The Feasibility of Closing Vehicle Crossings along St. Charles Avenue: A Study of Transit Safety and Performance

The St. Charles streetcar is an important transit line in the city of New Orleans, with about 65,000 people living within a ½ mile walking distance from it. However, the line experiences a very high streetcar/automobile crash rate due in large part to the large number of grade vehicle crossings over the tracks that lack signalization. Through traffic modeling, the closure of many of these vehicle crossings and the diversion of automotive traffic to the remaining, signalized crossings is analyzed to determine traffic impacts on street network. The result is a modest increase in traffic, about 7-8%, at the remaining signalized intersections

Study of knowledge, attitude, and practices towards current updates of pharmacovigilance and adverse drug reaction reporting among doctors in a tertiary care teaching hospital of Western India

Background: In general, adverse drug reactions (ADRs) are global problems causing both morbidity and mortality. Spontaneous ADR reporting is important to monitor adverse effects of medicines but under reporting is still very prevalent so, there is a need of constant monitoring and rectification of system of Pharmacovigilance. The objective of this study was to evaluate the knowledge, attitude, and practices (KAP) of the healthcare professionals about Pharmacovigilance and to identify the reason for under reporting of ADRs.Methods: A cross-sectional study was carried out using a pretested questionnaire among doctors with minimum qualification MBBS or B.D.S. including faculties, senior and junior residents. Subsequently, analysis of association between education and experience was done by chi square test at P-value <0.05.Results: A pretested questionnaire was distributed among 403 doctors and 240 (59.16%) responded voluntarily. In general, 131 (54.58%) participants noted lack of time to report ADR while 90 (37.50%) participants noted no benefit of reporting already known ADR. On the other hand, total 104 (43.33%) participants were aware about need to report a serious adverse event during “Clinical Trial” within 24 hours to the Ethics Committee. Only 87 (36.25%) participants noted a need of reporting of already known ADR.Conclusions: Participants had good knowledge and attitude towards pharmacovigilance, but the actual practice of ADR reporting is still deficient among them that can be improved by sensitization training and involvement of grass root level health care workers

Minimal hepatic encephalopathy: consensus statement of a working party of the Indian National Association for study of the liver

Hepatic encephalopathy (HE) is a major complication that develops in some form and at some stage in a majority of patients with liver cirrhosis. Overt HE occurs in approximately 30-45% of cirrhotic patients. Minimal HE (MHE), the mildest form of HE, is characterized by subtle motor and cognitive deficits and impairs health-related quality of life. The Indian National Association for Study of the Liver (INASL) set up a Working Party on MHE in 2008 with a mandate to develop consensus guidelines on various aspects of MHE relevant to clinical practice. Questions related to the definition of MHE, its prevalence, diagnosis, clinical characteristics, pathogenesis, natural history and treatment were addressed by the members of the Working Party

A leprosy clinical severity scale for erythema nodosum leprosum: An international, multicentre validation study of the ENLIST ENL Severity Scale.

OBJECTIVES: We wished to validate our recently devised 16-item ENLIST ENL Severity Scale, a clinical tool for measuring the severity of the serious leprosy associated complication of erythema nodosum leprosum (ENL). We also wished to assess the responsiveness of the ENLIST ENL Severity Scale in detecting clinical change in patients with ENL. METHODS: Participants, recruited from seven centres in six leprosy endemic countries, were assessed using the ENLIST ENL Severity Scale by two researchers, one of whom categorised the severity of ENL. At a subsequent visit a further assessment using the scale was made and both participant and physician rated the change in ENL using the subjective categories of "Much better", "somewhat better", "somewhat worse" and "much worse" compared with "No change" or "about the same". RESULTS: 447 participants were assessed with the ENLIST ENL Severity Scale. The Cronbach alpha of the scale and each item was calculated to determine the internal consistency of the scale. The ENLIST ENL Severity Scale had good internal consistency and this improved following removal of six items to give a Cronbach's alpha of 0.77. The cut off between mild ENL and more severe disease was 9 determined using ROC curves. The minimal important difference of the scale was determined to be 5 using both participant and physician ratings of change. CONCLUSIONS: The 10-item ENLIST ENL Severity Scale is the first valid, reliable and responsive measure of ENL severity and improves our ability to assess and compare patients and their treatments in this severe and difficult to manage complication of leprosy. The ENLIST ENL Severity Scale will assist physicians in the monitoring and treatment of patients with ENL. The ENLIST ENL Severity Scale is easy to apply and will be useful as an outcome measure in treatment studies and enable the standardisation of other clinical and laboratory ENL research

