling. Methods We used custom software to interactively place virtual transcatheter pulmonary valves (TPVs) into RVOT models created from pre‐implant and post Harmony valve implant CT scans of 5 ovine surgical models of TOF to quantify and visualize device volume and compression. Results Virtual device placement visually mimicked actual device placement and allowed for quantification of device volume and radius. On average, simulated proximal and distal device volumes and compression did not vary statistically throughout the cardiac cycle (P = 0.11) but assessment was limited by small sample size. In comparison to actual implants, there was no significant pairwise difference in the proximal third of the device (P > 0.80), but the simulated distal device volume was significantly underestimated relative to actual device implant volume (P = 0.06). Conclusions This study demonstrates that pre‐implant modeling which assumes a rigid vessel wall may not accurately predict the degree of distal RVOT expansion following actual device placement. We suggest the potential for virtual modeling of TPVR to be a useful adjunct to procedural planning, but further development is needed.
The estimation of effective population sizes (Ne) through time is of fundamental interest in population genetics, but the interpretation of Ne as the effective number of breeding individuals in the population is challenged by the effect of population structure. In fact, variation in Ne reported in many studies may be a consequence of changes in migration rates between populations rather than changes in actual population size. We address this long-standing problem here by constructing joint models of population size changes, migration, and divergence that can adjust temporal estimates of Ne and estimate the actual Ne of a local deme connected to another population through migration. We also develop a method for estimating divergence times and migration rates taking into account complex scenarios of changing population sizes. We apply the method to previously published data from humans, and show that, when taking migration and changes in Ne into account, the estimated divergence between the San and Dinka populations is approximately 108 kya, and not 255 kya as reported in a previous study. Using simulations, we demonstrate that the previously reported and surprisingly old estimates of divergence between San and Dinka is in fact caused by a quantifiable estimation bias due to changes in Ne through time.
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