Collecting and evaluating convalescent plasma for COVID-19 treatment: why and how?

Plasma provided by COVID-19 convalescent patients may provide therapeutic relief as the number of COVID-19 cases escalates steeply worldwide. Prior findings in various viral respiratory diseases including SARS-CoV-related pneumonia suggest that convalescent plasma can reduce mortality, although formal proof of efficacy is still lacking. By reducing viral spread early on, such an approach may possibly downplay subsequent immunopathology. Identifying, collecting, qualifying and preparing plasma from convalescent patients with adequate SARS-CoV-2-neutralizing Ab titres in an acute crisis setting may be challenging, although well within the remit of most blood establishments. Careful clinical evaluation should allow to quickly establish whether such passive immunotherapy, administered at early phases of the disease in patients at high risk of deleterious evolution, may reduce the frequency of patient deterioration, and thereby COVID-19 mortality.     

The acceptability and effectiveness of a questionnaire for the identification of risk factors for HIV and hepatitis B and C: An observational study in general practice

Background: Many people in Europe remain undiagnosed for human immunodeficiency virus (HIV), hepatitis B virus (HBV), hepatitis C virus (HCV).

Objectives: To evaluate acceptability and effectiveness of a questionnaire designed to facilitate identification of risk factors for these viruses.

Methods: We performed an observational study, in a prospectively enrolled cohort of patients in Paris (France) seen in 2014. Eighteen GPs administered a questionnaire to the first 50 patients, collecting information about risk factors. GPs were randomized into two groups: A (self-administered questionnaire) and B (GP-administered questionnaire). We used the overall response rate to assess the acceptability of the questionnaire. We used the rate of newly identified risk factors and compared the number of tests performed one year before and immediately after the intervention to assess the effectiveness of the questionnaire.

Results: 842 patients were randomized: 349 (41.5%) in group A and 493 (58.5%) in group B. Acceptability was 88.5% (95%CI: 86.3–90.6); 93.1% (95%CI: 90.5–95.8) in-group A and 85.2% (95%CI: 82.1–88.3) in group B (P?=?0.0004). Prevalence of risk factors was 51.8% (95%CI: 48.2–54.4) and 58.3% were newly identified (95%CI: 52.9–63.7). The number of HIV tests performed during the four weeks after intervention increased by 27% compared to the same period one year before (P?=?0.22). It increased by 113% (P?=?0.005) and 135% (P?=?0.005) for HBV and HCV, respectively.

Conclusion: The questionnaire proved acceptable and effective in identifying risk factors for HIV, HBV and HCV in general practice.     

Optimal chemotherapy in cancer treatment: state dependent Riccati equation control and extended Kalman filter

In this work, we design a nonlinear state feedback controller based on the State Dependent Riccati Equation (SDRE) technique to eliminate the tumor. One of the most interesting advantages of the SDRE is that it is possible to consider the specific conditions of patients by defining appropriate weights in the cost function and by limiting the administrated drug. Another advantage of this approach is that there are infinite ways to form the state dependent matrices. For each patient, a suitable drug regimen has been obtained using these advantages. A nonlinear model has been utilized to predict the growth of tumor. The model is a system of ODE with four state variables: normal cells, tumor cells, immune cells, and drug concentration. To use the SDRE controller, all state variables must be available for feedback. But for measuring the tumor size, the professional equipment is needed. So, it is impossible to measure the tumor size any time. We suppose that the number of normal cells could be measured in the presence of the Gaussian white noise. Therefore, we can design a state observer to estimate the immeasurable states from measurements. Extended Kalman Filter (EKF) can be used as a state observer for a nonlinear system, and in this work, we use EKF as a nonlinear state observer. Consequently, we can use the SDRE technique just by measuring the normal cell population. Numerical simulations are given to illustrate the design procedure and to show the flexibility of the method. Copyright © 2012 John Wiley & Sons, Ltd.