Characteristics and Outcomes of Patients Directly Discharged to Home from the Intensive Care Unit

Introduction: Given the current era of decreasing hospital bed availability, there has been a rise in the practice of direct discharge to home (DDH) from ICUs. We evaluated the demographics, clinical characteristics, outcomes and readmission patterns among DDH patients. Methods: Retrospective review of patients from 2 MICUs from June 2017 to June 2019 at Thomas Jefferson University hospital, an urban tertiary care center. Primary outcome of interest was 30-day hospital readmission. Patients were dichotomized into two groups based on time between ward transfer order and hospital discharge (\u3c24 or ≥24 hours). Risk adjustment performed with Mortality Probability Model (MPM0 -III). ICU workload at admission and discharge was estimated with nine equivalents of nursing manpower use score (NEMS). Patient characteristics compared using t-test and Fisher exact or χ2 test. Results: 331 DDH patients were analyzed, with the majority (68.3%, 226/331) waiting \u3c24 hours for discharge. Mean LOS significantly longer in patients who had waited ≥24 hours prior to discharge compared to that of patients who waited \u3c24 hours (4.63 vs 2.65 days, p\u3c0.001). 10.3% (45/331) presented to TJU for evaluation within 30 days of discharge. Of these patients, 75.6% (34/45) were readmitted. No significant difference in severity-of-illness, admission NEMS, or 30-day readmission between the 2 groups (p=0.70). Discussion: Shorter wait-times for ICU patients after being determined ready for DDH were associated with shorter hospital and ICU LOS but not with an increase in 30-day readmissions. Further examining pre-discharge and post-discharge data could better identify those at risk of readmission

Assessment of rotator cuff repair integrity using ultrasound and magnetic resonance imaging in a multicenter study

Background: This study compared ultrasound and magnetic resonance imaging (MRI) evaluation of the repaired rotator cuff to determine concordance between these imaging studies. Methods: We performed a concordance study using the data from a prospective nonrandomized multicenter study at 13 centers. A suture bridge technique was used to repair 113 rotator cuff tears that were between 1 and 4 cm wide. Repairs were evaluated with MRI and ultrasound at multiple time points after surgery. The MRI scans were read by a central radiologist and the surgeon, and the ultrasounds were read by a local radiologist or the surgeon who performed the ultrasound. Results: The concordance between the central radiologist's MRI reading and the investigator's MRI readings at all time points was 89%, with a k coefficient of 0.60. The concordance between the central radiologist's MRI and ultrasound readings at all time points was 85%, with a k coefficient of 0.40. The concordance between the investigator's MRI and ultrasound readings was 92%, with a k coefficient of 0.70. Conclusions: In the community setting, ultrasound may be used to evaluate the integrity of a repaired rotator cuff tendon and constitutes a comparable alternative to MRI when evaluating the integrity of a rotator cuff repair. Clinical investigators should compare their postoperative ultrasound results with their postoperative MRI results for a certain time period to establish the accuracy of ultrasound before relying solely on ultrasound imaging to evaluate the integrity of their rotator cuff repairs. Level of evidence: Level III, Diagnostic Study

Characteristics and Outcomes of Patients Discharged Directly Home from a Medical Intensive Care Unit

RATIONALE: Discharging patients directly from ICUs is an increasingly common practice, largely due to decreased availability of ward beds. The purpose of this study was to describe the population and evaluate the outcomes of patients discharged directly from the MICU. METHODS: We conducted a retrospective chart review of direct discharges to home from June 2018 to June 2019 from two MICUs. Patients were separated into two groups based on wait time (\u3c24 hours or ≥ 24 hours) between ward transfer order and actual discharge. The primary outcome was 30-day hospital readmission. Risk was adjusted using Mortality Probability Model (MPM-III); ICU workload at admission and discharge was estimated using the nine equivalents of nursing manpower use score (NEMS). Patient characteristics were compared using t-test and Fisher exact or X2. RESULTS: There was no difference in severity-of-illness or admission NEMS between the two groups. Patients who waited \u3c24 hours for discharge were more likely to be admitted from home. Patients who waited ≥24 hours prior to discharge had significantly longer mean hospital LOS compared to those who waited \u3c24 hours (4.63 days vs. 2.65 days, p\u3c0.001). There was no significant difference in 30-day readmission between patients who were discharged after waiting \u3c24 hours vs. waiting ≥24 hours (p=0.70). CONCLUSION: Patients who returned directly home from the MICU without any discharge delay were not readmitted to the hospital more frequently within 30 days than those discharged to home after a delay exceeding 24 hours. Further investigation into identifying those patients for whom early discharge planning directly to home from the ICU is viable and safe may aid in reducing unnecessary critical care resource utilization

Simple, Fast and Accurate Implementation of the Diffusion Approximation Algorithm for Stochastic Ion Channels with Multiple States

