VOTE Scores Research Articles

Changing nurses' views of the therapeutic environment: randomised controlled trial.

Although patients value evidence-based therapeutic activities, little is known about nurses' perceptions.AimsTo investigate whether implementing an activities training programme would positively alter staff perceptions of the ward or be detrimental through the increased workload (trial registration: ISRCTN 06545047). We conducted a stepped wedge cluster randomised trial involving 16 wards with psychology-led nurse training as the intervention. The main outcome was a staff self-report measure of perceptions of the ward (VOTE) and secondary outcomes measuring potential deterioration were the Index of Work Satisfaction (IWS) and the Maslach Burnout Inventory (MBI). Data were analysed using mixed-effects regression models, with repeated assessments from staff over time. There were 1075 valid outcome measurements from 539 nursing staff. VOTE scores did not change over time (standardised effect size 0.04, 95% CI -0.09 to 0.18, P = 0.54), neither did IWS or MBI scores (IWS, standardised effect size 0.02, 95% CI -0.11 to 0.16, P = 0.74; MBI standardised effect size -0.09, 95% CI -0.24 to 0.06, P = 0.24). There was a mean increase of 1.5 activities per ward (95% CI -0.4 to 3.4, P = 0.12) and on average 6.3 more patients attended groups (95% CI -4.1 to 16.6, P = 0.23) following training. Staff feedback on training was positive. Our training programme did not change nurses' perceptions of the ward, job satisfaction or burnout. During the study period many service changes occurred, most having a negative impact through increased pressure on staffing, patient mix and management so it is perhaps unsurprising that we found no benefits or reduction in staff skill.Declaration of interestNone.

Towards a prediction model for drug-induced sleep endoscopy as selection tool for oral appliance treatment and positional therapy in obstructive sleep apnea.

To evaluate the effect of different passive maneuvers on upper airway patency during drug-induced sleep endoscopy (DISE) compared to recent literature on treatment outcomes of positional therapy (PT), oral appliance therapy (OAT), and combined treatment in obstructive sleep apnea (OSA) patients. A retrospective, single-center cohort study including a consecutive series of 200 OSA patients. All patients underwent DISE with and without manually performed jaw thrust and lateral head rotation by using the VOTE classification. The effect of these maneuvers were analyzed by using the sum VOTE score comparing non-positional (NPP) and positional OSA patients (PP). Two hundred patients were included (80.5% male) with a mean age of 50.1 ± 11.7years, a BMI of 27.0 ± 3.1kg/m2, and a median AHI of 19.2 events per hour. Forty-four percent of the patients were NPP; of the remaining 56%, 34% was diagnosed with supine isolated and 66% with supine predominant POSA. Manually performed jaw thrust showed a reduction of sum VOTE score of 66.7% in all subgroups. The effect of lateral head rotation was a reduction of 33.3% in NPP and supine predominant PP and 50% in supine isolated PP. Combining these maneuvers a reduction of more than 75% was seen in all patients. The present model leaves room for improvement. The effect of manually performed jaw thrust is greater and the effect of lateral head rotation alone is less than what was expected compared to recent literature on treatment outcome of OAT, PT, and combined treatment.

GOOWE

Designing adaptive classifiers for an evolving data stream is a challenging task due to the data size and its dynamically changing nature. Combining individual classifiers in an online setting, the ensemble approach, is a well-known solution. It is possible that a subset of classifiers in the ensemble outperforms others in a time-varying fashion. However, optimum weight assignment for component classifiers is a problem, which is not yet fully addressed in online evolving environments. We propose a novel data stream ensemble classifier, called Geometrically Optimum and Online-Weighted Ensemble (GOOWE), which assigns optimum weights to the component classifiers using a sliding window containing the most recent data instances. We map vote scores of individual classifiers and true class labels into a spatial environment. Based on the Euclidean distance between vote scores and ideal-points, and using the linear least squares (LSQ) solution, we present a novel, dynamic, and online weighting approach. While LSQ is used for batch mode ensemble classifiers, it is the first time that we adapt and use it for online environments by providing a spatial modeling of online ensembles. In order to show the robustness of the proposed algorithm, we use real-world datasets and synthetic data generators using the Massive Online Analysis (MOA) libraries. First, we analyze the impact of our weighting system on prediction accuracy through two scenarios. Second, we compare GOOWE with eight state-of-the-art ensemble classifiers in a comprehensive experimental environment. Our experiments show that GOOWE provides improved reactions to different types of concept drift compared to our baselines. The statistical tests indicate a significant improvement in accuracy, with conservative time and memory requirements.

