Bridging the Acute-to-Outpatient Care Gap in Mental Health: Developing and Implementing a Mental Health Transition Process.

BACKGROUND: A national Department of Veterans Affairs (VA) mental health (MH) quality metric tracks engagement in outpatient MH care after discharge from residential and inpatient settings, with recommendations for 2 or more visits 30 days postdischarge. LOCAL PROBLEM: A gap in transitioning patients from residential to outpatient MH care was identified at this site. METHODS: A transition management process was developed and piloted, including a new MH Discharge Consult and an RN Transition Care Managers team. INTERVENTIONS: Transition Care Managers triaged Discharge Consults, communicated with schedulers and patients pre- and postdischarge, and tracked MH engagement for 30 days postdischarge. Process, outcome, and balancing measures were developed and iteratively adjusted using Plan-Do-Study-Act (PDSA) cycles. RESULTS: Over 55 weeks, 443 Discharge Consults were placed. There was an average 89% success rate in connecting patients with 2 or more MH visits versus 53% preintervention. CONCLUSIONS: This pilot showed promising results in improving postdischarge MH engagement with the use of PDSA cycles to collect data and refine processes.

Amyloidosis and spontaneous hepatic bleeding, transcatheter therapy for hepatic parenchymal bleeding with massive intraperitoneal hemorrhage: a case report and review of the literature.

Hepatic hemorrhage can be devastating, especially in patients with underlying hepatic pathology. This is a case report of a 50-year-old man who presented to the emergency room with Stage 3 shock as evidenced by a systolic blood pressure of 90 mmHg, a heart rate of 125 beats per minute, respiration of 32, with delayed capillary refill and agitation. At this time, he was found to have a massive spontaneous intra-abdominal hemorrhage with an advanced stage of amyloidosis with multiple organ malfunctions. The initial diagnosis was based on an abdominal computed tomography scan and the patient was taken expeditiously to a hybrid angiography suite for a celiac angiogram. An intraoperative diagnosis of extravasation from amyloid related vasculopathy was made based on the angiographic appearance of hepatic circulation. Coil embolization of the feeding branch of the bleeder was achieved using the interlock coil system and a completion angiogram was done showing complete cessation of active bleeding. The postoperative phase was uneventful and the patient was discharged home on postoperative day three. His postoperative visit at five months later was unremarkable.

Quantifying Systematic RBE-Weighted Dose Uncertainty Arising from Multiple Variable RBE Models in Organ at Risk.

PURPOSE: Relative biological effectiveness (RBE) uncertainties have been a concern for treatment planning in proton therapy, particularly for treatment sites that are near organs at risk (OARs). In such a clinical situation, the utilization of variable RBE models is preferred over constant RBE model of 1.1. The problem, however, lies in the exact choice of RBE model, especially when current RBE models are plagued with a host of uncertainties. This paper aims to determine the influence of RBE models on treatment planning, specifically to improve the understanding of the influence of the RBE models with regard to the passing and failing of treatment plans. This can be achieved by studying the RBE-weighted dose uncertainties across RBE models for OARs in cases where the target volume overlaps the OARs. Multi-field optimization (MFO) and single-field optimization (SFO) plans were compared in order to recommend which technique was more effective in eliminating the variations between RBE models. METHODS: Fifteen brain tumor patients were selected based on their profile where their target volume overlaps with both the brain stem and the optic chiasm. In this study, 6 RBE models were analyzed to determine the RBE-weighted dose uncertainties. Both MFO and SFO planning techniques were adopted for the treatment planning of each patient. RBE-weighted dose uncertainties in the OARs are calculated assuming ( α ß ) x of 3 Gy and 8 Gy. Statistical analysis was used to ascertain the differences in RBE-weighted dose uncertainties between MFO and SFO planning. Additionally, further investigation of the linear energy transfer (LET) distribution was conducted to determine the relationship between LET distribution and RBE-weighted dose uncertainties. RESULTS: The results showed no strong indication on which planning technique would be the best for achieving treatment planning constraints. MFO and SFO showed significant differences (P <.05) in the RBE-weighted dose uncertainties in the OAR. In both clinical target volume (CTV)-brain stem and CTV-chiasm overlap region, 10 of 15 patients showed a lower median RBE-weighted dose uncertainty in MFO planning compared with SFO planning. In the LET analysis, 8 patients (optic chiasm) and 13 patients (brain stem) showed a lower mean LET in MFO planning compared with SFO planning. It was also observed that lesser RBE-weighted dose uncertainties were present with MFO planning compared with SFO planning technique. CONCLUSIONS: Calculations of the RBE-weighted dose uncertainties based on 6 RBE models and 2 different ( α ß ) x revealed that MFO planning is a better option as opposed to SFO planning for cases of overlapping brain tumor with OARs in eliminating RBE-weighted dose uncertainties. Incorporation of RBE models failed to dictate the passing or failing of a treatment plan. To eliminate RBE-weighted dose uncertainties in OARs, the MFO planning technique is recommended for brain tumor when CTV and OARs overlap.

