Surface Waves on a Semi-toroidal Water Ring

We study the dynamics of surface waves on a semi-toroidal ring of water that is excited by vertical vibration. We create this specific fluid volume by patterning a glass plate with a hydrophobic coating, which confines the fluid to a precise geometric region. To excite the system, the supporting plate is vibrated up and down, thus accelerating and decelerating the fluid ring along its toroidal axis. When the driving acceleration is sufficiently high, the surface develops a standing wave, and at yet larger accelerations, a traveling wave emerges. We also explore frequency dependencies and other geometric shapes of confinement

Medication Management Program Among Elderly at a Residential Facility

Abstract This quality improvement project aimed to address medication management-related issues at a residential facility. The project\u27s population was elderly residents who self- administered their medications. A root cause analysis and SWOT analysis identified multiple factors contributing to medication management errors, including lack of resident education, resident competency, and technology limitations. An intervention plan was developed and implemented in two phases. Phase 1 involved conducting medication reconciliation, assessing resident competency, and 1:1 educational sessions with the residents. Educational retention was assessed by using a pre-test and a post-test. Phase 2, to be implemented in the future, will address technology limitations, incorporate an electronic medical records (EMR) system, and provide ongoing staff education. Results from Phase 1 include 80% recalled new information while 20% showed no change after completion of the educational session and the pre/post-test; from those residents assessed with the Medi-Cog, 55% scored above 8 out of 10 while 45% scored below the cutoff score of 8, and last 100% of the Medication Administration Records (MAR) were reviewed. Although time constraints prevented Phase 2 interventions from being implemented, implementing an EMR system and a professional development plan for staff education are expected to contribute to further improvements in medication management at the residential facility. Continued monitoring and collaboration with the residents and staff are vital for sustained success

Factors in perioperative care that determine blood loss in liver surgery

AbstractObjectivesExcessive blood loss during liver surgery contributes to postoperative morbidity and mortality and the minimizing of blood loss improves outcomes. This study examines pre- and intraoperative factors contributing to blood loss and identifies areas for improvement.MethodsAll patients who underwent elective hepatic resection between June 2007 and June 2009 were identified. Detailed information on the pre- and perioperative clinical course was analysed. Univariate and multivariate analyses were used to identify factors associated with intraoperative blood loss.ResultsA total of 175 patients were studied, of whom 95 (54%) underwent resection of three or more segments. Median blood loss was 782ml. Greater blood loss occurred during major resections and prolonged surgery and was associated with an increase in postoperative complications (P= 0.026). Peak central venous pressure (CVP) of >10cm H2O was associated with increased blood loss (P= 0.01). Although no differences in case mix were identified, blood loss varied significantly among anaesthetists, as did intraoperative volumes of i.v. fluids and transfusion practices.ConclusionsThis study confirms a relationship between CVP and blood loss in hepatic resection. Intraoperative CVP values were higher than those described in other studies. There was variation in the intraoperative management of patients. Collaboration between surgical and anaesthesia teams is required to minimize blood loss and the standardization of intraoperative anaesthesia practice may improve outcomes following liver surgery

Abemaciclib in Combination with Single-Agent Options in Patients with Stage IV Non–Small Cell Lung Cancer: A Phase Ib Study

