OBJECTIVE: This paper presents a rescue framework for the transfusion of the best CP to the most critical patients with COVID-19 on the basis of biological requirements by using machine learning and novel MCDM methods.
METHOD: The proposed framework is illustrated on the basis of two distinct and consecutive phases (i.e. testing and development). In testing, ABO compatibility is assessed after classifying donors into the four blood types, namely, A, B, AB and O, to indicate the suitability and safety of plasma for administration in order to refine the CP tested list repository. The development phase includes patient and donor sides. In the patient side, prioritisation is performed using a contracted patient decision matrix constructed between 'serological/protein biomarkers and the ratio of the partial pressure of oxygen in arterial blood to fractional inspired oxygen criteria' and 'patient list based on novel MCDM method known as subjective and objective decision by opinion score method'. Then, the patients with the most urgent need are classified into the four blood types and matched with a tested CP list from the test phase in the donor side. Thereafter, the prioritisation of CP tested list is performed using the contracted CP decision matrix.
RESULT: An intelligence-integrated concept is proposed to identify the most appropriate CP for corresponding prioritised patients with COVID-19 to help doctors hasten treatments.
DISCUSSION: The proposed framework implies the benefits of providing effective care and prevention of the extremely rapidly spreading COVID-19 from affecting patients and the medical sector.
METHODS: This cross-sectional study recruited 120 adult PWE from the Neurology Clinic of the Universiti Kebangsaan Malaysia Medical Centre (UKMMC). Consent-taking was conducted via synchronous or asynchronous approaches, followed by a phone call interview session. The interview collected socio-demographic information, epilepsy-related variables, and vaccination-related variables. Univariate analysis and multiple logistic regression analysis were done to confirm factors associated with the AEFI of COVID-19 vaccination.
RESULTS: Among all types of COVID-19 vaccines, most of the PWE received the Cominarty® COVID-19 vaccination (52.5%). Overall, local AEFI was the quickest to develop, with an average onset within a day. PWE with normal body mass index (BMI) had a higher risk of developing both local and systemic AEFI compared to those underweight and obese PWE (OR: 15.09, 95% CI 1.70-134.28, P = 0.02).
SIGNIFICANCE: COVID-19 vaccines are safe for PWE. AEFI among PWE are similar to those of the general population following COVID-19 vaccination. Therefore, clinicians should encourage PWE to take COVID-19 vaccines.
AREAS COVERED: A literature search was performed using PubMed between December 1, 2019-June 23, 2020. This review highlights the current state of knowledge on the viral replication and pathogenicity, diagnostic and therapeutic strategies, and management of COVID-19. This review will be of interest to scientists and clinicians and make a significant contribution toward development of vaccines and targeted therapies to contain the pandemic.
EXPERT OPINION: The exit strategy for a path back to normal life is required, which should involve a multi-prong effort toward development of new treatment and a successful vaccine to protect public health worldwide and prevent future COVID-19 outbreaks. Therefore, the bench to bedside translational research as well as reverse translational works focusing bedside to bench is very important and would provide the foundation for the development of targeted drugs and vaccines for COVID-19 infections.