Incomplete reprogramming after fusion of human multipotent stromal cells and bronchial epithelial cells.

Bone marrow-derived progenitor cells can fuse with cells of several different tissues, including lung, especially following injury. Despite many reports of cell fusion, few studies have examined the function of the resulting hybrid cells. We cocultured human multipotent stromal cells (hMSCs) and normal human bronchial epithelial cells (NHBEs) and observed the formation of hMSC/NHBE heterokaryons. The heterokaryons expressed several proteins characteristic of epithelial cells, such as keratin and occludin. Hybrid cells also expressed the mRNAs and proteins for 2 important ion channels that maintain bronchial and alveolar fluid balance: the cystic fibrosis transmembrane conductance regulator (CFTR) and the amiloride-sensitive epithelial Na(+) channel (ENaC). By immunocytochemistry, CFTR was expressed in many hybrid cells but was absent or low in others. Whole-cell patch-clamp recordings demonstrated a glibenclamide-sensitive current in the presence of barium chloride, consistent with functional CFTR channels, in control NHBEs and hMSC/NHBE heterokaryons. Total cell capacitance measurements showed that the membrane surface area of heterokaryons was similar to that of NHBEs. Heterokaryons expressed the α- and γ-ENaC subunits but did not express the ß-ENaC subunit, indicating the inability to form a complete ENaC channel. In addition, hybrid cells formed by the fusion of hMSCs with immortalized bronchial cells that expressed CFTR ΔF508 did not lead to reprogramming of the hMSC nucleus and expression of wild-type CFTR mRNA. Our data show that reprogramming can be incomplete following fusion of adult progenitor cells and somatic cells and may lead to altered cell function.

Idiopathic hemodynamically unstable polymicrobial purulent pericarditis: a rare case presentation.

Purulent pericarditis is an extremely rare disease accounting for <1% of pericarditis cases. Purulent pericarditis with hemodyamically unstable tamponade if untreated is fatal. Furthermore, although idiopathic polymicrobial disease is documented, a combination Haemophilus parainfluenzae, Prevotella buccae, and Citrobacter freundii have not been found in the literature by the authors. What follows is a case of a 58-year-old male who presented to the emergency department (ED) with these features and underwent emergent bedside pericardiocentesis and a brief review of current pericardiocentesis techniques in the emergency department.

Standardizing Monte Carlo simulation parameters for a reproducible dose-averaged linear energy transfer.

OBJECTIVE: Dose-averaged linear energy transfer (LETD) is one of the factors which determines relative biological effectiveness (RBE) for treatment planning in proton therapy. It is usually determined from Monte Carlo (MC) simulation. However, no standard simulation protocols were established for sampling of LETD. Simulation parameters like maximum step length and range cut will affect secondary electrons production and have an impact on the accuracy of dose distribution and LETD. We aim to show how different combinations of step length and range cut in GEANT4 will affect the result in sampling of LETD using different MC scoring methods. METHODS: In this work, different step length and range cut value in a clinically relevant voxel geometry were used for comparison. Different LETD scoring methods were established and the concept of covariance between energy deposition per step and step length is used to explain the differences between them. RESULTS: We recommend a maximum step length of 0.05 mm and a range cut of 0.01 mm in MC simulation as this yields the most consistent LETD value across different scoring methods. Different LETD scoring methods are also compared and variation up to 200% can be observed at the plateau of 80 MeV proton beam. Scoring Method one has one of the lowest percentage differences compared across all simulation parameters. CONCLUSION: We have determined a set of maximum step length and range cut parameters to be used for LETD scoring in a 1 mm voxelized geometry. LETD scoring method should also be clearly defined and standardized to facilitate cross-institutional studies. ADVANCES IN KNOWLEDGE: Establishing a standard simulation protocol for sampling LETD would reduce the discrepancy when comparing data across different centres, and this can improve the calculation for RBE.