Purpose: Abemaciclib, a dual inhibitor of cyclin-dependent kinases 4 and 6, has demonstrated preclinical activity in non–small cell lung cancer (NSCLC). A multicenter, nonrandomized, open-label phase Ib study was conducted to test safety, MTD, pharmacokinetics, and preliminary antitumor activity of abemaciclib in combination with other therapies for treatment in patients with metastatic NSCLC. Patients and Methods: An initial dose escalation phase was used to determine the MTD of twice-daily oral abemaciclib (150, 200 mg) plus pemetrexed, gemcitabine, or ramucirumab, followed by an expansion phase for each drug combination. Pemetrexed and gemcitabine were administered according to label. The abemaciclib plus ramucirumab study examined two dosing schedules. Results: The three study parts enrolled 86 patients; all received ≥1 dose of combination therapy. Across arms, the most common treatment-emergent adverse events were fatigue, diarrhea, neutropenia, decreased appetite, and nausea. The trial did not identify an abemaciclib MTD for the combination with pemetrexed or gemcitabine but did so for the combination of abemaciclib with days 1 and 8 ramucirumab (8 mg/kg). Plasma sample analysis showed that abemaciclib did not influence the pharmacokinetics of the combination agents and the combination agents did not affect abemaciclib exposure. The disease control rate was 57% for patients treated with abemaciclib–pemetrexed, 25% for abemaciclib–gemcitabine, and 54% for abemaciclib–ramucirumab. Median progression-free survival was 5.55, 1.58, and 4.83 months, respectively. Conclusions: Abemaciclib demonstrated an acceptable safety profile when dosed on a continuous twice-daily schedule in combination with pemetrexed, gemcitabine, or ramucirumab. Abemaciclib exposures remained consistent with those observed in single-agent studies

Coronary atherosclerosis scoring with semiquantitative CCTA risk scores for prediction of major adverse cardiac events: Propensity score-based analysis of diabetic and non-diabetic patients.

AIMS:We aimed to compare semiquantitative coronary computed tomography angiography (CCTA) risk scores - which score presence, extent, composition, stenosis and/or location of coronary artery disease (CAD) - and their prognostic value between patients with and without diabetes mellitus (DM). Risk scores derived from general chest-pain populations are often challenging to apply in DM patients, because of numerous confounders. METHODS:Out of a combined cohort from the Leiden University Medical Center and the CONFIRM registry with 5-year follow-up data, we performed a secondary analysis in diabetic patients with suspected CAD who were clinically referred for CCTA. A total of 732 DM patients was 1:1 propensity-matched with 732 non-DM patients by age, sex and cardiovascular risk factors. A subset of 7 semiquantitative CCTA risk scores was compared between groups: 1) any stenosis ≥50%, 2) any stenosis ≥70%, 3) stenosis-severity component of the coronary artery disease-reporting and data system (CAD-RADS), 4) segment involvement score (SIS), 5) segment stenosis score (SSS), 6) CT-adapted Leaman score (CT-LeSc), and 7) Leiden CCTA risk score. Cox-regression analysis was performed to assess the association between the scores and the primary endpoint of all-cause death and non-fatal myocardial infarction. Also, area under the receiver-operating characteristics curves were compared to evaluate discriminatory ability. RESULTS:A total of 1,464 DM and non-DM patients (mean age 58 ± 12 years, 40% women) underwent CCTA and 155 (11%) events were documented after median follow-up of 5.1 years. In DM patients, the 7 semiquantitative CCTA risk scores were significantly more prevalent or higher as compared to non-DM patients (p ≤ 0.022). All scores were independently associated with the primary endpoint in both patients with and without DM (p ≤ 0.020), with non-significant interaction between the scores and diabetes (interaction p ≥ 0.109). Discriminatory ability of the Leiden CCTA risk score in DM patients was significantly better than any stenosis ≥50% and ≥70% (p = 0.003 and p = 0.007, respectively), but comparable to the CAD-RADS, SIS, SSS and CT-LeSc that also focus on the extent of CAD (p ≥ 0.265). CONCLUSION:Coronary atherosclerosis scoring with semiquantitative CCTA risk scores incorporating the total extent of CAD discriminate major adverse cardiac events well, and might be useful for risk stratification of patients with DM beyond the binary evaluation of obstructive stenosis alone

What Is the Additive Value of Nutritional Deficiency to Va-Fi in the Risk Assessment For Heart Failure Patients?

