The factors associated with high-quality communication for critically ill children

OBJECTIVE: Timely, high quality communication with families is essential to family-centered decision-making. Quality communication is represented by widespread documentation of prognostic, goals-of-care conversations (PGOCC) in the pediatric intensive care unit (PICU) and should occur without variation by patient characteristics. METHODS: Cohort included 645 PICU admissions in the top decile of risk of mortality on admission over six years. Electronic medical records were used to determine PGOCC, diagnosis on admission and complex chronic condition (CCC) status. Multivariate logistic regression and time-to-event analyses were used. RESULTS: Overall, 31% had a documented PGOCC. 51% had CCC status. 11% had an oncologic, 13% had a cardiovascular diagnosis on admission. 94% of patients who died in the PICU had PGOCC documented, but among the 200 patients with documented PGOCC, 78% did not die in the PICU. Oncologic diagnosis on admission was associated with a higher likelihood of PGOCC compared to non-CCC patients (ARR=1.86; SE=0.26) whereas no other diagnosis category reached the level of statistical significance. Median time from admission to PGOCC was 2 days. Age, gender and CCC status were not associated with whether a PGOCC was documented or with time from admission to PGOCC documentation. 45% of PGOCC in the cohort and 50% of conversations in patients with CCC were documented by PICU physicians. CONCLUSIONS: This study reveals the opportunity for improvement in documentation of PGOCC for critically ill children. It raises the questions of why there is variation of PGOCC across disease categories and whether PGOCC should be considered a quality measure for family-centered care

Contrast-Detail Analysis Characterizing Diffuse Optical Fluorescence Tomography Image Reconstruction

Contrast-detail analysis is used to evaluate the imaging performance of diffuse optical fluorescence tomography (DOFT), characterizing spatial resolution limits, signal-to-noise limits, and the trade-off between object contrast and size. Reconstructed images of fluorescence yield from simulated noisy data were used to determine the contrast-to-noise ratio (CNR). A threshold of CNR=3 was used to approximate a lowest acceptable noise level in the image, as a surrogate measure for human detection of objects. For objects 0.5 cm inside the edge of a simulated tissue region, the smallest diameter that met this criteria was approximately 1.7 mm, regardless of contrast level, and test field diameter had little impact on this limit. Object depth had substantial impact on object CNR, leading to a limit of 4 mm for objects near the center of a 51-mm test field and 8.5 mm for an 86-mm test field. Similarly, large objects near the edge of both test fields required a minimum contrast of 50% to achieve acceptable image CNR. The minimum contrast for large, centered objects ranged between 50% and 100%. Contrast-detail analysis using human detection of lower contrast limits provides fundamentally important information about the performance of reconstruction algorithms, and can be used to compare imaging performance of different systems

DRUG-NEM: Optimizing drug combinations using single-cell perturbation response to account for intratumoral heterogeneity.

An individual malignant tumor is composed of a heterogeneous collection of single cells with distinct molecular and phenotypic features, a phenomenon termed intratumoral heterogeneity. Intratumoral heterogeneity poses challenges for cancer treatment, motivating the need for combination therapies. Single-cell technologies are now available to guide effective drug combinations by accounting for intratumoral heterogeneity through the analysis of the signaling perturbations of an individual tumor sample screened by a drug panel. In particular, Mass Cytometry Time-of-Flight (CyTOF) is a high-throughput single-cell technology that enables the simultaneous measurements of multiple ([Formula: see text]40) intracellular and surface markers at the level of single cells for hundreds of thousands of cells in a sample. We developed a computational framework, entitled Drug Nested Effects Models (DRUG-NEM), to analyze CyTOF single-drug perturbation data for the purpose of individualizing drug combinations. DRUG-NEM optimizes drug combinations by choosing the minimum number of drugs that produce the maximal desired intracellular effects based on nested effects modeling. We demonstrate the performance of DRUG-NEM using single-cell drug perturbation data from tumor cell lines and primary leukemia samples

Electromagnetic wave scattering experiments in Hall thruster plasma plumes

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76740/1/AIAA-1998-3642-699.pd

Fluorescence Tomography Characterization for Sub-Surface Imaging with Protoporphyrin IX

Optical imaging of fluorescent objects embedded in a tissue simulating medium was characterized using non-contact based approaches to fluorescence remittance imaging (FRI) and sub-surface fluorescence diffuse optical tomography (FDOT). Using Protoporphyrin IX as a fluorescent agent, experiments were performed on tissue phantoms comprised of typical in-vivo tumor to normal tissue contrast ratios, ranging from 3.5:1 up to 10:1. It was found that tomographic imaging was able to recover interior inclusions with high contrast relative to the background; however, simple planar fluorescence imaging provided a superior contrast to noise ratio. Overall, FRI performed optimally when the object was located on or close to the surface and, perhaps most importantly, FDOT was able to recover specific depth information about the location of embedded regions. The results indicate that an optimal system for localizing embedded fluorescent regions should combine fluorescence reflectance imaging for high sensitivity and sub-surface tomography for depth detection, thereby allowing more accurate localization in all three directions within the tissue