Comparative study of VOTE classification in obstructive sleep apnea hypopnea syndrome patients between awake and sleep state

Objective:To compare the differences of the sites of airway obstruction in OSAHS patients between awake and sleep state by using the VOTE classification system. Method:Forty OSAHS patients diagnosed by PSG underwent awake Müller's maneuver and drug-induced sleep endoscopy (DISE). Video and compare the observation. Its findings were described using the VOTE classification system which include the following features: level, degree and configuration of obstruction. Associations were analyzed between different degrees of obstruction, BMI, AHI, minimal SaO₂ and average SaO₂. Result:Our patients had 52.5% complete velum collapse and 30.0% complete oropharyngeal lateral wall collapse in awake Müller's maneuver. In DISE, airway closure of 95.0% cases related to velum occurred collapse in concentric configuration, and 90.0% cases showed completely obstructive. We found that 60.0% complete oropharyngeal lateral wall collapse and 17.5% complete tongue base collapse. There was a significant difference in the VOTE scores between DISE and awake Müller's maneuver, and the VOTE scores of DISE were higher in all levels (P<0.05). No association was found between degrees of obstruction, AHI, BMI, minimal SaO2 and average SaO₂ in Müller's maneuver (P>0.05). Complete velum collapse was just significantly associated with AHI and minimal SaO₂ in DISE (P<0.05). Conclusion:The VOTE scores of DISE were higher than awake Müller's maneuver, reflected by more obstructive levels and severe degree. The difference between different degrees of obstruction, BMI, AHI, minimal SaO₂ and average SaO₂ was not significant.

Efficacy of Upper Airway Stimulation on Collapse Patterns Observed during Drug-Induced Sedation Endoscopy.

To describe upper airway collapse patterns observed on drug-induced sedation endoscopy (DISE) during screening for a clinical trial and to evaluate the impact of collapse patterns found on preoperative DISE on response rates to upper airway stimulation (UAS) therapy. Retrospective review of an ongoing prospective multi-institutional cohort study. Twenty-two participating institutions of the STAR trial. In total, 222 subjects were screened with DISE to determine eligibility for an implantable UAS device. Supine laryngoscopy was performed during moderate sedation (propofol and/or midazolam). Airway collapse pattern and severity were graded at 4 levels, including velum, oropharynx, tongue base, and epiglottis (VOTE classification). Patients with complete concentric collapse (CCC) at the velum were excluded from implantation. The CCC at the velum was observed in 52 (23%) of screened subjects, and these subjects were subsequently excluded from implantation. Of the 170 subjects without CCC at the velum, 126 (77%) underwent implantation: 121 (96%) had multilevel collapse and 5 (4%) had single-level collapse. When comparing preimplantation DISE findings, UAS responders at 12 months had lower baseline VOTE scores compared with therapy nonresponders. Drug-induced sedation endoscopy is an efficient and safe method for determining UAS eligibility and has the potential to identify UAS nonresponders. Most patients had multilevel airway collapse, illustrating the limitations of single-level upper airway surgery in treating obstructive sleep apnea. Upper airway stimulation is effective therapy for most patients with multilevel airway collapse; however, patients with complete anterior-posterior or lateral soft palate and/or epiglottic collapse may be at increased risk of therapy failure.

Privacy‐friendly weighted‐reputation aggregation protocols against malicious adversaries in cloud services

SummaryReputation systems are used for evaluating trustworthiness of the users based on their feedback (i.e., votes) about each other. Such systems are particularly important for cloud service providers, as they allow them to collect and aggregate feedback on the past behavior of users. Weighted‐reputation aggregation is a protocol, where the vote server has a weight vector for all voters, each voter has a vote score yi, and they cooperate to compute . We call it ‘privacy‐friendly’, if the respective inputs are kept private. In other words, a privacy‐friendly weighted aggregation protocol is a secure evaluation for functionality . In this work, we propose two privacy‐friendly weighted‐reputation aggregation protocols: one in semi‐honest model and another one in malicious model. The latter protocol uses the cryptographic primitives of homomorphic encryption, verifiable encryption, and the proof of knowledge of a discrete logarithm. Our protocols need only two rounds of communications, which is very efficient in practice. Our protocols are secure against the collusion of at most n − 2malicious adversaries. Copyright © 2014 John Wiley &amp; Sons, Ltd.

