11 research outputs found

    Risk of COVID-19 after natural infection or vaccination

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    BACKGROUND: While vaccines have established utility against COVID-19, phase 3 efficacy studies have generally not comprehensively evaluated protection provided by previous infection or hybrid immunity (previous infection plus vaccination). Individual patient data from US government-supported harmonized vaccine trials provide an unprecedented sample population to address this issue. We characterized the protective efficacy of previous SARS-CoV-2 infection and hybrid immunity against COVID-19 early in the pandemic over three-to six-month follow-up and compared with vaccine-associated protection. METHODS: In this post-hoc cross-protocol analysis of the Moderna, AstraZeneca, Janssen, and Novavax COVID-19 vaccine clinical trials, we allocated participants into four groups based on previous-infection status at enrolment and treatment: no previous infection/placebo; previous infection/placebo; no previous infection/vaccine; and previous infection/vaccine. The main outcome was RT-PCR-confirmed COVID-19 \u3e7-15 days (per original protocols) after final study injection. We calculated crude and adjusted efficacy measures. FINDINGS: Previous infection/placebo participants had a 92% decreased risk of future COVID-19 compared to no previous infection/placebo participants (overall hazard ratio [HR] ratio: 0.08; 95% CI: 0.05-0.13). Among single-dose Janssen participants, hybrid immunity conferred greater protection than vaccine alone (HR: 0.03; 95% CI: 0.01-0.10). Too few infections were observed to draw statistical inferences comparing hybrid immunity to vaccine alone for other trials. Vaccination, previous infection, and hybrid immunity all provided near-complete protection against severe disease. INTERPRETATION: Previous infection, any hybrid immunity, and two-dose vaccination all provided substantial protection against symptomatic and severe COVID-19 through the early Delta period. Thus, as a surrogate for natural infection, vaccination remains the safest approach to protection. FUNDING: National Institutes of Health

    An?lise local e sist?mica das rea??es tissulares a diferentes materiais utilizados em pulpotomias : estudo em ratos

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    Made available in DSpace on 2015-04-14T13:30:02Z (GMT). No. of bitstreams: 1 434141.pdf: 4096445 bytes, checksum: 46ea01752aceb50c79baf98a79715628 (MD5) Previous issue date: 2011-08-31Introdu??o : O objetivo deste estudo foi avaliar, em ratos, a rea??o do tecido conjuntivo subcut?neo, e dos ?rg?os f?gado e rim, a materiais utilizados em pulpotomias: agregado tri?xido mineral (MTA), pasta de hidr?xido de c?lcio (HC) e formocresol (FC). M?todos: Tubos de polietileno vazios (grupo controle) e contendo os materiais de teste foram implantados no tecido subcut?neo de 46 ratos. Ap?s 7 e 21 dias, as observa??es no dorso foram feitas para altera??es inflamat?rias, condensa??o fibrosa, forma??o de abscesso e corpo estranho e, no f?gado e rim, foram avaliadas esteatose, apoptose, inflama??o, altera??es vasculares e hipercelularidade. Compara??es entre os grupos e per?odos de tempo foram feitas usando o teste de Kruskal-Wallis, Post-hoc e Mann-Whitney. Resultados: Os grupos MTA e HC mostraram um comportamento semelhante ao do grupo controle, nas altera??es inflamat?rias em 21 dias, ao contr?rio do grupo FC, o qual apresentou diferen?a estatisticamente significante em rela??o aos outros grupos. No grupo FC, n?o houve forma??o de c?psula fribrosa e houve forma??o de abscesso, em 21 dias. Em todos grupos, altera??es no f?gado e rim foram observadas. Conclus?o: Os grupos MTA e HC mostraram um comportamento similar em todos os eventos analisados. O grupo FC apresentou resultados n?o favor?veis. Foram observadas altera??es tissulares no f?gado e rim

    Breathing Pattern Monitoring by Using Remote Sensors

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    The ability to continuously and unobtrusively monitor and classify breathing patterns can be very valuable for automated health assessments because respiration is tightly coupled to many physiological processes. Pathophysiological changes in these processes often manifest in altered breathing patterns and can thus be immediately detected. In order to develop a breathing pattern monitoring system, a study was conducted in which volunteer subjects were asked to breathe according to a predefined breathing protocol containing multiple breathing patterns while being recorded with color and thermal cameras. The recordings were used to develop and compare several respiratory signal extraction algorithms. An algorithm for the robust extraction of multiple respiratory features was developed and evaluated, capable of differentiating a wide range of respiratory patterns. These features were used to train a one vs. one multiclass support vector machine, which can distinguish between breathing patterns with an accuracy of 95.79 %. The recorded dataset was published to enable further improvement of contactless breathing pattern classification, especially for complex breathing patterns

    Infection Probability Index: Implementation of an Automated Chronic Wound Infection Marker

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    The number of people suffering from chronic wounds is increasing due to demographic changes and the global epidemics of obesity and diabetes. Innovative imaging techniques within the field of chronic wound diagnostics are required to improve wound care by predicting and detecting wound infections to accelerate the application of treatments. For this reason, the infection probability index (IPI) is introduced as a novel infection marker based on thermal wound imaging. To improve usability, the IPI was implemented to automate scoring. Visual and thermal image pairs of 60 wounds were acquired to test the implemented algorithms on clinical data. The proposed process consists of (1) determining various parameters of the IPI based on medical hypotheses, (2) acquiring data, (3) extracting camera distortions using camera calibration, and (4) preprocessing and (5) automating segmentation of the wound to calculate (6) the IPI. Wound segmentation is reviewed by user input, whereas the segmented area can be refined manually. Furthermore, in addition to proof of concept, IPIs’ correlation with C-reactive protein (CRP) levels as a clinical infection marker was evaluated. Based on average CRP levels, the patients were clustered into two groups, on the basis of the separation value of an averaged CRP level of 100. We calculated the IPIs of the 60 wound images based on automated wound segmentation. Average runtime was less than a minute. In the group with lower average CRP, a correlation between IPI and CRP was evident

    An Anatomical Thermal 3D Model in Preclinical Research: Combining CT and Thermal Images

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    Even though animal trials are a controversial topic, they provide knowledge about diseases and the course of infections in a medical context. To refine the detection of abnormalities that can cause pain and stress to the animal as early as possible, new processes must be developed. Due to its noninvasive nature, thermal imaging is increasingly used for severity assessment in animal-based research. Within a multimodal approach, thermal images combined with anatomical information could be used to simulate the inner temperature profile, thereby allowing the detection of deep-seated infections. This paper presents the generation of anatomical thermal 3D models, forming the underlying multimodal model in this simulation. These models combine anatomical 3D information based on computed tomography (CT) data with a registered thermal shell measured with infrared thermography. The process of generating these models consists of data acquisition (both thermal images and CT), camera calibration, image processing methods, and structure from motion (SfM), among others. Anatomical thermal 3D models were successfully generated using three anesthetized mice. Due to the image processing improvement, the process was also realized for areas with few features, which increases the transferability of the process. The result of this multimodal registration in 3D space can be viewed and analyzed within a visualization tool. Individual CT slices can be analyzed axially, sagittally, and coronally with the corresponding superficial skin temperature distribution. This is an important and successfully implemented milestone on the way to simulating the internal temperature profile. Using this temperature profile, deep-seated infections and inflammation can be detected in order to reduce animal suffering
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