OBJECTIVES: to assess the impact of adding the Prognostic Nutritional Index (PNI) to the U.S. Veterans Health Administration frailty index (VA-FI) for the prediction of time-to-death and other clinical outcomes in Veterans hospitalized with Heart Failure. METHODS: A retrospective cohort study of veterans hospitalized for heart failure (HF) from October 2015 to October 2018. Veterans ≥50 years with albumin and lymphocyte counts, needed to calculate the PNI, in the year prior to hospitalization were included. We defined malnutrition as PNI ≤43.6, based on the Youden index. VA-FI was calculated from the year prior to the hospitalization and identified three groups: robust (≤0.1), prefrail (0.1-0.2), and frail (\u3e0.2). Malnutrition was added to the VA-FI (VA-FI-Nutrition) as a 32 RESULTS: We identified 37,601 Veterans hospitalized for HF (mean age: 73.4 ± 10.3 years, BMI: 31.3 ± 7.4 kg/m CONCLUSION: Adding PNI to VA-FI provides a more accurate and comprehensive assessment among Veterans hospitalized for HF. Clinicians should consider adding a specific nutrition algorithm to automated frailty tools to improve the validity of risk prediction in patients hospitalized with HF

Effect of Public Deliberation on Attitudes toward Return of Secondary Results in Genomic Sequencing

The increased use of genomic sequencing in clinical diagnostics and therapeutics makes imperative the development of guidelines and policies about how to handle secondary findings. For reasons both practical and ethical, the creation of these guidelines must take into consideration the informed opinions of the lay public. As part of a larger Clinical Sequencing Exploratory Research (CSER) consortium project, we organized a deliberative democracy (DD) session that engaged 66 participants in dialogue about the benefits and risks associated with the return of secondary findings from clinical genomic sequencing. Participants were educated about the scientific and ethical aspects of the disclosure of secondary findings by experts in medical genetics and bioethics, and then engaged in facilitated discussion of policy options for the disclosure of three types of secondary findings: 1) medically actionable results; 2) adult onset disorders found in children; and 3) carrier status. Participants’ opinions were collected via surveys administered one month before, immediately following, and one month after the DD session. Post DD session, participants were significantly more willing to support policies that do not allow access to secondary findings related to adult onset conditions in children (Χ2 (2, N = 62) = 13.300, p = 0.001) or carrier status (Χ2 (2, N = 60) = 11.375, p = 0.003). After one month, the level of support for the policy denying access to secondary findings regarding adult‐onset conditions remained significantly higher than the pre‐DD level, although less than immediately post‐DD (Χ2 (1, N = 60) = 2.465, p = 0.041). Our findings suggest that education and deliberation enhance public appreciation of the scientific and ethical complexities of genome sequencing.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146892/1/jgc40122-sup-0006.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146892/2/jgc40122.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146892/3/jgc40122-sup-0005.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146892/4/jgc40122-sup-0007.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146892/5/jgc40122-sup-0002.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146892/6/jgc40122-sup-0001.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146892/7/jgc40122-sup-0003.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146892/8/jgc40122-sup-0004.pd

Dogslife: A web-based longitudinal study of Labrador Retriever health in the UK

<p>Abstract</p> <p>Background</p> <p>Dogslife is the first large-scale internet-based longitudinal study of canine health. The study has been designed to examine how environmental and genetic factors influence the health and development of a birth cohort of UK-based pedigree Labrador Retrievers.</p> <p>Results</p> <p>In the first 12 months of the study 1,407 Kennel Club (KC) registered eligible dogs were recruited, at a mean age of 119 days of age (SD 69 days, range 3 days – 504 days). Recruitment rates varied depending upon the study team’s ability to contact owners. Where owners authorised the provision of contact details 8.4% of dogs were recruited compared to 1.3% where no direct contact was possible. The proportion of dogs recruited was higher for owners who transferred the registration of their puppy from the breeder to themselves with the KC, and for owners who were sent an e-mail or postcard requesting participation in the project. Compliance with monthly updates was highly variable. For the 280 dogs that were aged 400 days or more on the 30^th June 2011, we estimated between 39% and 45% of owners were still actively involved in the project. Initial evaluation suggests that the cohort is representative of the general population of the KC registered Labrador Retrievers eligible to enrol with the project. Clinical signs of illnesses were reported in 44.3% of Labrador Retrievers registered with Dogslife (median age of first illness 138 days), although only 44.1% of these resulted in a veterinary presentation (median age 316 days).</p> <p>Conclusions</p> <p>The web-based platform has enabled the recruitment of a representative population of KC registered Labrador Retrievers, providing the first large-scale longitudinal population-based study of dog health. The use of multiple different methods (e-mail, post and telephone) of contact with dog owners was essential to maximise recruitment and retention of the cohort.</p

Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning.

OBJECTIVES:To develop, demonstrate and evaluate an automated deep learning method for multiple cardiovascular structure segmentation. BACKGROUND:Segmentation of cardiovascular images is resource-intensive. We design an automated deep learning method for the segmentation of multiple structures from Coronary Computed Tomography Angiography (CCTA) images. METHODS:Images from a multicenter registry of patients that underwent clinically-indicated CCTA were used. The proximal ascending and descending aorta (PAA, DA), superior and inferior vena cavae (SVC, IVC), pulmonary artery (PA), coronary sinus (CS), right ventricular wall (RVW) and left atrial wall (LAW) were annotated as ground truth. The U-net-derived deep learning model was trained, validated and tested in a 70:20:10 split. RESULTS:The dataset comprised 206 patients, with 5.130 billion pixels. Mean age was 59.9 ± 9.4 yrs., and was 42.7% female. An overall median Dice score of 0.820 (0.782, 0.843) was achieved. Median Dice scores for PAA, DA, SVC, IVC, PA, CS, RVW and LAW were 0.969 (0.979, 0.988), 0.953 (0.955, 0.983), 0.937 (0.934, 0.965), 0.903 (0.897, 0.948), 0.775 (0.724, 0.925), 0.720 (0.642, 0.809), 0.685 (0.631, 0.761) and 0.625 (0.596, 0.749) respectively. Apart from the CS, there were no significant differences in performance between sexes or age groups. CONCLUSIONS:An automated deep learning model demonstrated segmentation of multiple cardiovascular structures from CCTA images with reasonable overall accuracy when evaluated on a pixel level

Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry.

Background Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed tomography angiography-determined qualitative and quantitative plaque features within a machine learning (ML) framework to determine its performance for predicting RPP. Methods and Results Qualitative and quantitative coronary computed tomography angiography plaque characterization was performed in 1083 patients who underwent serial coronary computed tomography angiography from the PARADIGM (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging) registry. RPP was defined as an annual progression of percentage atheroma volume ≥1.0%. We employed the following ML models: model 1, clinical variables; model 2, model 1 plus qualitative plaque features; model 3, model 2 plus quantitative plaque features. ML models were compared with the atherosclerotic cardiovascular disease risk score, Duke coronary artery disease score, and a logistic regression statistical model. 224 patients (21%) were identified as RPP. Feature selection in ML identifies that quantitative computed tomography variables were higher-ranking features, followed by qualitative computed tomography variables and clinical/laboratory variables. ML model 3 exhibited the highest discriminatory performance to identify individuals who would experience RPP when compared with atherosclerotic cardiovascular disease risk score, the other ML models, and the statistical model (area under the receiver operating characteristic curve in ML model 3, 0.83 [95% CI 0.78-0.89], versus atherosclerotic cardiovascular disease risk score, 0.60 [0.52-0.67]; Duke coronary artery disease score, 0.74 [0.68-0.79]; ML model 1, 0.62 [0.55-0.69]; ML model 2, 0.73 [0.67-0.80]; all P&lt;0.001; statistical model, 0.81 [0.75-0.87], P=0.128). Conclusions Based on a ML framework, quantitative atherosclerosis characterization has been shown to be the most important feature when compared with clinical, laboratory, and qualitative measures in identifying patients at risk of RPP