Atrial Fibrillation Burden and Atrial Shunt Therapy in Heart Failure With Preserved Ejection Fraction

Background: Atrial fibrillation (AF) is a common comorbidity in patients with heart failure with preserved ejection fraction (HFpEF) and in heart failure with mildly reduced ejection fraction (HFmrEF). Objectives: This study sought to describe AF burden and its clinical impact among individuals with HFpEF and HFmrEF who participated in a randomized clinical trial of atrial shunt therapy (REDUCE LAP-HF II [A Study to Evaluate the Corvia Medical, Inc IASD System II to Reduce Elevated Left Atrial Pressure in Patients with Heart Failure]) and to evaluate the effect of atrial shunt therapy on AF burden. Methods: Study investigators characterized AF burden among patients in the REDUCE LAP-HF II trial by using ambulatory cardiac patch monitoring at baseline (median patch wear time, 6 days) and over a 12-month follow-up (median patch wear time, 125 days). The investigators determined the association of baseline AF burden with long-term clinical events and examined the effect of atrial shunt therapy on AF burden over time. Results: Among 367 patients with cardiac monitoring data at baseline and follow-up, 194 (53%) had a history of AF or atrial flutter (AFL), and median baseline AF burden was 0.012% (IQR: 0%-1.3%). After multivariable adjustment, baseline AF burden ≥0.012% was significantly associated with heart failure (HF) events (HR: 2.00; 95% CI: 1.17-3.44; P = 0.01) both with and without a history of AF or AFL (P for interaction = 0.68). Adjustment for left atrial reservoir strain attenuated the baseline AF burden-HF event association (HR: 1.71; 95% CI: 0.93-3.14; P = 0.08). Of the 367 patients, 141 (38%) had patch-detected AF during follow-up without a history of AF or AFL. Atrial shunt therapy did not change AF incidence or burden during follow-up. Conclusions: In HFpEF and HFmrEF, nearly 40% of patients have subclinical AF by 1 year. Baseline AF burden, even at low levels, is associated with HF events. Atrial shunt therapy does not affect AF incidence or burden.</p

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Global prevalence and genotype distribution of hepatitis C virus infection in 2015 : A modelling study

Publisher Copyright: © 2017 Elsevier LtdBackground The 69th World Health Assembly approved the Global Health Sector Strategy to eliminate hepatitis C virus (HCV) infection by 2030, which can become a reality with the recent launch of direct acting antiviral therapies. Reliable disease burden estimates are required for national strategies. This analysis estimates the global prevalence of viraemic HCV at the end of 2015, an update of—and expansion on—the 2014 analysis, which reported 80 million (95% CI 64–103) viraemic infections in 2013. Methods We developed country-level disease burden models following a systematic review of HCV prevalence (number of studies, n=6754) and genotype (n=11 342) studies published after 2013. A Delphi process was used to gain country expert consensus and validate inputs. Published estimates alone were used for countries where expert panel meetings could not be scheduled. Global prevalence was estimated using regional averages for countries without data. Findings Models were built for 100 countries, 59 of which were approved by country experts, with the remaining 41 estimated using published data alone. The remaining countries had insufficient data to create a model. The global prevalence of viraemic HCV is estimated to be 1·0% (95% uncertainty interval 0·8–1·1) in 2015, corresponding to 71·1 million (62·5–79·4) viraemic infections. Genotypes 1 and 3 were the most common cause of infections (44% and 25%, respectively). Interpretation The global estimate of viraemic infections is lower than previous estimates, largely due to more recent (lower) prevalence estimates in Africa. Additionally, increased mortality due to liver-related causes and an ageing population may have contributed to a reduction in infections. Funding John C Martin Foundation.publishersversionPeer reviewe