Accurate Determination of Imaging Modality using an Ensemble of Text- and Image-Based Classifiers

Imaging modality can aid retrieval of medical images for clinical practice, research, and education. We evaluated whether an ensemble classifier could outperform its constituent individual classifiers in determining the modality of figures from radiology journals. Seventeen automated classifiers analyzed 77,495 images from two radiology journals. Each classifier assigned one of eight imaging modalities--computed tomography, graphic, magnetic resonance imaging, nuclear medicine, positron emission tomography, photograph, ultrasound, or radiograph-to each image based on visual and/or textual information. Three physicians determined the modality of 5,000 randomly selected images as a reference standard. A "Simple Vote" ensemble classifier assigned each image to the modality that received the greatest number of individual classifiers' votes. A "Weighted Vote" classifier weighted each individual classifier's vote based on performance over a training set. For each image, this classifier's output was the imaging modality that received the greatest weighted vote score. We measured precision, recall, and F score (the harmonic mean of precision and recall) for each classifier. Individual classifiers' F scores ranged from 0.184 to 0.892. The simple vote and weighted vote classifiers correctly assigned 4,565 images (F score, 0.913; 95% confidence interval, 0.905-0.921) and 4,672 images (F score, 0.934; 95% confidence interval, 0.927-0.941), respectively. The weighted vote classifier performed significantly better than all individual classifiers. An ensemble classifier correctly determined the imaging modality of 93% of figures in our sample. The imaging modality of figures published in radiology journals can be determined with high accuracy, which will improve systems for image retrieval.

The Partisan Foundations of Balanced Budget Politics

The historical image of the Republican Party as a party strongly supporting the balanced budget norm has come under increasing scrutiny as many prominent Republicans, including President George W. Bush, have overtly argued that tax cuts should be a higher priority than deficit reduction. Have the Democrats truly surpassed the Republicans as being better advocates for deficit reduction, however? To determine partisan support for balancing the budget, I analyze balanced budget amendment votes in Congress since 1982, the “Fiscal Responsibility” vote scores given to members of Congress by the Concord Coalition, and the relationship between party control of the White House and the size of the deficit. Findings suggest mixed evidence to support both Democratic and Republican claims to be the party most likely to back deficit reduction. While evidence from the legislative branch implies that Republicans are competitive with the Democrats in regards to deficit reduction, the story from the executive branch suggests that Democrats have done a much better job of reigning in budget deficits. As a result, the leadership of the White House in regards to balancing the budget appears to be more important than ever.

Who are the "Deficit Hawks?": An Analysis of the Concord Coalition Congressional Vote Scores

Which members of Congress are most likely to consistently support policies leading to balanced budgets? Who are the true “deficit hawks” in Congress? This paper analyzes the degree to which the nation’s representatives and senators support policies conducive toward balancing the budget and reducing the national debt, as measured by the annual Fiscal Responsibility scores from 1995-2000 given to members of the House and Senate by the Concord Coalition. An analysis of the Concord Coalition vote scores indicates that a legislator’s party tends to have an important effect on congressional votes on balanced budget priorities, though the direction of partisan influences is not consistent. Fiscal responsibility is related to party preference, but varies over time. That is, for some years being a Republican has a positive effect on scores by the Concord Coalition, in other years there is a positive relationship being a Democrat. The fact that the votes that the Concord Coalition find most relevant to deficit reduction cannot be placed consistently on the left or right of the American ideological spectrum differentiates it from most other interest groups from an ideological perspective.

Searching for cincinnatus: Representatives' backgrounds and voting behavior

Proponents of legislative term limits express concern about professional politicians, individuals who have no other occupation than running for and holding office. Term limits presumably will help allow the reemergence of the citizen-legislator. This paper examines whether pre-political background affects Congressional voting, specifically concentrating on whether a business background affects U.S. Chamber of Commerce vote scores. Business background significantly affects voting in the House, even with party affiliation and corporate and labor campaign contributions included as control variables, but background variables are insignificant for Senate voting.