Dosimetric uncertainties impact on cell survival curve with low energy proton.

There is an increasing number of radiobiological experiments being conducted with low energy protons (less than 5 MeV) for radiobiological studies due to availability of sub-millimetre focused beam. However, low energy proton has broad microdosimetric spectra which can introduce dosimetric uncertainty. In this work, we quantify the impact of this dosimetric uncertainties on the cell survival curve and how it affects the estimation of the alpha and beta parameters in the LQ formalism. Monte Carlo simulation is used to generate the microdosimetric spectra in a micrometer-sized water sphere under proton irradiation. This is modelled using radiobiological experiment set-up at the Centre of Ion Beam Application (CIBA) in National University of Singapore. Our results show that the microdosimetric spectra can introduce both systematic and random shifts in dose and cell survival; this effect is most pronounced with low energy protons. The alpha and beta uncertainties can be up to 10% and above 30%, respectively for low energy protons passing through thin cell target (about 10 microns). These uncertainties are non-negligible and show that care must be taken in using the cell survival curve and its derived parameters for radiobiological models.

Dependence of LET on material and its impact on current RBE model.

Biological uncertainty remains one of the main sources of uncertainties in proton therapy, and is encapsulated in a scalar quantity known as relative biological effective (RBE). It is currently recognised that a constant RBE of 1.1 is not consistent with radiobiological experiment and may lead to sub-optimal exploitation of the benefits of proton therapy. To overcome this problem, several RBE models have been developed, and in most of these models, there is a dependence of RBE on dose-averaged linear energy transfer (LET), [Formula: see text]. In this work, we show that the [Formula: see text] estimation in these models during the data-fitting (or parameter estimation) phase could be subjected to a huge uncertainty due to not taking into account cellular materials during simulation, and this uncertainty can propagate down to the resulting RBE models. The dosimetric impact of this [Formula: see text] uncertainty is then evaluated on a simple clinical spread out Bragg peak (SOBP) and a prostate example. Our simulation shows that [Formula: see text] uncertainty due to the use of water as cellular material is non-negligible under low [Formula: see text] and low dose (2 Gy), and can be neglected otherwise. Thus, this study indicates that further dose and range margins may be required for low [Formula: see text] target under low dose. This is due to greater uncertainties in RBE model associated with incomplete knowledge of cellular composition for [Formula: see text] computation.

Sea turtle fibropapilloma tumors share genomic drivers and therapeutic vulnerabilities with human cancers.

Wildlife populations are under intense anthropogenic pressures, with the geographic range of many species shrinking, dramatic reductions in population numbers and undisturbed habitats, and biodiversity loss. It is postulated that we are in the midst of a sixth (Anthropocene) mass extinction event, the first to be induced by human activity. Further, threatening vulnerable species is the increased rate of emerging diseases, another consequence of anthropogenic activities. Innovative approaches are required to help maintain healthy populations until the chronic underlying causes of these issues can be addressed. Fibropapillomatosis in sea turtles is one such wildlife disease. Here, we applied precision-medicine-based approaches to profile fibropapillomatosis tumors to better understand their biology, identify novel therapeutics, and gain insights into viral and environmental triggers for fibropapillomatosis. We show that fibropapillomatosis tumors share genetic vulnerabilities with human cancer types, revealing that they are amenable to treatment with human anti-cancer therapeutics.

Ziprasidone: a novel psychotropic with unique properties.

Ziprasidone (Geodon) is a relatively new atypical antipsychotic medication with a unique pharmacological profile. It is indicated for the treatment of schizophrenia, but has also often been used off-label for other uses. This review summarizes its important properties, specifically the pharmacodynamic parameters, receptor-binding profile and relevance to clinical outcomes, side effects, and potential for drug-drug interactions and established clinical indications. Novel therapeutic applications and relevant clinical trials or reports are also examined. The authors review the current market and speculate on likely changes in 5 years.