Fossortega2725
The disruption of conventional manufacturing, supply, and distribution channels during the COVID-19 pandemic caused widespread shortages in personal protective equipment (PPE) and other medical supplies. These shortages catalyzed local efforts to use nontraditional, rapid manufacturing to meet urgent healthcare needs. Here we present a crisis-responsive design framework designed to assist with product development under pandemic conditions. The framework emphasizes stakeholder engagement, comprehensive but efficient needs assessment, rapid manufacturing, and modified product testing to enable accelerated development of healthcare products. We contrast this framework with traditional medical device manufacturing that proceeds at a more deliberate pace, discuss strengths and weakness of pandemic-responsive fabrication, and consider relevant regulatory policies. We highlight the use of the crisis-responsive framework in a case study of face shield design and production for a large US academic hospital. Finally, we make recommendations aimed at improving future resilience to pandemics and healthcare emergencies. These include continued development of open source designs suitable for rapid manufacturing, education of maker communities and hospital administrators about rapidly-manufactured medical devices, and changes in regulatory policy that help strike a balance between quality and innovation.
Many European countries introduced (confidential) rebates in the past years. Authorities and manufacturers argue that this strategy allows reduction of spending on high-cost drugs, and quick access of innovative drugs. We evaluated these arguments using Switzerland as an example, one of the last countries with transparent rebates.
We identified all drugs granted rebates in Switzerland and all new drugs without rebates between January 2012 and October 2020. We assessed the amount of introduced drugs with and without rebates over time, clinical benefit of drugs with rebates, and duration between approval and price determination.
Our study cohort included 51 drugs with rebates, the majority were cancer drugs (32; 63%). 15/51 (29%) had high clinical benefit, 25/51 (49%) low benefit and for 11/51 (22%) benefit could not be assessed. The number of drugs with rebates increased in recent years. Time duration between approval and price determination was 302 days in median for drugs with and 106 days for drugs without rebates.
Drugs with rebates may hamper access to drugs and lead to overpayment. Improving transparency on actual drug prices and stronger cooperation between countries could help national authorities to make better informed pricing decisions, and improve access of innovative drugs to patients.
This study was partially funded by the Swiss Cancer Research Foundation (Krebsforschung Schweiz) and the Swiss National Foundation (SNF).
This study was partially funded by the Swiss Cancer Research Foundation (Krebsforschung Schweiz) and the Swiss National Foundation (SNF).
Atrial fibrillation (AF) is the most common supraventricular arrhythmia, characterized by disorganized atrial electrical activity, maintained by localized arrhythmogenic atrial drivers. Pulmonary vein isolation (PVI) allows to exclude PV-related drivers. However, PVI is less effective in patients with additional extra-PV arrhythmogenic drivers.
To discriminate whether AF drivers are located near the PVs vs extra-PV regions using the noninvasive 12-lead electrocardiogram (ECG) in a computational and clinical framework, and to computationally predict the acute success of PVI in these cohorts of data.
AF drivers were induced in 2 computerized atrial models and combined with 8 torso models, resulting in 1128 12-lead ECGs (80 ECGs with AF drivers located in the PVs and 1048 in extra-PV areas). A total of 103 features were extracted from the signals. Binary decision tree classifier was trained on the simulated data and evaluated using hold-out cross-validation. The PVs were subsequently isolated in the models to assess PVI success. Finally, the classifier was tested on a clinical dataset (46 patients 23 PV-dependent AF and 23 with additional extra-PV sources).
The classifier yielded 82.6% specificity and 73.9% sensitivity for detecting PV drivers on the clinical data. Consistency analysis on the 46 patients resulted in 93.5% results match. Applying PVI on the simulated AF cases terminated AF in 100% of the cases in the PV class.
Machine learning-based classification of 12-lead-ECG allows discrimination between patients with PV drivers vs those with extra-PV drivers of AF. The novel algorithm may aid to identify patients with high acute success rates to PVI.
Machine learning-based classification of 12-lead-ECG allows discrimination between patients with PV drivers vs those with extra-PV drivers of AF. The novel algorithm may aid to identify patients with high acute success rates to PVI.Therapeutics for hospitalized COVID-19 patients were identified through a robust research response with several lessons learned clinical trial data should guide therapeutic use, results should not be extrapolated between disease stages, and robust studies should be designed to give clinically relevant data. These lessons should be applied to the outpatient research response.
Data on COVID-19-induced disruption to routine vaccinations in the South-East Asia and Western Pacific regions (SEAR/WPR) have been sparse. This study aimed to quantify the impact of COVID-19 on routine vaccinations by country, antigen, and sector (public or private), up to 1 June 2020, and to identify the reasons for disruption and possible solutions.
Sanofi Pasteur teams from 19 countries in SEAR/WPR completed a structured questionnaire reporting on COVID-19 disruptions for 13-19 routinely delivered antigens per country, based on sales data, government reports, and regular physician interactions. Data were analysed descriptively, disruption causes ranked, and solutions evaluated using a modified public health best practices framework.
95% (18/19) of countries reported vaccination disruption. When stratified by country, a median of 91% (interquartile range 77-94) of antigens were impacted. Infancy and school-entry age vaccinations were most impacted. Orlistat Both public and private sector healthcare providers experienced disruptions.