The phenomena that emerge from the interaction of the stochastic opening and closing of ion channels (channel noise) with the non-linear neural dynamics are essential to our understanding of the operation of the nervous system. The effects that channel noise can have on neural dynamics are generally studied using numerical simulations of stochastic models. Algorithms based on discrete Markov Chains (MC) seem to be the most reliable and trustworthy, but even optimized algorithms come with a non-negligible computational cost. Diffusion Approximation (DA) methods use Stochastic Differential Equations (SDE) to approximate the behavior of a number of MCs, considerably speeding up simulation times. However, model comparisons have suggested that DA methods did not lead to the same results as in MC modeling in terms of channel noise statistics and effects on excitability. Recently, it was shown that the difference arose because MCs were modeled with coupled activation subunits, while the DA was modeled using uncoupled activation subunits. Implementations of DA with coupled subunits, in the context of a specific kinetic scheme, yielded similar results to MC. However, it remained unclear how to generalize these implementations to different kinetic schemes, or whether they were faster than MC algorithms. Additionally, a steady state approximation was used for the stochastic terms, which, as we show here, can introduce significant inaccuracies. We derived the SDE explicitly for any given ion channel kinetic scheme. The resulting generic equations were surprisingly simple and interpretable - allowing an easy and efficient DA implementation. The algorithm was tested in a voltage clamp simulation and in two different current clamp simulations, yielding the same results as MC modeling. Also, the simulation efficiency of this DA method demonstrated considerable superiority over MC methods.Comment: 32 text pages, 10 figures, 1 supplementary text + figur

Optically levitated nanoparticle as a model system for stochastic bistable dynamics

Nano-mechanical resonators have gained an increasing importance in nanotechnology owing to their contributions to both fundamental and applied science. Yet, their small dimensions and mass raises some challenges as their dynamics gets dominated by nonlinearities that degrade their performance, for instance in sensing applications. Here, we report on the precise control of the nonlinear and stochastic bistable dynamics of a levitated nanoparticle in high vacuum. We demonstrate how it can lead to efficient signal amplification schemes, including stochastic resonance. This work contributes to showing the use of levitated nanoparticles as a model system for stochastic bistable dynamics, with applications to a wide variety of fields.inancial support from the ERC- QnanoMECA (Grant No. 64790), the Spanish Ministry of Economy and Competitiveness, under grant FIS2016-80293-R and through the ‘Severo Ochoa’ Programme for Centres of Excellence in R&D (SEV-2015-0522), Fundació Privada CELLEX and from the CERCA Programme/Generalitat de Catalunya. J.G. has been supported by H2020-MSCA-IF-2014 under REA grant Agreement No. 655369. L.R. acknowledges support from an ETH Marie Curie Cofund Fellowship

A Fokker-Planck formalism for diffusion with finite increments and absorbing boundaries

Gaussian white noise is frequently used to model fluctuations in physical systems. In Fokker-Planck theory, this leads to a vanishing probability density near the absorbing boundary of threshold models. Here we derive the boundary condition for the stationary density of a first-order stochastic differential equation for additive finite-grained Poisson noise and show that the response properties of threshold units are qualitatively altered. Applied to the integrate-and-fire neuron model, the response turns out to be instantaneous rather than exhibiting low-pass characteristics, highly non-linear, and asymmetric for excitation and inhibition. The novel mechanism is exhibited on the network level and is a generic property of pulse-coupled systems of threshold units.Comment: Consists of two parts: main article (3 figures) plus supplementary text (3 extra figures

The emergence of waves in random discrete systems

Essential criteria for the emergence of wave-like manifestations occurring in an entirely discrete system are identified using a simple model for the movement of particles through a network. The dynamics are entirely stochastic and memoryless involving a birth-death-migration process. The requirements are that the network should have at least three nodes, that migration should have a directional bias, and that the particle dynamics have a non-local dependence. Well defined bifurcations mark transitions between amorphous, wave-like and collapsed states with an intermittent regime between the latter two

What Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology

Stochastic resonance is said to be observed when increases in levels of unpredictable fluctuations—e.g., random noise—cause an increase in a metric of the quality of signal transmission or detection performance, rather than a decrease. This counterintuitive effect relies on system nonlinearities and on some parameter ranges being “suboptimal”. Stochastic resonance has been observed, quantified, and described in a plethora of physical and biological systems, including neurons. Being a topic of widespread multidisciplinary interest, the definition of stochastic resonance has evolved significantly over the last decade or so, leading to a number of debates, misunderstandings, and controversies. Perhaps the most important debate is whether the brain has evolved to utilize random noise in vivo, as part of the “neural code”. Surprisingly, this debate has been for the most part ignored by neuroscientists, despite much indirect evidence of a positive role for noise in the brain. We explore some of the reasons for this and argue why it would be more surprising if the brain did not exploit randomness provided by noise—via stochastic resonance or otherwise—than if it did. We also challenge neuroscientists and biologists, both computational and experimental, to embrace a very broad definition of stochastic resonance in terms of signal-processing “noise benefits”, and to devise experiments aimed at verifying that random variability can play a functional role in the brain, nervous system, or other areas of biology

Structural basis for selective inhibition of immunoglobulin E-receptor interactions by an anti-IgE antibody

Immunoglobulin E (IgE) antibodies play a central role in the allergic response: interaction with FcεRI on mast cells and basophils leads to immediate hypersensitivity reactions upon allergen challenge, while interaction with CD23/FcεRII, expressed on a variety of cells, regulates IgE synthesis among other activities. The receptor-binding IgE-Fc region has recently been found to display remarkable flexibility, from acutely bent to extended conformations, with allosteric communication between the distant FcεRI and CD23 binding sites. We report the structure of an anti-IgE antibody Fab (8D6) bound to IgE-Fc through a mixed protein-carbohydrate epitope, revealing further flexibility and a novel extended conformation with potential relevance to that of membrane-bound IgE in the B cell receptor for antigen. Unlike the earlier, clinically approved anti-IgE antibody omalizumab, 8D6 inhibits binding to FcεRI but not CD23; the structure reveals how this discrimination is achieved through both orthosteric and allosteric mechanisms, supporting therapeutic strategies that retain the benefits of CD23 binding